1
Chapter 1
INTRODUCTION
A sudden unexpected death during epilepsy (SUDEP) can occur to an unattended epilepsy
sufferer. Reference [1] proposes that, in addition to electroencephalography (EEG) monitoring,
monitoring of cardiac and respiratory physiology is also required for SUDEP monitoring. This
collaborative project investigates the feasibility of developing a miniature, unobtrusive, and selfcontained module that an epilepsy patient could wear in bed and a small bedside alarm unit. The
combined system monitors cessation of breathing or heartbeats to alert healthcare providers to prevent
SUDEP.
The feasibility is studied by developing prototypes of the wearable module and bedside unit. It
is assumed that the wearable module receives an input voltage from a small strip of piezoelectric film
made of polyvinylidine fluoride (PVDF) attached to the patient’s chest. The PVDF sensor voltage
changes in response to both the chest expansion and contraction of breathing and to the chest vibrations
caused by heartbeats. The wearable module performs processing of the PVDF signal and communicates
wirelessly the occurrences of breaths and heartbeats to the bedside unit. The bedside unit calculates
breathing and heart rates and provides an alert on cessation of breathing or heartbeats or when there is a
wireless link failure. The investigation is performed by developing and testing prototypes for the
wearable module and bedside alarm unit. Miss Swetha Seshu Ayyagari designed the hardware for the
signal conditioning circuit and software for digital signal processing to separate out breathing and heart
signals. Mr. Pritam Rajendra Chopda designed the software to detect individual breaths and heartbeats,
transmit detected breaths and heartbeats to the bedside unit, calculate breathing and heart rates, and alert
on cessation of breathing or heartbeats or wireless link failure.
The report is structured as follows: Chapter 2 provides a brief background of the hardware and
microcontroller peripherals used for the breathing and heart monitor. Chapter 3 discusses the
methodologies used for the project. Chapter 4 presents the results of each development phase. Chapter 5
2
contains a brief discussion of the design limitations of the breathing and heart monitor. Chapter 6 gives
the summary, conclusions, and recommendations.
3
Chapter 2
BACKGROUND
Epilepsy is a brain disorder involving repeated spontaneous seizures. A SUDEP is defined as
“sudden, unexpected, witnessed or unwitnessed, nontraumatic and nondrowning death in patients with
epilepsy, with or without evidence for a seizure and excluding documented status epilepticus, in which
postmortem examination does not reveal a toxicologic or anatomic cause for death” [2]. It accounts for
ten percent of all epilepsy related deaths and occurs more commonly among younger adults [2]. Cardiac
arrhythmia, apnea, and cerebral shutdown are three major possible causes of SUDEP. Reference [1]
proposes that electroencephalography (EEG) is not sufficient for SUDEP monitoring. In addition,
SUDEP monitoring requires cardiac and respiratory physiology monitoring. This collaborative project
investigates the feasibility of developing a miniature, unobtrusive, and self-contained module that an
epilepsy patient could wear in bed and a small bedside alarm unit. The combined system is intended to
monitor cessation of breathing or heartbeats.
2.1. Approach
In this work, prototypes of the wearable module and bedside alarm unit are developed. The
wearable module consists of the PVDF sensor, signal conditioning circuit, and signal processing
hardware. It performs data acquisition, extraction of the heart and breathing signals from the PVDF
signal, and detection of heartbeats and breaths. The occurrences of heartbeats and breaths are transmitted
wirelessly from the wearable module to the bedside alarm unit. The bedside alarm unit consists of
firmware for calculation of heart and breathing rates and alerts the user on cessation of heartbeats or
breathing.
2.2. Review of software used for the development
Code Composer Studio v4 (CCS) is an enhanced integrated development environment
4
developed by Texas Instruments, Inc. (Dallas, Texas), for its microcontrollers. “It is an easy to learn tool
with extended features for code generation, debugging, and real time analysis support” [3]. The software
is designed based on an open source framework and is freely distributed with a code size limit of 16 KB
[3], which is sufficient for the project.
2.3. Review of wireless protocol
The wireless protocols considered were Wireless Fidelity (Wi-Fi), Bluetooth, and ZigBee,
which correspond to the IEEE 802.11, 802.15.11, and 802.15.14 standards, respectively.
2.3.1. Wireless Fidelity
Wireless Fidelity is a standard for a wireless local area network (WLAN). The protocol requires
any Wi-Fi enabled device to be connected to an access point [4]. It is a dual band protocol operating in
the unlicensed industrial, scientific, and medical (ISM) bands of 2.4 GHz or 5 GHz. For example, IEEE
802.11/a operates at 5 GHz with a maximum signal rate of 54.0 Mb/s. The power consumption of Wi-Fi
is 725 mW [4].
2.3.2. Bluetooth
Bluetooth is a wireless protocol for a wireless personal area network (WPAN). The protocol
operates in the ISM band at 2.4 GHz. The protocol has a nominal range of 10 m with a maximum signal
rate of 1.0 Mb/s and maximum power consumption of 2.5 mW. The protocol can be used for batteryoperated devices. The disadvantage of Bluetooth is the complex protocol implementation [4].
2.3.3. ZigBee
ZigBee is a wireless protocol that provides a solution for applications such as automation and
control [4]. It allows low power and low bandwidth communication for low-rate wireless personal area
networks (LR-WPANs) [4]. The protocol has a power consumption of 1 mW. It has a maximum signal
rate of 0.250 Mb/s and a response time of 0.5 ms for the device to wake up from sleep mode. The
protocol operates in multiple ISM bands of 868 MHz, 900 MHz, and 2.4 GHz. The network consists of
two types of devices, a full function device (FFD) and a reduced function device (RFD). The FFD can
operate in three modes, a personal area network (PAN) coordinator, coordinator, or device. The RFD
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operates in the device mode and hence utilizes minimal resources. It can communicate only with the
FFD [4]. Table 1 compares the wireless protocols Wi-Fi, Bluetooth, and ZigBee.
Table 1. Wireless protocol comparison.
Characteristic
Wi-Fi
Bluetooth
ZigBee
IEEE specifications
802.11
802.15.1
802.15.4
Frequency band (GHz)
2.4
2.4
2.4
Maximum signal rate
54.0
1.0
0.250
Nominal range (m)
100
10
10-100
Nominal Tx Power (dB)
15-20
0-10
0
Security
High
Medium
High
Protocol complexity
32
151
35
Tx (mA)
219
57
24.7
Rx (mA)
215
47
27
Wakeup time (ms)
Not available
3
0.5
(Mb/s)
(primitives)
2.4. Hardware board review
2.4.1. Microcontroller experimenter’s board
The MSP430FG4618/F2013 Experimenter’s Board from Texas Instruments, Inc. (Dallas,
Texas), as shown in Figure 1 is used for the development of firmware and testing. The experimenter’s
board has a low power MSP430FG4618 microcontroller from Texas Instruments, Inc. The board can be
powered either from a Universal Serial Bus (USB) cable or from AAA batteries. It offers compatibility
with Texas Instrument’s CC2500 wireless transceiver module. The microcontroller board supports
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integrated peripherals, a liquid crystal display (LCD), switches, a buzzer, and a Joint Test Action Group
(JTAG) programming interface [5] as shown in Figure 1.
Figure 1. MSP430FG4618/F2013 Experimenter’s Board [6].
2.4.2. ZigBee transceiver
The ZigBee CC2500EMK Evaluation Module 2.4 GHz from Texas Instruments, Inc. (Dallas,
Texas), as shown in Figure 2, is used in the project. Following are the key features of CC2500 chip. It is
a single-chip 2.4-GHz IEEE 802.15.4 compliant RF transceiver. It has a sleep mode, allowing low power
consumption. The maximum data rate is 250 kbps, and it has a total of 768 bytes of on-chip RAM. It has
a serial peripheral interface (SPI) for interfacing with the MSP430FG4618 microcontroller. The CC2500
EMK Evaluation Module comes with two 2.4 GHz whip antennas.
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2.4.3. Emulation tool
The emulation tool used for programming and debugging is the MSP-FET430UIF module from
Texas Instruments, Inc. The MSP-FET430UIF module is shown in Figure 3. It supports the JTAG
interface and is USB powered.
Figure 2. CC2500EMK Evaluation Module 2.4 GHz [7].
Figure 3. MSP-FET430UIF module [8].
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2.5. Review of MSP430FG4618 microcontroller and its peripherals
The MSP430FG4618 microcontroller belongs to the MSP430x4xx product series from Texas
Instruments, Inc. The peripherals used in this project are the 12-bit successive approximation register
(SAR) analog-to-digital (A/D) converter, 16-bit hardware multiplier, LCD controller, and SPI
communication interface [9].
2.5.1. Memory map
The flash memory of the MSP430FG168 microcontroller consists of 60 KB of main memory
and 256 B of information memory. The main memory of the microcontroller is divided into 120
segments of 512 bytes each, and the information memory is divided into two segments of 128 bytes
each. A memory location of the microcontroller is addressed by a 16-bit word. The flash memory
locations usually are represented using hexadecimal numbers, shown using the prefix ‘0x’ or suffix ‘h’.
The flash memory locations from 0xFFE0 to 0xFFFF are reserved memory addresses for interrupt
vectors [9].
2.5.2. Clock module
The clock module, referred as a frequency locked loop (FLL+), has features that are suitable for
battery operated applications. It provides three clock signals - auxiliary clock (ACLK), master clock
(MCLK), and sub-system master clock (SMCLK). The low frequency ACLK can be configured to
operate on a watch crystal and is used for low power operation. The processor (CPU) and other high
speed peripherals are configured to operate at the MCLK frequency. The SMCLK can be configured
individually for the peripheral modules [9].
The clock module includes multiple clock sources. They are as follows: low frequency/high
frequency oscillator (LFXT1CLK), high frequency oscillator (XT2CLK), and digitally controlled
oscillator (DCOCLK). The LFXT1CLK can be a watch crystal or standard crystals or resonators in the
frequency range of 450 kHz to 8 MHz. The XT2CLK supports standard crystals or resonators in the
frequency range of 450 kHz to 8 MHz and requires external load capacitance [9]. The module also can
use the internal DCOCLK with RC type characteristics, stabilized with the FLL+. The DCOCLK runs on
an external watch crystal connected to ACLK.
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2.5.3. Low power options
The MSP430FG4618 provides five different low power modes, LPM0 to LPM4, to manage
power consumption. The low power mode options are selected using the SCG1, SCG0, OSCOFF, and
CPUOFF bits of the STATUS register. Table 2 shows the STATUS register settings and the
corresponding CPU and clocks status for the different low power modes available in the MSP430FG168
microcontroller. From Table 2, the lowest power mode is LPM4 (idle mode), in which all the clocks are
disabled. In mode LPM3, except for the ACLK, all clocks are disabled. Modes LPM1 and LPM2 allow
an additional clock to be active, which can keep a peripheral on if required. The active mode is used
when the CPU is active, and all the clocks are enabled.
The current consumption of the MSP430FG168 microcontroller in the active mode for 1 MIPS
(Million Instructions Per Second) at a room temperature of 25 oC and a supply voltage of 3 V is 300 A
[9]. In LPM0 mode, the microcontroller consumes about 55 A and only 0.1 A in LPM4 mode [9].
2.5.4. Timer
The MSP430FG4618 has two 16-bit timers, Timer_A and Timer_B. The clock sources for the
timers can be ACLK, SMCLK, or an external input at pin TACLK or pin INCLK. There are four
operating modes available to produce a desired time interval using a 16-bit counter.
Table 3 describes the timer operation modes. Up mode can be used to provide an interrupt when
the timer counts up to a certain value [9]. The counter limit is set to a constant value between 0 and
65535, depending on the desired time period of the interrupt. Once the counter reaches the counter limit,
an interrupt is produced, and the counter starts counting again from zero.
2.5.5. USART peripheral interface
The universal synchronous asynchronous receiver/transmitter (USART) module enables the
microcontroller for serial data communication at a specified baud rate. The MSP430FG4618 has two
USART modules that support SPI and I2C protocols. The SPI mode connects the microcontroller to an
external system via four pins: SIMO, SOMI, UCLK, and STE [9]. It is a synchronous mode of
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communication. The SIMO pin is slave in master out; SOMI is slave out master in; UCLK is the clock;
STE is the slave transmit enable. The STE pin enables the master mode when it is asserted.
Figure 4 shows a typical configuration, in which MSP430FG4618 is the master communicating
with a slave device. The USART contains two shift registers and buffers for transmission and reception.
For transmission, the data written to the transmit buffer are loaded into the transmit shift register. The
data then are driven on the SIMO pin at every clock edge of UCLK. Data received by the slave device’s
data shift register then are loaded into the receive buffer.
Table 2. Low power modes [9].
SCG1
SCG0
OSCOFF
CPUOFF
Mode
CPU and Clocks Status
0
0
0
0
Active
0
1
LPM0
1
0
1
LPM1
1
0
0
1
LPM2
1
1
0
1
LPM3
CPU is active, all enabled clocks are active.
CPU, MCLK are disabled. SMCLK, ACLK
are active.
CPU, MCLK, DCO are disabled. DC
generator is disabled if the DCO is not used
for MCLK or SMCLK in active mode.
SMCLK, ACLK are active.
CPU, MCLK, SMCLK, DCO are disabled.
DC generator remains enabled. ACLK is
active.
CPU, MCLK, SMCLK, DCO are disabled.
DC generator disabled. ACLK is active.
0
0
0
1
1
1
1
LPM4
CPU and all clocks disabled.
Table 3. Timer operation modes [9].
MCx
Mode
00
Stop
01
Up
10
Continuous
11
Up/down
Description
The timer is halted.
The timer repeatedly counts from zero to the value of TACCR0.
The timer repeatedly counts from zero to 0FFFFh.
The timer repeatedly counts from zero up to the value of TACCR0
and back down to zero.
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2.5.6. Supply voltage supervisory circuit
The MSP430FG4168 has a supply voltage supervisory (SVS) circuit that is used to detect low
supply voltage conditions. The microcontroller compares the supply voltage against a threshold voltage
selected by the user using the VLDx bits of the supply voltage supervisory control register (SVSCTL).
Internally, the module contains a comparator, which continuously monitors the voltage to detect a low
voltage condition [9]. When the comparator detects a voltage lower than the set threshold, a flag is set in
the SVSCTL register. The flag has to be cleared through software to restart the supervisory circuit.
Figure 4. USART master and external slave configuration [9].
2.5.7. Interrupts
Interrupt processing occurs when a peripheral asserts its interrupt due to an event. The central
processing unit (CPU) executes its current instruction and starts executing the interrupt service routine
(ISR) requested by the peripheral. The latency for interrupt processing to start is six clock cycles [9]. On
completion of the service routine, the CPU continues with the previous execution. The MSP430FG4618
has three types of interrupts: system reset, non-maskable interrupt, and maskable interrupt. There are
three sources for generating a non-maskable interrupt: an edge on the reset (RST) pin, oscillator fault,
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and access violation to the flash memory. Maskable interrupts can be disabled. They have a global
enable bit (GIE) and an individual enable bit [9].
2.5.8. LCD controller
The LCD controller provides required signals to drive the LCD module. It supports static, 2Mux, 3-Mux, and 4-Mux types of LCDs. The static LCD requires a driver for each segment, while a 2Mux LCD shares a driver between two segments [9]. Similarly, a 3-Mux shares a driver among three
segments, and a 4-Mux shares a driver among four segments. The frame frequency, LCD blinking, and
contrast of the display are configurable.
2.5.9. ADC12 module
The ADC12 module consists of a 12-bit SAR A/D converter. This module can be configured to
choose from various reference sources: on-chip reference voltage (1.5 V or 2.5 V), internal analog
supply voltage, and external reference [9]. The source of the ADC12 module is an internal oscillator,
ADC12OSC. The ADC12OSC runs at 5 MHz. The pulse sample mode is used to provide the sampling
time required by the A/D converter. The module supports four modes. The CONSEQx bits in the
ADC12CTL register are configured to select the conversion mode. Table 4 summarizes all four modes
supported by the module.
Table 4. A/D converter operation modes [9].
CONSEQx
Mode
00
Single channel single-conversion
01
Sequence-of-channels
10
Repeat-single-channel
11
Repeat-sequence-of-channels
Operation
A single channel is
converted once.
A sequence of channels
is converted once.
A single channel is
converted repeatedly.
A sequence of channels
is converted repeatedly.
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2.5.10. Hardware multiplier
The hardware multiplier is a peripheral for performing multiplication and accumulation
operations for applications such as digital signal processing. It has two 16-bit operand registers, OP1 and
OP2. Register OP1 has four selectable addresses to select among the four supported operations [9].
Table 5 summarizes each operation. The peripheral has three result registers, RESLO, RESHI, and
SUMEXT. Register RESLO stores the lower 16 bits of the result. Register RESHI stores the upper 16
bits and is mode dependent. Table 6 summarizes register RESHI contents depending on the operation.
Register SUMEXT stores the sign during the signed operations and the carry bit during an unsigned
multiply accumulate operation. Table 7 summarizes the SUMEXT operation in different modes.
Table 5. Hardware multiplier operation modes [9].
OP1 Address
Register Name
Operation
0130h
MPY
Unsigned multiply.
0132h
MPYS
0134h
MAC
0136h
MACS
Signed multiply.
Unsigned multiply
accumulate.
Signed multiply
accumulate.
Table 6. Hardware multiplier RESHI modes [9].
Mode
MPY
RESHI Contents
MPYS
Upper 16 bits of the result.
The MSB is the sign of the result. The remaining bits are the upper 15 bits of
the result. Two’s complement notation is used for the result.
MAC
Upper 16 bits of the result.
MACS
Upper 16 bits of the result. Two’s complement notation is used for the result.
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Table 7. Hardware multiplier SUMEXT modes [9].
Mode
MPY
MPYS
MAC
MACS
SUMEXT Contents
SUMEXT is always 0000h.
SUMEXT contains the extended sign of the result.
00000h Result is positive or zero.
0FFFFh Result is negative.
SUMEXT contains the carry of the result.
0000h No carry for result.
0001h Result has a carry.
SUMEXT contains the extended sign of the result.
00000h Result is positive or zero.
0FFFFh Result is negative.
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Chapter 3
METHODOLOGY
3.1. Development flow
The development flow is shown in Figure 5. The project started with the study of the PVDF
signal. Recordings of the polyvinylidine fluoride (PVDF), strain-gauge plethysmography (SPG),
electrocardiography (ECG), and photoplethysmography (PPG) signals were analyzed. Based on the
goals of the project, hardware and wireless protocol were chosen. Based on the data analysis,
specifications were derived, followed by design of the prototypes. Further, each individual block in the
system was implemented and tested. In the final step, the complete firmware was integrated and tested.
Analysis of
PVDF signal
Selection of
protocol,
hardware,
and software
Development
of hardware
and firmware
Block level
testing
Final
integration
and testing
Figure 5. Development flow.
3.2. Analysis of PVDF signal
Work done in [10] provided data recordings related to six subjects for PVDF, SPG, ECG, and
PPG signals. The analysis on the signals was done using MATLAB from Mathworks, Inc. (Natick,
Massachusetts). The Fast Fourier transform (FFT) of the recordings was taken, and the results were
plotted. Peaks were identified in the frequency domain plots of the PVDF, SPG and PPG signals. The
ECG signal was not used for the analysis, as the peaks were low in magnitude in comparison with the
peaks of the PPG signal. Therefore, the SPG signal was set as a clinical standard for extraction of the
breathing signal, and similarly the PPG signal was set as a clinical standard for extraction of the heart
signal [10]. The obtained peaks in the PVDF signal were compared with peaks in the frequency domain
16
plots of the clinical standards to identify the fundamental frequency and harmonics of breathing and
heart signals in the PVDF signal. The results were tabulated and were used to develop the hardware and
firmware for the prototypes.
3.3. Design methodology
3.3.1. Selection of hardware and wireless protocol
The goal of this project was to study the feasibility of developing a miniature, unobtrusive, and
self-contained SUDEP monitoring system. Selection of hardware and wireless protocol was done by a
comparative study of low-power and miniature products available in the market by referring to the data
sheets. The system hardware was divided into wearable module and bedside unit for low power
consumption by the wireless transceiver.
3.3.2. Design methodology for hardware
Each individual block in the circuit was designed. The designed circuit was simulated in Pspice
from Cadence Design Systems, Inc. (San Jose, California), to verify if the design met the specifications,
followed by implementation and testing on a prototype board.
3.3.3. Design methodology for software
Each individual block in the software was designed. The designed software was simulated in
MATLAB, followed by implementation and testing on the microcontroller experimenter’s board.
3.4. Testing methodology
3.4.1. Digital filter testing
The PVDF recordings of six subjects [10] were available for testing the digital filters.
Recordings were given as input to both the low-pass and band-pass filters implemented in MATLAB
and the microcontroller of the wearable module. The outputs of both MATLAB and the microcontroller
were compared to verify the implementation of the digital filters.
3.4.2. Extraction and detection of breathing and heartbeats
The PVDF recordings were given as input to the low-pass and band-pass filters implemented in
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the microcontroller of the wearable module. The outputs of the low-pass and band-pass filters were
given to the respective threshold detectors implemented in the microcontroller of the wearable module.
The breaths and heartbeats detected by the respective threshold detectors were tabulated. In the
waveforms of the clinical standards, peaks were identified manually. Each peak in the PPG signal was
tabulated as a heartbeat. A sinusoid pattern observed in the PVDF signal is assumed as a breathing
pattern. For confirming a peak in the SPG signal as a breath, each identified peak was compared with the
breathing pattern in the PVDF signal, and the confirmed peaks were tabulated as breaths. The tabulated
results of the threshold detectors were compared to those of the clinical standards to determine how well
the designed software extracted and detected breaths and heartbeats.
3.4.3. Telemetric alert mechanism
An algorithm implemented in the microcontroller of the wearable module configured the
module’s wireless transceiver to send a data packet at regular intervals. This data packet simulated the
occurrence of a breath or heartbeat. The algorithm varied the rate at which packets were sent to simulate
the cessation of breaths and heartbeats. The result was used to determine the functionality of the alert
mechanism.
3.4.4. Communication failure
An algorithm implemented in the microcontroller of the wearable module disabled the wireless
transceiver, simulating communication failure. The result was used to determine the functionality of
communication failure detection.
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Chapter 4
RESULTS
4.1. Data analysis
The goal of data analysis is to locate the possible frequency regions of breathing and heart
signals in the PVDF signal. The algorithm used for the analysis is shown in Figure 6. Appendix A
contains the MATLAB program for the data analysis.
The data recordings of the PVDF, SPG, and PPG signals for Subject 1 were imported and
stored in three arrays. The average of each recording were calculated and subtracted from every sample
in the recording. The PVDF array values for Subject 1 after subtraction of the average are plotted in
Figure 7. The Fast Fourier transform (FFT) was calculated for each array, and the magnitude was
plotted. The FFT magnitude array for the PVDF recording is plotted in Figure 8.
The FFT magnitude array for the SPG recording for Subject 1 is plotted in Figure 9. The x and
y coordinates for each peak are labeled for the SPG signal in Figure 10. The FFT magnitude array for the
PPG recording is plotted in Figure 11. The x and y coordinates for each peak are labeled for the PPG
signal in Figure 12. The x and y coordinates for each peak are labeled for the PVDF signal in Figure 13.
The x-coordinates for the peaks in Figure 10, Figure 12, and Figure 13 are tabulated in Table 8.
Peaks 1, 2, 3, 5, 6, and 7 for the PVDF and SPG signals match. From the analysis, the frequency region
of the breathing signal is approximated to be from 0 Hz to 0.8 Hz. The frequencies at 0.71 Hz, 1.38 Hz,
and 2.09 Hz in the SPG and the PPG signals overlap. Because of the overlapping frequencies, a digital
filter cannot separate out the heart and breathing signals. Overlapping of the peaks is shown in Figure
14.
To locate another frequency region for the heart signal, further analysis of the PVDF time
domain plot is done. Figure 15 is the zoomed in time domain plot of the PVDF signal from time 8.0 s to
10.5 s. The region represents a single heartbeat in the PVDF signal. The time differences of adjacent
peaks as shown in Figure 15 are computed. Table 9 contains the time differences of the adjacent peaks
19
and frequencies calculated by taking the inverse of the time differences. From the analysis, the
frequency region of the heart signal, shown in Figure 16, is approximated to be from 8 Hz to 40 Hz.
Start
Import the data (PVDF, SPG, and PPG)
Store the data in respective arrays
Compute the average of the samples in the
array
Subtract computed average from individual
samples in the array
Compute the FFT of each array
Compute magnitude of the FFT for each array
Plot amplitude vs. time and magnitude vs.
frequency for each respective signal
Figure 6. Flowchart for MATLAB program for data analysis.
4.2. Hardware structure
The hardware for the portable telemetry breathing and heart monitoring system consists of a
wearable module and bedside unit. The basic functions of the combined system are signal conditioning,
A/D conversion, signal processing, wireless transmission, and alarm if breaths or heartbeats cease or if
20
the wireless link fails. Two possible configurations were considered to divide the functionality between
the wearable module and bedside unit. In the first configuration, signal processing is implemented in the
bedside unit, requiring wireless transmission of every sample by the wearable module. In the second
configuration, signal processing is implemented in the wearable module, requiring wireless transmission
of detected breaths and heartbeats. The breathing and heart rates were lower than the sampling rate. The
power consumption by the wireless transceiver is low if only the detected breaths and heartbeats are
transmitted. Therefore, the second configuration was chosen for implementation.
The implemented wearable module consists of a PVDF sensor, a signal conditioning circuit, an
analog-to-digital converter, a signal processing unit, and a wireless transceiver. The wearable module
processes an incoming PVDF signal, separates out individual breathing and heartbeat signals, detects
individual breaths and heartbeats, and wirelessly transmits them to the bedside unit. The PVDF sensor
was attached to a human subject’s chest, and the output voltage of the PVDF signal was measured using
an oscilloscope. The measured amplitude was approximately -20 mV to + 20 mV. The output of the
PVDF sensor is given to the signal conditioning circuit. The signal conditioning circuit consists of an
amplifier circuit, a switched capacitor low-pass anti-aliasing filter, and a passive low-pass filter. The
amplifier circuit is implemented using the LMC6482, from National Semiconductors, Inc. (Santa Clara,
CA), and the switched capacitor low-pass anti-aliasing filter is implemented using the MAX7427, from
Maxim Integrated Products, Inc. (Sunnyvale, CA). The clock source for the switched capacitor filter is
provided from a function generator. The analog output of the passive low-pass filter is converted to
digitized samples by the A/D converter peripheral of the MSP430FG4618 microcontroller. The output
samples of the A/D converter are given to the signal processing unit. The signal processing unit consists
of a low-pass filter, band-pass filter, and two threshold detectors. The output of the signal processing
unit is given to the wireless transceiver.
The bedside unit consists of a wireless transceiver and an alarm unit. The wireless transceiver
receives the detected breaths and heartbeats. The output of the wireless transceiver is given to the alarm
unit which calculates breathing and heart rates and alarms if breaths or heartbeats cease or if the wireless
link fails.
21
22
23
24
25
26
27
28
29
30
31
Table 8. Summary of fundamental frequencies and harmonics for Subject 1.
Peak
SPG (Hz)
PPG (Hz)
PVDF (Hz)
1
0.22
0.71
0.22
2
0.49
1.38
0.49
3
0.71
2.09
0.71
4
Not available
2.81
0.80
5
0.98
0.98
6
1.38
1.38
7
1.74
1.74
8
2.09
1.92
9
2.10
Table 9. Time intervals between adjacent peaks of a heartbeat for Subject 1.
Time difference between two adjacent
Frequency (Hz)
peaks (s)
8.515 – 8.449 = 0.066
15.00
8.658 – 8.515 = 0.143
6.99
8.737 – 8.658 = 0.079
12.65
8.880 – 8.809 = 0.071
14.00
4.3. Signal conditioning circuit
4.3.1. Amplifier circuit
The input voltage to the amplifier circuit is -20 mV to +20 mV. The output of the amplifier
circuit is connected to the input of switched capacitor low-pass anti-aliasing filter. Therefore, the input
32
resistance and input capacitance of the switched capacitor low-pass anti-aliasing filter act as load
resistance and load capacitance for the amplifier circuit. Therefore, the amplifier circuit is designed for
the input voltage of -20 mV to +20 mV, load resistance of 208 MΩ, and load capacitance of 1 pF. The
load resistance and load capacitance are determined from the datasheet [11]. The other specifications of
this circuit are that the output voltage is to be 0 to 3 V, gain is to be 75 V/V, minimum frequency
response is to be 0 to 50 Hz, and input offset voltage is to be less than the resolution of the A/D
converter (0.732 mV). The voltage resolution of an A/D converter is equal to its overall voltage
measurement range divided by the number of discrete voltage intervals. The overall measurement range
is 3 V. The number of discrete voltage intervals is 2^12. Therefore, 3/(2^12) gives the resolution of
0.732 mV. Figure 17 shows the circuit schematic for the amplifier.
4.3.2. Switched capacitor low-pass anti-aliasing filter
The specifications for the switched capacitor low-pass anti-aliasing filter are that the cut-off
frequency (fc) is to be 48 Hz, stop band frequency (fs) is to be 60 Hz, and stop band rejection is to be
greater than 32 dB. From the datasheet [11], the clock frequency is fc times 100. Therefore, the clock
frequency is 4.8 kHz. Figure 18 shows the circuit schematic for the switched capacitor low-pass antialiasing filter using the MAX7427. The clock signal, with a frequency of approximately 4.8 kHz, was
given from a function generator to the switched capacitor filter. The actual wearable module requires a
low power clock source. The MAX7427 has an internal oscillator which can be configured to act as a
clock source for the switched capacitor low-pass anti-aliasing filter.
4.3.3. Passive low-pass filter
The goal of the passive low-pass filter is to suppress the clock noise introduced by the switched
capacitor filter. The clock frequency of the switched capacitor low-pass anti-aliasing filter is 4.8 kHz.
Therefore, the clock noise is at 4.8 kHz. The specifications for the passive low-pass filter are that the
cut-off frequency (fc) is to be greater than 100 Hz, stop band frequency (fs) is to be 4.8 kHz, and stop
band rejection is to be greater than 32 dB. Figure 19 shows the circuit schematic of the passive low-pass
filter.
DC = 3
AC =
TRAN =
0
0
0
Vcc GND_0
V4
0
VPOT
VOFF = 0
VAMPL = 20m
FREQ = 100
DC = 303m
AC =
TRAN =
0
Vin
Vin
100k
R10
9.63k
R3
0
1.5
133
R11
0
5
+
U1B
6
-
732k
R4
Vdc
R1 9.63k
4
8
Vcc
0
V-
205000000
LMC6482AIN
OUT
7
R2 732k
V+
Amplifier circuit
0
R9
Vout
0
1p
C1
33
34
Figure 18. Circuit schematic of switched capacitor low-pass anti-aliasing filter [11].
Figure 19. Circuit schematic of passive low-pass filter.
4.4. Software structure
The software for the monitoring system is divided into two parts. Part 1 is programmed on the
microcontroller (MCU1) in the prototype of the wearable module attached to the patient’s chest. The
microcontroller is responsible for digitizing the captured PVDF signal, separating out the breathing and
heart signals from the PVDF signal, detecting breaths and heartbeats, and transmitting them to the
microcontroller in the prototype of bedside unit. Part 2 is programmed on the microcontroller (MCU2) in
35
the prototype of the bedside unit. It is responsible for receiving the incoming data, calculating the
breathing and heart rates, and alerting the user in case of cessation of breathing or heartbeats or wireless
communication failure.
Figure 20 shows the main program flow for MCU1. On power-up, MCU1 initializes the clock
sources DCO clock, ACLK, and SMCLK, and the registers for the peripheral modules. The device then
configures the CC2500 of the wearable module for transmission. The device then enters into low power
mode LPM3. Upon the interrupt from Timer_A, that occurs every 1/128 s, the device begins A/D
conversion. The A/D converter output is given to the low-pass digital filter and band-pass digital filter
subroutines. The output of each filter then is passed to an individual threshold detector subroutine. If the
subroutine result is 1, the current sample number is transmitted to MCU2. The C code, based on the flow
in Figure 20, is given in Appendix B.
Figure 21 shows the main program flow for MCU2. On power-up, MCU2 initializes the clock
sources DCO clock, ACLK, SMCLK, and peripheral modules. The device then configures the CC2500
of the bedside unit for reception and enters into low power mode LPM3. Upon an interrupt from the
CC2500, the microcontroller captures the data sent by the CC2500 on the SPI interface. The
microcontroller then decodes the data received as either breath data, heartbeat data, or communication
data and executes the respective subroutine. The C code, based on the flow in Figure 21, is given in
Appendix C.
4.5. Software description
4.5.1. Configuration of clock
The microcontroller MSP430FG4618 has an oscillator called LFXT1. When low-frequency
mode is chosen, it supports a 32768 Hz watch crystal, available on the experimenter’s board. In order to
generate the CPU clock frequency of 4 MHz, two clocks have to be configured, MCLK and ACLK. The
source of ACLK is software-selected as LFXT1. Therefore, the ACLK frequency is equal to the watch
crystal frequency. The DCOCLK is software-selected as the source for the operation of the MCLK. The
DCOCLK frequency is stabilized by the FLL to a multiple of ACLK that can be configured with the help
36
of the lower seven bits of the System Clock Control Register [9]. The relationship is MCLK = (N + 1) *
ACLK. Therefore, N = 121 provides MCLK = 4 MHz with ACLK being 32768 Hz.
Start
Initialize clocks, registers, and variables.
Initialize supply voltage supervisor
Configure Timer_A, A/D converter, IO ports,
and LCD
Configure CC2500 for transmission
Low power mode
No
Timer_A interrupt?
Yes
Start A/D converter sampling
Yes
A/D converter interrupt? No
No
Yes
A/D converter subroutine ()
Figure 20. Flowchart of main program for wearable module’s microcontroller (MCU1).
37
Start
Initialize clocks, registers, and variables.
Initialize Supply voltage supervisor
Configure CC2500 as the reciever
Configure Timer_A, input ports, output
ports, and LCD
Low power mode
No
No
Timer interrupt?
Yes
Timer subroutine ()
CC2500 interrupt?
Yes
CC2500 subroutine ()
Figure 21. Flowchart of main program for bedside unit’s microcontroller (MCU2).
4.5.2. Configuration of Timer_A
The peripheral Timer_A generates an interrupt every 1/128 s. The interrupt starts the sampling
and A/D conversion. The clock source for the timer is the ACLK. Timer operation is configured through
registers Timer_A Counter (TAR) and Timer_A Capture/Compare Register (TACCR0). The timer
generates an interrupt when the value in TAR, incremented every ACLK, matches the value stored in
38
TACCR0 [9]. The TACCR0 is configured to provide a sampling frequency of 128 Hz. The value stored
in the TACCR0 is calculated from the relation TACCR0 = ACLK frequency / Sampling frequency. The
calculated value is 256.
4.5.3. Configuration of A/D converter
The A/D converter generates an interrupt after sampling and conversion. The interrupt starts the
execution of a subroutine for the digital filters. The clock source for the converter is ADC12OSC. The
ADC12DIV bits are configured to divide the ADC12OSC frequency (5 MHz) to 1 MHz. Figure 22
shows the method for calculating the sample and hold time (tsample). The output resistance (Rs) of the
passive low-pass filter is 4100 Ω. The input resistance of the A/D peripheral (Ri) is 2000 Ω, and the
input capacitance of the A/D peripheral (Ci) is 40 pF. Substituting the values of Rs, Ri, and Ci in the
equation given in Figure 22, tsample is calculated to be greater than 3 µs. Therefore, the SHTx bits are
configured to provide the tsample of 4 µs.
Figure 22. Method for calculating sample and hold time (tsample) [9].
39
4.5.4. Digital signal processing
The frequency region of interest for the breathing signal is 0 to 0.8 Hz and for the heart signal is
8 to 40 Hz. Therefore, the cut-off frequency of the low-pass filter is 0.8 Hz with an attenuation of 32 dB
in the transition band. The band-pass filter’s lower cut-off frequency is 8 Hz and upper cut-off
frequency is 40 Hz. The attenuation required in the transition band is 32 dB. The flowchart in Figure 23
describes the procedure to design the digital filters. The MATLAB code for Figure 23 is given in
Appendix D. Hamming windows with 119 taps for the low-pass filter and 129 taps for the band-pass
filter give frequency responses as shown in Figures 24 and 25. The flow chart in Figure 26 describes the
implementation of the digital filter algorithm. The coefficients of the digital filters are given in Appendix
E, and the MATLAB code for Figure 26 is given in Appendix F.
4.5.5. Breath threshold detector
The breath threshold detector takes the output of the low-pass digital filter as its input and
compares the output to a threshold to determine if the output can be considered as a breath. Figure 27
shows the algorithm for the breath threshold detector. The algorithm is implemented as a subroutine and
consists of two steps. The active step sets the threshold value to lower_threshold or upper_threshold.
Step 1 compares the input with lower_threshold, and step 2 compares it with upper_threshold.
On power-on, step 1 is set as active. The subroutine initializes variables and thresholds upon
start of execution. The input then is compared with lower_threshold, and if greater than that threshold,
step 2 is set as active, and step 1 is cleared. The subroutine exits by returning 0. On the next execution,
the input is compared with upper_threshold, and if greater than that threshold, step 1 is set as active, and
step 2 is cleared. The subroutine exits by returning 1.
40
Start
Enter the number of taps for lowpass and band-pass filters
Design of windowed FIR filter
using MATLAB toolbox function FIR1
Compute the frequency response of
the digital filter using Freqz
function in MATLAB
Compute magnitude response
No
Does the response
meet specifications?
Change the number of taps
and window type
Yes
Store the coefficients
Stop
Figure 23. Design procedure for required digital filter frequency response.
41
Magnitude Response (dB)
0
Frequency: 0.796875
Magnitude: -3.016072
-10
-20
Frequency: 2.328125
Magnitude: -32.19386
-30
Magnitude (dB)
-40
-50
-60
-70
-80
-90
-100
0
2
4
6
8
10
12
14
16
18
20
Frequency (Hz)
Figure 24. Low-pass digital filter frequency response with a cut-off frequency of 0.8 Hz.
42
Magnitude Response (dB)
0
Frequency: 8
Frequency: 40.00781
Magnitude: -2.999898
Magnitude: -3.046397
-10
-20
Frequency: 6.28125
Magnitude (dB)
Magnitude: -31.88956
-30
Frequency: 41.71875
Magnitude: -32.06283
-40
-50
-60
-70
0
10
20
30
40
50
60
Frequency (Hz)
Figure 25. Frequency response of band-pass filter with lower cut-off frequency at 8 Hz and upper
cut-off frequency at 40 Hz.
4.5.6. Heartbeat threshold detector
The heartbeat threshold detector takes the output of the band-pass digital filter as its input and
compares the output to a threshold to determine if the output can be considered as a heartbeat. Figure 28
shows the algorithm for the heartbeat threshold detector. The algorithm is implemented as a subroutine
and consists of two steps. The active step sets the threshold value to lower_threshold or upper_threshold.
Step 1 compares the input with lower_threshold, and step 2 compares it with upper_threshold.
43
Start
Store order, coefficients, and
samples
Initialize variables
Store the current sample pointed to
the index
No
Is i less
than taps?
Load the coefficients
Is j equal
to zero?
No
Load the sample in OP2
register and decrement j
Yes
Load the sample in OP2
register and set j to end of
circular buffer
Is circular buffer
filled?
No
Yes
Reset the index
Increment index
Return
Figure 26. Flowchart for digital filter implementation in the microcontroller.
44
Compare_brate()
Initialize variables and threshold
values.
Yes
Is value < lowerthreshold?
Is br_step_1 set?
No
Yes
Set br_step_2, clear
br_step_1, return 0;
Is br_step_2 set?
No
Yes
Set br_step_1, clear
br_step_2, return 0;
No
Is value > upperYes
threshold?
Set br_step_1, clear
br_step_2, return 0;
Yes
Set br_step_1, clear
br_step_2, return 1;
Set br_step_2, clear
br_step_1, return 0;
Figure 27. Flowchart for breath threshold detector.
No
45
Compare_hrate()
Initialize variables and
threshold values.
Yes
Is hr_step_1
set?
Yes
No
Is hr_step_2
set?
Is value > lowerThreshold?
No
Set hr_step_2, clear
hr_step_1, return 0;
Set hr_step_1, clear
hr_step_2, return 0;
Yes
Is value > upperthreshold and last_act
> 64?
Set hr_step_1, clear
hr_step_2, return 0;
No
No
Yes
Set hr_step_1, clear
hr_step_2, return 1;
Set hr_step_2, clear
hr_step_1, return 0;
Figure 28. Flowchart for heartbeat threshold detector.
On power-on, step 1 is set as active. The subroutine initializes variables and thresholds upon
start of execution. The input then is compared with lower_threshold. If the input is greater than that
threshold, step 2 is set as active, and step 1 is cleared. The subroutine exits by returning 0. On the next
execution, the input then is compared with upper_threshold. If the input is greater than that threshold,
and the previous heartbeat was detected before for a minimum of 64 inputs, step 1 is set as active, and
step 2 is cleared. The subroutine exits by returning 1. The maximum heart rate was assumed to be 2 Hz,
46
and the sampling rate for the A/D conversion was 128 Hz. Therefore, any input before 64 inputs cannot
be a heartbeat.
4.5.7. Data transmission
The CC2500 ZigBee transceiver can be interfaced with the microcontroller using the USART
SPI peripheral on the microcontroller. The two devices are configured such that the microcontroller is
the master and the CC2500 is a slave. The configuration is similar to the one depicted in Figure 4. The
threshold detectors on detection of a breath or heartbeat update a 32-bit register with the current sample
number. Sample number is the count in a 32-bit register that is incremented every time the A/D
converter samples the input signal. Figure 29 shows the algorithm for data transmission. After the start
of the A/D converter subroutine and completion of digital filtering, the breath threshold detector
subroutine is executed. If the subroutine returns 1 as its result, then a packet is prepared, and the
subroutine for packet transmission is executed. The microcontroller waits in low power mode until the
packet is sent. After the breath packet is sent or if the breath detector subroutine returns a 0, then the
heartbeat threshold detector subroutine is executed. If the subroutine returns 1 as its result, then a packet
is prepared, and the subroutine for packet transmission is executed. The microcontroller waits in low
power mode until the packet is sent and then exits the subroutine. The packet contains fields for length
of packet, address of the receiver (set to default 1d), data from the count register, and data identity. The
packet identity is stored in a register called data_id. The register data_id indicates if the packet is for a
breath (0xbb), heartbeat (0xff), or communication check (0xcc).
4.5.8. Supply voltage monitor
The supply voltage monitor (SVS) peripheral in the microcontroller monitors the supply voltage
for a set threshold voltage. The flash RAM present on the microcontroller operates at a minimum of 2.7
V and thus is the deciding factor for the threshold voltage. The algorithm implemented for the SVS is
shown in Figure 30. On power-up, the microcontroller initializes the SVSCTL register in the
microcontroller of the wearable module to select the threshold voltage at 2.7 V. The SVSCTL register
was set to 0x1000. Upon detection of a lower voltage, a red light emitting diode (LED) on the
MSP430FG4618/F2013 Experimenter’s Board is turned on, and the program execution is halted.
47
Figure 29. Flowchart for data transmission.
48
Power up the
microcontroller
Initialize variables, and set the
SVSCTL value to 2.7 V
Initialize other peripherals and
other registers
Resume execution of
the main program
Is SVSCTL Flag
set?
Yes
No
Low power mode
Execution of main
program stopped
Figure 30. Flowchart for supply voltage supervisor.
4.5.9. Calculation of breathing and heart rates
The bedside unit calculates the breathing and heart rates. The algorithm implemented for the
calculation is given in Figure 31 and continued to Figure 32. The microcontroller in the bedside unit,
upon receiving an interrupt from the CC2500, captures the packet received by the CC2500. The packet is
decoded for two fields, packet identity and sample number. The packet identity is stored in a register
called data_id. If the data_id is 0xbb, then the sample number is stored in variable sample_number and is
used for calculating the breathing rate. If the data_id is 0xff, then the count_data is used for calculating
the heart rate. If the data_id is 0xcc, then the communication link check subroutine is executed. If the
data_id is 0xbb, and if sample_number is greater than the previous sample number stored in register
49
CC2500 interrupt ()
Capture the packet received
by CC2500
Decode packet for packetid and count data.
Is packet-id hh?
Yes
1
No
Is packet-id bb?
Yes
No
Calculate breathing
rate
2
No
Is packet-id cc?
Calculate heartbeat
rate
Yes
Check the received
data
3
Exit CC2500 interrupt
subroutine
Figure 31. Flowchart for the CC2500 interrupt for MCU2 (continued to Figure 32).
50
2
1
Is newdata >
olddata?
No
Is newdata >
olddata?
Yes
No
Yes
interval = newdata –
olddata
interval = newdata –
olddata
heartrate = constant/
interval
breathrate = constant/
interval
interval = Hex FFFFFFFF
– olddata + newdata
interval = Hex FFFFFFFF
– olddata + newdata
Exit CC2500 interrupt
subroutine
Exit CC2500 interrupt
subroutine
3
Data match?
Yes
Set comm_link_good
No
Display error message
on LCD
Exit CC2500 interrupt
subroutine
Figure 32. Flowchart for the CC2500 interrupt for MCU2 (continued from Figure 31).
51
br_temp_sample, then br_temp_sample is subtracted from sample_number to calculate the interval. The
variable br_interval stores the time difference between two consecutive detected breaths and is used to
calculate the breathing rate. If sample_number is less than br_temp_sample, then the counter in the
microcontroller of the wearable module has overflowed, and hence br_temp_sample is subtracted from
xFFFFFFFF and added to sample_number to calculate the interval. A similar algorithm is implemented
for calculating heart rate when data_id is 0xff.
4.5.10. Alarm unit
The alarm unit is implemented in the microcontroller of the bedside unit. The algorithm for the
alarm unit is shown in Figure 33. The Timer_A peripheral generates an interrupt at a regular interval.
Upon receiving the interrupt, the current breathing rate is compared with a threshold. If lower than the
minimum breathing rate [10], then the subroutine checks if a packet was received after the last interrupt.
If yes, communication between the wearable module and bedside unit is good. The user is notified by
flashing the LED and turning on the buzzer of the bedside unit. If no, then heart rate is compared with a
threshold. If the heart rate is lower than the minimum heart rate [10], then the subroutine checks if a
packet was received after the last interrupt. If yes, communication between the wearable module and
bedside unit is good. If no, then an error message is printed on the LCD of the bedside unit.
4.6. Testing results
4.6.1. Signal conditioning circuit
The amplifier circuit shown in Figure 17 was simulated in Pspice to verify the gain, output
voltage, and frequency response. The circuit was designed for an input voltage of -20 mV to +20 mV
and output voltage of 0 V to 3 V. The plot in Figure 34, generated by choosing the time domain sweep
analysis in Pspice, verifies the input and output voltages of the circuit. Figure 35 is an alternating current
(AC) sweep analysis plot generated in Pspice, verifying a gain of 75 for the minimum frequency
response of 0 Hz to 50 Hz. The amplifier circuit was implemented on a prototype board. The circuit was
52
tested in the laboratory with a 40-mV peak-to-peak, approximately 31-Hz sine wave as the input signal,
as shown in Figure 36. Figure 37 verifies the output signal of the circuit, 0 to 3 V.
Timer_A interrupt
subroutine
Is breath rate <
threshold?
Yes
Is communication
link good?
No
Is heart rate <
threshold?
Yes
Yes
Flash LED, BUZZER ON
No
Is communication
link good?
No
Yes
Exit Timer_A subroutine
No
DISPLAY ERR on LCD
Figure 33. Flowchart for the alarm unit.
The switched capacitor low-pass anti-aliasing filter was implemented on a prototype board.
The filter was tested with a 0 to 3 V peak-to-peak sine wave. The frequency of the sine wave was varied
from 0 Hz to 60 Hz to verify the frequency response. The results are tabulated in Table 10. The stop
53
band rejection of the switched capacitor filter is the ratio of the pass band output voltage to the stop band
output voltage. The pass band output voltage is 3 V, and the stop band output voltage is 40 mV.
Therefore, the stop band rejection is 37.5 dB, thus satisfying the design requirement of more than 32 dB
at 60 Hz.
Figure 34. Plot verifying input voltage of -20 mV to +20 mV and output voltage of 0 V to 3 V of
amplifier circuit.
54
The passive low-pass filter circuit was simulated in Pspice to verify the required frequency
response, that is, a cut-off frequency at 300 Hz and attenuation greater than 32 dB at 4.8 kHz. The plot of
the frequency response of the filter is given in Figure 38. Figure 39 is the signal conditioning circuit
implemented on a prototype board.
Figure 35. Plot of closed loop frequency response of amplifier circuit verifying gain of 75 for
minimum frequency response of 0 Hz to 50 Hz.
55
Figure 36. Input signal (-20 mV to +20 mV) to the amplifier circuit.
Figure 37. Output signal (0 V to 3 V) of amplifier circuit.
56
Figure 38. Plot of frequency response of passive low-pass filter circuit with output voltage = 0.024
V at 4.8 kHz for an input voltage of 1 V.
Figure 39. Signal conditioning circuit implemented on a prototype board.
57
Table 10. Testing results of switched capacitor low-pass anti-aliasing filter.
Frequency (Hz)
Output (V)
0.5
3.0
2.0
3.0
4.0
3.0
8.0
3.0
10.0
3.0
14.0
3.0
20.0
3.0
30.0
3.0
40.0
3.0
44.0
3.0
48.0
0.9
50.0
0.8
60.0
0.04
4.6.2. Signal processing
The A/D converter sampling frequency is 128 Hz. In reference [10], the PVDF recordings were
sampled at 1000 Hz. For testing purposes, the PVDF recordings were resampled at 125 Hz, as 1000 is an
integer multiple of 125 Hz, and 125 Hz is closest to 128 Hz.
The consequence of sampling at 125 Hz instead of 128 Hz is explained through an example.
Consider a 1-Hz sinusoid. This sinusoid is sampled at 125 Hz (125 samples represent exactly one
complete cycle of the sinusoid). The samples are fed into the digital filter algorithms. The filters assume
that the samples were taken at 128 Hz. Therefore, the filters will see a sinusoid that has a higher
frequency of 128/125 = 1.024 Hz. This same phenomenon applies for all frequency components.
Therefore, sampling at 125 Hz instead of 128 Hz will result in a 2.4% increase for all frequency
components. This increase of 2.4% is assumed to have a negligible effect on signal processing.
58
The recordings of the PVDF signal for six subjects were sampled at 125 Hz to give 2801
samples for each subject. These 2801 samples were given to the low-pass and band-pass filters
implemented in both the microcontroller and MATLAB. Figures 40, 41, and 42 are the time domain
plots of the PVDF, SPG, and PPG signals, respectively. The outputs of the digital filters implemented in
MATLAB are used to generate the time domain plots as show in Figures 43 and 44 for Subject 1. Figure
43 is the output of the low-pass filter that represents the breathing signal in the PVDF signal, and Figure
44 is the output of the band-pass filter that represents the heart signal in the PVDF signal. In this section,
results related to Subject 1 are presented. Results related to the six subjects are presented in Appendix G.
Table 11 shows the outputs of the low-pass filter obtained for samples 1100 to 1120 for Subject
1 and Subject 2 from MATLAB and the microcontroller. Table 12 shows the outputs of the band-pass
filter obtained for samples 1100 to 1120 for Subject 1 and Subject 2 from MATLAB and the
microcontroller. Table 11 and Table 12 verify that the digital filters are implemented correctly, as the
outputs of the microcontroller and MATLAB are equal.
1500
1000
500
Amplitude
0
-500
-1000
-1500
-2000
0
5
10
15
20
Time (s)
Figure 40. Time domain plot of PVDF signal for Subject 1.
25
59
150
100
Amplitude
50
0
-50
-100
-150
0
5
10
15
20
25
Time (s)
Figure 41. Time domain plot of SPG signal for Subject 1.
500
400
300
Amplitude
200
100
0
-100
-200
0
5
10
15
20
Time (s)
Figure 42. Time domain plot of PPG signal for Subject 1.
25
60
7
x 10
1.5
1
Amplitude
0.5
0
-0.5
-1
-1.5
0
5
10
15
20
25
Time(s)
Figure 43. Time domain plot of breathing signal in the PVDF signal for Subject 1.
7
x 10
3
2
1
Amplitude
0
-1
-2
-3
-4
0
5
10
15
20
25
Time (s)
Figure 44. Time domain plot of heart signal in the PVDF signal for Subject 1.
61
Table 11. Output of low-pass filter for Subject 1 and Subject 2.
Outputs of low-pass filter for
Outputs of low-pass filter for
Subject 1
Subject 2
sample
MATLAB
Microcontroller
MATLAB
Microcontroller
1101
-1425
-1425
-2865
-2865
1102
-3320
-3320
-6326
-6326
1103
-5920
-5920
-10545
-10545
1104
-8984
-8984
-15764
-15764
1105
-12326
-12326
-21582
-21582
1106
-16059
-16059
-27981
-27981
1107
-20026
-20026
-35401
-35401
1108
-23877
-23877
-44251
-44251
1109
-27827
-27827
-54369
-54369
1110
-31667
-31667
-66244
-66244
1111
-35474
-35474
-79421
-79421
1112
-40261
-40261
-94083
-94083
1113
-46879
-46879
-110676
-110676
1114
-55124
-55124
-129036
-129036
1115
-64073
-64073
-149299
-149299
1116
-71440
-71440
-171719
-171719
1117
-75960
-75960
-196722
-196722
1118
-83844
-83844
-224333
-224333
1119
-94252
-94252
-254947
-254947
1120
-106611
-106611
-288482
-288482
4.6.3. Breath detector test
The breaths detected by the breath threshold detector were compared with the breaths from the
gold standard SPG signal. A true peak is a peak in the gold standard SPG signal. A false peak is a peak
detected by the threshold detector but absent in the gold standard SPG signal. A missed peak is a peak
not detected by the threshold detector but present in the gold standard SPG signal. The threshold values
62
were determined by analyzing all of the low-pass digital filter plots obtained in MATLAB. The lower
threshold was set to 00000000, as there was always a zero crossing between consecutive true peaks. For
calculation of the higher threshold, the amplitude of the lowest true peak in the time domain plot of the
breathing signal in the PVDF signal for each subject was noted. Then the average of the noted
amplitudes was taken. The calculated average value was rounded off to 11000000, which was set as the
Table 12. Output of band-pass filter for Subject 1 and Subject 2.
Outputs of band-pass filter for
Outputs of band-pass filter
Subject 1
for Subject 2
Sample
Matlab
Microcontroller
Matlab
Microcontroller
1101
-2375
-2375
-4775
-4775
1102
-3380
-3380
-6214
-6214
1103
-5120
-5120
-8559
-8559
1104
-8176
-8176
-14592
-14592
1105
-9105
-9105
-15817
-15817
1106
-9229
-9229
-14949
-14949
1107
-10008
-10008
-18128
-18128
1108
-7521
-7521
-16583
-16583
1109
-3086
-3086
-9858
-9858
1110
657
657
-9140
-9140
1111
6414
6414
-4997
-4997
1112
12807
12807
6722
6722
1113
14073
14073
8774
8774
1114
14041
14041
9191
9191
1115
15018
15018
18737
18737
1116
12579
12579
15548
15548
1117
9948
9948
3149
3149
1118
1780
1780
4008
4008
1119
-7775
-7775
-6141
-6141
1120
-19363
-19363
-30672
-30672
63
upper threshold.
The results obtained for six subjects are tabulated in Table 13 for Subject 1, Table 14 for
Subject 2, Table 15 for Subject 3, Table 16 for Subject 4, Table 17 for Subject 5, and Table 18 for
Subject 6. A result is determined to be a true positive if the detected breath is present in the gold
standard. A result is determined to be a false positive if the detected breath is not present in the gold
standard. Table 19 tabulates the percentage of true positive and false positive for each subject. The true
positive percentage for each subject is calculated from the equation [(True peaks – Missed peaks) / (True
peaks )] * 100. The false positive percentage for each subject is calculated from the equation [False
peaks / True peaks ] * 100.
Table 13. Results of breathing threshold detector for Subject 1.
Breath
Number
1
2
3
4
5
Count register value
from the
microcontroller.
133
651
1186
1887
2442
Sample for
breathing peak in
SPG recording.
216
692
1211
1842
2500
Remark
True peak (TP)
False peak (FP)
Missed peak (MP)
True peak
True peak
True peak
True peak
True peak
Table 14. Results of breathing threshold detector for Subject 2.
Breath
Number
1
2
3
Count register value
from the
microcontroller.
1447
2131
2537
Sample for
breathing peak in
SPG recording.
1603
2160
2679
Remark
True peak (TP)
False peak (FP)
Missed peak (MP)
True peak
True peak
True peak
64
Table 15. Results of breathing threshold detector for Subject 3.
Breath
Number
1
2
3
Count register value
from the
microcontroller.
Not detected
Not detected
Not detected
Sample for
breathing peak in
SPG recording.
303
1508
2210
Remark
True peak (TP)
False peak (FP)
Missed peak (MP)
Missed peak
Missed peak
Missed peak
Table 16. Results of breathing threshold detector for Subject 4.
Breath
Number
1
2
Count register value
from the
microcontroller.
399
Not detected
Sample for
breathing peak in
SPG recording.
40
2375
Remark
True peak (TP)
False peak (FP)
Missed peak (MP)
True peak
Missed peak
Table 17. Results of breathing threshold detector for Subject 5.
Breath
Number
1
2
3
4
Count register value
from the
microcontroller.
822
1519
2056
2734
Sample for
breathing peak in
SPG recording.
923
1555
2125
2750
Remark
True peak (TP)
False peak (FP)
Missed peak (MP)
True peak
True peak
True peak
True peak
Table 18. Results of breathing threshold detector for Subject 6.
Breath
Number
1
2
3
Count register value
from the
microcontroller.
Not detected
Not detected
2187
Sample for
breathing peak in
SPG recording.
267
1455
2250
Remark
True peak (TP)
False peak (FP)
Missed peak (MP)
Missed peak
Missed peak
True peak
65
Table 19. Summary of breathing threshold detector for six subjects.
Subject
number
True positive %
False positive %
1
100
0
2
100
0
3
0
0
4
50
0
5
100
0
6
33
0
4.6.4. Heartbeat detector test
The heartbeats detected by the heartbeat threshold detector were compared with the heartbeats
from the gold standard PPG signal. A true peak is a peak in the gold standard PPG signal. A false peak is
a peak detected by the threshold detector but absent in the gold standard PPG signal. A missed peak is a
peak not detected by the threshold detector but present in the gold standard PPG signal. The threshold
values were determined by analyzing all of the band-pass digital filter plots obtained in MATLAB. The
lower threshold was set to 00000000, as there was always a zero crossing between consecutive true
peaks. For calculation of the higher threshold, the amplitude of the lowest true peak in the time domain
plot of breathing signal in the PVDF signal for each subject was noted. Then the average of the noted
amplitudes was taken. The calculated average value was rounded off to 15000000, which was set as the
upper threshold.
The results obtained for six subjects are tabulated in Table 20 for Subject 1, Table 21 for
Subject 2, Table 22 for Subject 3, Table 23 for Subject 4, Table 24 for Subject 5, and Table 25 for
Subject 6. A result is determined to be a true positive if the detected heartbeat is present in the gold
standard. A result is determined to be a false positive if the detected heartbeat is not present in the gold
standard. Table 26 tabulates the percentage of true positive and false positive for each Subject. The true
positive percentage for each subject is calculated from the equation [(True peaks – Missed peaks) / (True
66
peaks )] * 100. The false positive percentage for each subject is calculated from the equation [False
peaks / True peaks ] * 100.
Table 20. Results of heartbeat threshold detector for Subject 1.
Heartbeat
Number
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Count register value
from the
microcontroller.
Sample for
heartbeat peak in
PPG recording.
Not detected
231
406
591
764
943
1172
1295
1480
Not detected
1880
2008
2200
2429
2554
Not detected
33
203
377
553
735
914
1093
1266
1441
1626
1799
2001
2161
2349
2523
2701
Remark
True peak (TP)
False peak (FP)
Missed peak (MP)
Missed peak
True peak
True peak
True peak
True peak
True peak
True peak
True peak
True peak
Missed peak
True peak
True peak
True peak
True peak
True peak
Missed peak
67
Table 21. Results of heartbeat threshold detector for Subject 2.
Heartbeat
Number
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
Count register value
from the
microcontroller.
Sample for
heartbeat peak in
PPG recording.
132
302
472
651
838
1014
1189
1367
1547
1716
1890
2072
2124
2246
2423
2598
2770
100
272
441
621
808
985
1162
1338
1518
1689
1861
2043
Absent
2217
2394
2569
2741
Remark
True peak (TP)
False peak (FP)
Missed peak (MP)
True peak
True peak
True peak
True peak
True peak
True peak
True peak
True peak
True peak
True peak
True peak
True peak
False peak
True peak
True peak
True peak
True peak
68
Table 22. Results of heartbeat threshold detector for Subject 3.
Heartbeat
Number
Count register value
from the
microcontroller.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Not detected
Not detected
Not detected
Not detected
Not detected
Not detected
Not detected
Not detected
Not detected
Not detected
Not detected
Not detected
Not detected
Not detected
Not detected
Not detected
Not detected
Not detected
Not detected
Not detected
Sample for
heartbeat peak in
PPG recording.
100
250
376
496
624
750
880
1100
1250
1352
1498
1635
1786
1884
2010
2136
2273
2412
2589
2735
Remark
True peak (TP)
False peak (FP)
Missed peak (MP)
Missed peak
Missed peak
Missed peak
Missed peak
Missed peak
Missed peak
Missed peak
Missed peak
Missed peak
Missed peak
Missed peak
Missed peak
Missed peak
Missed peak
Missed peak
Missed peak
Missed peak
Missed peak
Missed peak
Missed peak
69
Table 23. Results of heartbeat threshold detector for Subject 4.
Heartbeat
Number
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
Count obtained from
microcontroller
Sample for peak
in PPG recording.
Not detected
159
273
386
502
642
801
965
1116
1257
1398
1524
1669
1804
Not detected
Not detected
Not detected
2219
2415
2533
2653
Not detected
22
140
252
361
473
614
770
934
1088
1229
1370
1508
1642
1780
1909
2032
2150
2272
2391
2509
2630
2779
Remark
True peak (TP)
False peak (FP)
Missed peak (MP)
Missed peak
True peak
True peak
True peak
True peak
True peak
True peak
True peak
True peak
True peak
True peak
True peak
True peak
True peak
Missed peak
Missed peak
Missed peak
True peak
True peak
True peak
True peak
Missed peak
70
Table 24. Results of heartbeat threshold detector for Subject 5.
Heartbeat
Number
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
Count register value
from the
microcontroller.
Sample for
heartbeat peak in
PPG recording.
65
174
303
430
546
663
771
879
992
1111
1240
1370
1439
1505
1616
1729
1863
1944
2127
2230
2307
2396
2473
2599
2729
25
139
269
395
511
628
737
843
956
1074
1202
1332
1461
Absent
1580
1698
1826
1954
2078
2195
2313
Absent
2438
2563
2694
Remark
True peak (TP)
False peak (FP)
Missed peak (MP)
True peak
True peak
True peak
True peak
True peak
True peak
True peak
True peak
True peak
True peak
True peak
True peak
True peak
False peak
True peak
True peak
True peak
True peak
True peak
True peak
True peak
False peak
True peak
True peak
True peak
71
Table 25. Results of heartbeat threshold detector for Subject 6.
Heartbeat
Number
Count register value
from the
microcontroller.
Sample for
heartbeat peak in
PPG recording.
67
132
222
296
369
453
676
796
933
1009
1185
1310
1439
1567
1696
1812
1936
2068
2158
2260
2331
2411
2486
2554
2646
2747
74
Absent
182
278
366
500
628
757
884
1011
1137
1262
1391
Absent
1649
1779
1902
2019
2124
2221
2316
2405
2503
2609
2712
2694
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
Remark
True peak (TP)
False peak (FP)
Missed peak (MP)
True peak
False peak
True peak
Correct detection
True peak
True peak
True peak
True peak
True peak
True peak
True peak
True peak
True peak
False peak
True peak
True peak
True peak
True peak
True peak
True peak
True peak
True peak
True peak
True peak
True peak
True peak
Table 26. Summary of heart threshold detector for six subjects.
Subject number
1
2
3
4
5
6
True positive %
100
100
0
77
100
100
False positive %
0
6
0
0
8
8
72
Chapter 5
LIMITATIONS
The hardware amplifier operates with a fixed gain of 75. This gain is designed for a PVDF
signal of -20 mV to +20 mV. However, the PVDF signal amplitude can vary from patient to patient. The
prototype system does not adapt to changing PVDF signal amplitudes from subject to subject.
If there is a decrease in the amplitude of the PVDF signal, the output of the amplifier will decrease,
reducing the maximum expected value at the digital filter outputs. Therefore, the current thresholds will
not function as desired and have to be changed to new values. If there is an increase in the amplitude of
the PVDF signal, the output of the amplifier will saturate, causing loss of signal information.
In this design, the clock to the switched capacitor low-pass anti-aliasing filter was provided
externally from a function generator. Therefore, the prototype system does not have a low power clock
source for the switched capacitor filter. The MAX7427 has an internal oscillator, which can be
configured to act as a clock source for the switched capacitor low-pass anti-aliasing filter.
No measurements were made of the power consumption of the wearable module electronics.
Therefore, at present, battery size to achieve a given operating time is not known.
In reference [10], the PVDF recordings were sampled at 1000 Hz. The signal processing
algorithms were designed for a sampling frequency of 128 Hz. For testing of the signal processing
algorithms, every eighth sample in the PVDF recording was given as an input to the algorithms.
Therefore, the sampling frequency is 1000/8 = 125 Hz. This sampling of 125 Hz instead of 128 Hz has
resulted in 2.4% increase for all frequency components seen by the digital filters. This 2.4% error is
assumed to have a negligible effect on signal processing. This error can be avoided by constructing a
waveform from the PVDF recordings using interpolation, and then sampling at 128 Hz. Linear
interpolation can be used to join two samples by a straight line to give a continuous curve.
No study was done regarding whether the order of the filters can be reduced. If the order of the
filter is reduced, then the processing time required by the microcontroller is decreased, thus reducing
power consumption.
73
The prototype uses whip antennas provided in the CC2500 EMK Evaluation module. Such
antennas, due to their large size, would cause discomfort to the patient. A possible replacement to the
whip antennas can be folded dipole printed circuit board antennas.
74
Chapter 6
SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS
6.1. Summary
Analysis of human subject recordings of PVDF, SPG, and PPG signals was done to understand
how to design a portable telemetry breathing and heart monitoring system. The analysis showed that the
frequency region of interest for the breathing signal is approximately 0 Hz to 0.8 Hz, and that of the
heart signal is approximately 8 Hz to 40 Hz. The PVDF sensor was attached to a human subject’s chest,
and the output voltage of the PVDF signal was measured using an oscilloscope. The measured amplitude
was approximately -20 mV to + 20 mV.
The wearable module consisted of a PVDF sensor, an amplifier, a switched capacitor low-pass
filter, a passive low-pass filter, an analog-to-digital converter, a microcontroller, and a ZigBee
transceiver module. The bedside unit consisted of a microcontroller, a ZigBee transceiver module, an
LCD, an LED, and a buzzer. The prototype developed for the wearable module is capable of processing
an incoming PVDF signal, separating out individual breathing and heartbeat signals, detecting individual
breaths and heartbeats, and wirelessly transmitting them to the bedside unit. Low power analog devices
for switched capacitor low-pass anti-aliasing filter (MAX7427), operational amplifier (LMC6482),
microcontroller (MSP430FG4618), and wireless protocol (ZigBee) were chosen in designing and
implementing the wearable module. A low power clock source for the switched capacitor filter was not
chosen. The prototype developed for the bedside unit is capable of receiving the detected breaths and
heartbeats and calculating breathing and heart rates. The bedside unit alarms if breaths or heartbeats
cease or if the wireless link fails. The bedside unit prototype developed can be miniaturized and can be
located within 10 m of the patient. The implementation and the testing of the signal conditioning circuit
was done on a breadboard. The algorithms for separating out breathing and heart signals, detecting
individual breaths and heartbeats, transmitting the detected breaths and heartbeats to the bedside unit,
calculating breathing and heart rates, and alerting on cessation of breathing or heartbeats or wireless link
failure were developed and tested on the MSP430FG4618 Experimenter’s Boards. On six 22-s PVDF
75
recordings, the percentage of peaks correctly detected as breaths (true positive) is 64%, and the
percentage of peaks falsely detected as breaths (false positive) is 0%. On six 22-s PVDF recordings, the
percentage of peaks correctly detected as heartbeats (true positive) is 80%, and the percentage of peaks
falsely detected as heartbeats (false positive) is 4%.
6.2. Conclusions
The study done in this project can be used to develop a miniature, unobtrusive, and selfcontained heart and breathing monitoring system. The prototypes of the wearable module and the
bedside alarm unit were successfully built from carefully chosen low-power analog, microcontroller, and
wireless technologies except for the clock source to the switched capacitor low-pass anti-aliasing filter.
Based on the design structure and chosen technology and hardware, the prototypes can be made small by
incorporating the miniature electronic components directly into custom integrated circuits.
In this work, the PVDF sensor was chosen. The PVDF sensor voltage changes in response to
both the chest expansion and contraction caused by breathing and to the chest vibrations caused by
heartbeats when attached to the patient’s chest. Therefore, the sensor and the wearable module provide
an unobtrusive way of monitoring cessation of breaths or heartbeats.
Testing of the signal conditioning circuit by connecting its input to the output of the PVDF
sensor has not been done in this work. No measurements were made of the power consumption of the
wearable module electronics. Therefore, at present, battery size to achieve a given operating time is not
known.
6.3. Recommendations
Before the monitoring system can be used for human studies, the signal conditioning circuit has
to be tested by connecting its input to the output of the PVDF sensor. The current software algorithm
does not consider the variability of PVDF signal amplitude from patient to patient. Therefore, the
algorithm has to be improved by incorporating automatic gain adjustment. Such adaptation is needed
before the monitoring system is useful for actual patients. A low power solution for the clock source to
76
the switched capacitor low-pass anti-aliasing filter has to be provided. Whether the order of the filter can
be reduced to reduce power consumption needs to be investigated. Measurements need to be made to test
whether the wireless link successfully functions when the wearable module is worn by a sleeping subject
changing position in bed. Such studies need to be done to determine if the monitoring system will work
in actual home settings.
77
APPENDIX A
MATLAB code for data analysis of PVDF recordings
% Create an array of discrete-time function values, xn.
xn1 = importdata('pvdf.txt');
xn2 = importdata ('ecg.txt');
xn3 = importdata ('ppg.txt');
xn4 = importdata ('spg.txt');
%Calculation of mean to remove the DC offset from samples
xn1m = mean(xn1)
xn2m = mean(xn2)
xn3m = mean(xn3)
xn4m = mean(xn4)
for i = 1:22401
x1(i) = xn1(i) - xn1m;
x2(i) = xn2(i)- xn2m;
x3(i)= xn3(i) - xn3m;
end
m = size (xn4)
for i = 1:m
x4(i)= xn4(i) - xn4m;
end
% Create the complex number array of DFT values, Xk.
xk1 = fft(x1);
xk2 = fft(x2);
xk3 = fft(x3);
xk4 = fft(x4);
% Create the arrays of magnitudes and phases of Xk.
MXk1 = abs(xk1);
MXk2 = abs(xk2);
MXk3 = abs(xk3);
MXk4 = abs(xk4);
% Create the array of frequency values, fk.
fk1 = 1000*(0:22400)/22401;
fk2 = 1000*(0:22400)/22401;
fk3 = 1000*(0:22400)/22401;
fk4 = 1000*(0:22346)/22347;
% create the array of time value
tk1 = 0:1/1000:22.4
tk2 = 0:1/1000:22.4
tk3 = 0:1/1000:22.4
tk4 = 0:1/1000:22.4
figure(1)
plot(fk1, MXk1)
78
xlim([0 3])
ylim([0 3000000])
title('Pvdf frequency plot');
xlabel('Frequency (Hz)');
ylabel('Magnitude');
figure(2)
plot(fk2, MXk2)
xlim([0 3])
ylim([0 3000000])
title('ecg frequency plot');
xlabel('Frequency (Hz)');
ylabel('Magnitude');
figure(3)
plot(fk3, MXk3)
xlim([0 3])
ylim([0 3000000])
title('ppg frequency plot');
xlabel('Frequency (Hz)');
ylabel('Magnitude');
figure(4)
plot(fk4, MXk4)
xlim([0 3])
ylim([0 3000000])
title('spg frequency plot');
xlabel('Frequency (Hz)');
ylabel('Magnitude');
figure(5)
plot(fk1, MXk1,fk3,MXk3)
xlim([0 20])
ylim([0 3000000])
title('pvdf&ppg frequency plot');
xlabel('Frequency (Hz)');
ylabel('Magnitude');
figure(6)
plot(fk1, MXk1,fk4,MXk4)
xlim([0 3])
ylim([0 3000000])
title('pvdf&spg frequency plot');
xlabel('Frequency (Hz)');
ylabel('Magnitude');
figure(7)
plot(fk4, MXk4,fk3,MXk3)
xlim([0 3])
ylim([0 3000000])
title('spg&ppg frequency plot');
xlabel('Frequency (Hz)');
ylabel('Magnitude');
79
figure(8)
plot(fk4, MXk4,fk3,MXk3,fk1,MXk1)
xlim([0 3])
ylim([0 3000000])
title('spg&ppg&pvdf frequency plot');
xlabel('Frequency (Hz)');
ylabel('Magnitude');
figure(9)
plot(tk1,x1)
xlabel('time')
ylabel('magnitude')
figure(10)
plot(fk1, MXk1,fk3,MXk3)
xlim([10 20])
ylim([0 3000000])
title('pvdf&ppg frequency plot');
xlabel('Frequency (Hz)');
ylabel('Magnitude');
figure(11)
plot(fk1, MXk1)
xlim([0 40])
ylim([0 3000000])
title('pvdf frequency plot');
xlabel('Frequency (Hz)');
ylabel('Magnitude');
figure(12)
plot(fk1, MXk1,fk3,MXk3)
xlim([12 14])
ylim([0 3000000])
title('pvdf&ppg frequency plot');
xlabel('Frequency (Hz)');
ylabel('Magnitude');
figure(13)
plot(fk1, MXk1,fk3,MXk3)
xlim([14 16])
ylim([0 3000000])
title('pvdf&ppg frequency plot');
xlabel('Frequency (Hz)');
ylabel('Magnitude');
figure(14)
plot(fk1, MXk1,fk3,MXk3)
xlim([16 18])
ylim([0 3000000])
title('pvdf&ppg frequency plot');
xlabel('Frequency (Hz)');
ylabel('Magnitude');
80
APPENDIX B
C program for microcontroller in the wearable module
#include "include.h"
char compare_brate (long signed intbr_df_output );
char compare_hrate (long inthr_df_output );
extern char paTable[];
extern char paTableLen;
char txBuffer [5];
char rxBuffer [10];
// Variables for detector
//static intsample_no = 0x0000;
long inthr_df_output ;
long signed intbr_df_output ;
unsigned intd_i,d_j,d_z;
inttemp_sample;
char byte_low ;
char sample_number ;
intaddhr, addbr;
intbreath_peak_cnt;
intheart_peak_cnt;
char power_temp;
UInt16 temp_pvdf_sample;
// Variables for filter
//variable declarations
static int count = 0x0000;
signed intADCResult;
long signed intdataoutlp;
long intdataoutbp;
intbufflp[119];
// Reserve loactions = Number of taps, for circular buffering; low pass filter
intbuffbp[129];
// Reserve locations = Number of taps, for circular buffering; band pass filter
intimpulse_testlp[119];
intimpulse_testbp[129];
signed intdataoutlp_high;
intdataoutbp_high;
signed intdataoutlp_low;
intdataoutbp_low;
//intverifylp[119];
//intverifybp[129];
intf_i;
// Function Prototypes for filter
//function prototypes
void filterlp(int);
// low pass FIR filter
void filterbp(int);
// band pass FIR filter
81
void main (void)
{
WDTCTL = WDTPW + WDTHOLD; // Stop WDT
FLL_CTL0 |= XCAP18PF;
// Set load capacitance for xtal
while ( LFOF & FLL_CTL0); // wait for watch crystal to stabilize
SCFI0 |= FN_4;
// x2 DCO, 4MHz nominal DCO
SCFQCTL = 0x79;
// (121 + 1) x 32768 = 4.0 MHz
// SVSCTL &= 0x0f ;
SVSCTL |= VLD0 + VLD2;
TI_CC_SPISetup();
// Set to 2.4V
// Initialize SPI port
TI_CC_PowerupResetCC2500();
// Reset CC2500
writeRFSettings();
// Write RF settings to configreg
TI_CC_SPIWriteBurstReg(TI_CC2500_PATABLE, paTable, paTableLen);//Write PATABLE
// Configure ports -- switch inputs, LEDs, GDO0 to RX packet info from CC2500
TI_CC_SW_PxIES = ~(TI_CC_SW1+TI_CC_SW2);
// Int on falling edge
TI_CC_SW_PxIFG&= ~(TI_CC_SW1+TI_CC_SW2); // Clear flags
TI_CC_SW_PxIE = TI_CC_SW1+TI_CC_SW2;
// Activate enables
TI_CC_LED_PxDIR = TI_CC_LED1 + TI_CC_LED2; // Port to LED set to Outputs
TI_CC_LED_PxOUT = TI_CC_LED1 + TI_CC_LED2; // Turn on LED at the beginning
TI_CC_GDO0_PxIES |= TI_CC_GDO0_PIN;
// Int on falling edge (end of pkt)
TI_CC_GDO0_PxIFG &= ~TI_CC_GDO0_PIN;
// Clear flag
TI_CC_GDO0_PxIE |= TI_CC_GDO0_PIN;
// Enable int on end of packet
P6SEL |= 0x01;
/// Clearing the Buffers used for filter
for (f_i=0;f_i<tapslp;f_i++)
{
bufflp[f_i] = 0;
}
for (f_i=0;f_i<tapsbp;f_i++)
{
buffbp[f_i] = 0;
}
adc_config();
// Initialize and enable ADC12
timerA0_config();
// Initialize TimerA1
initLCDPortPins();
// initBasicTimer();
initLCD_A();
// Initialize port pins
// Initialize basic timer
addhr = 1300;
addbr = 130;
TI_CC_SPIStrobe(TI_CC2500_SRX);
// Initialize CCxxxx in RX mode.
// When a pkt is received, it will
// signal on GDO0 and wake CPU
for (d_i=0;d_i<20;d_i++)
82
{
for(d_j=0;d_j<5000;d_j++)
{}
TI_CC_LED_PxOUT ^=(TI_CC_LED1 + TI_CC_LED2);// LED flashing during startup
}
TI_CC_LED_PxOUT =0;
// Initializing integers
power_temp = 0x00;
// Initialize LED to OFF
heart_peak_cnt = 0;
breath_peak_cnt = 0;
while(1)
{
power_temp |= SVSCTL;
power_temp&= 0x01;
if ( power_temp )
{
SVSCTL &= 0xFE;
}
else {
_BIS_SR(LPM3_bits + GIE);
// Enter LPM3, enable interrupts
}
}
}
#pragma vector = ADC12_VECTOR
__interrupt void ADC12_ISR(void)
{
__bic_SR_register_on_exit(LPM0_bits); // Exit LPM0
ADCResult = ADC12MEM0;
RESLO = 0 ;
RESHI = 0 ;
temp_pvdf_sample = pvdf_samples[count] - 2044 ;
filterlp(temp_pvdf_sample);
//verifylp[count] = dataoutlp;
RESLO = 0 ;
RESHI = 0 ;
temp_pvdf_sample = pvdf_samples[count] - 2044;
filterbp(temp_pvdf_sample);
//verifybp[count] = dataoutbp;
// Now since the filter output is ready
// Pass the values to the detector.
if ( count <br_comp_data_in ){
P5OUT ^= PIN1;
count++;
hr_df_output = dataoutbp;
br_df_output = dataoutlp;
if ( compare_hrate ( hr_df_output ) )
{
TI_CC_LED_PxOUT ^= TI_CC_LED2;
heart_peak_cnt ++;
83
temp_sample = count ;
temp_sample>>= 8;
sample_number = temp_sample ;
temp_sample = count ;
temp_sample&= 0x00ff;
byte_low = temp_sample ;
txBuffer[0] = 0x4;
// Packet length
txBuffer[1] = 0x1; // Packet address
txBuffer[2] = sample_number;
txBuffer[3] = byte_low;
txBuffer[4] = 0xff;
RFSendPacket(txBuffer, 5);
testChar(byte_low, 0,0);
testChar(byte_low, 1,1);
testChar(sample_number, 0,2);
testChar(sample_number, 1,3);
testChar(txBuffer[4], 0,4);
testChar(txBuffer[4], 1,5);
}
if ( compare_brate ( br_df_output ) )
{
TI_CC_LED_PxOUT ^= TI_CC_LED1;
breath_peak_cnt ++;
temp_sample = count ;
temp_sample>>= 8;
sample_number = temp_sample ;
temp_sample = count ;
temp_sample&= 0x00ff;
byte_low = temp_sample ;
txBuffer[0] = 0x4;
// Packet length
txBuffer[1] = 0x1; // Packet address
txBuffer[2] = sample_number;
txBuffer[3] = byte_low;
txBuffer[4] = 0xBB;
RFSendPacket(txBuffer, 5);
testChar(byte_low, 0,0);
testChar(byte_low, 1,1);
testChar(sample_number, 0,2);
testChar(sample_number, 1,3);
testChar(txBuffer[4], 0,4);
testChar(txBuffer[4], 1,5);
}
}
}
// Timer A0 interrupt service routine
#pragma vector = TIMERA0_VECTOR
__interrupt void TimerA0_ISR(void)
{
__bic_SR_register_on_exit(LPM0_bits); // Exit LPM0
P5OUT ^= TAIFG;
// Toggle P5.0
84
ADC12CTL0 |= ADC12SC;
__bis_SR_register(LPM0_bits + GIE);
// Start sampling/conversion
// LPM0, ADC12_ISR will force exit
}
#pragma vector=PORT1_VECTOR
__interrupt void port1_ISR (void)
{
if (P1IFG & BIT0 || P1IFG & BIT1)
// One of the Switches pressed
{
if (P1IFG & BIT1)
{
addhr -= 200;
addbr -= 20;
}
else
{
addhr += 200;
addbr += 20;
}
P1IFG &= ~(PIN1+PIN0);
}
else if(P1IFG & TI_CC_GDO0_PIN)
// Command received from RF
{
// RX active
char len=2;
// Len of pkt to be RXed (only addr
// plus data; size byte not incl b/c
// stripped away within RX function)
if (RFReceivePacket(rxBuffer,&len))
// Fetch packet from CCxxxx
{
if ( rxBuffer[1] == 0xAB )
{
// Start self testi.e initiate a ADC check.
// Further send a ack with data 0xCD
txBuffer[0] = 0x4;
// Packet length
txBuffer[1] = 0x1; // Packet address
txBuffer[2] = 0x00;
txBuffer[3] = 0x00;
txBuffer[4] = 0xcc;
RFSendPacket(txBuffer, 5);
// Send value over RF
// TI_CC_LED_PxOUT ^= BIT1;
// Toggle LEDs according to pkt data
for (d_i=0;d_i<20;d_i++)
{
for(d_j=0;d_j<5000;d_j++)
{}
}
txBuffer[0] = 0x4;
// Packet length
txBuffer[1] = 0x1; // Packet address
txBuffer[2] = 0xFF;
txBuffer[3] = 0xFF;
txBuffer[4] = 0xCD;
85
RFSendPacket(txBuffer, 5);
// LED flashing during startup
}
}}
P1IFG &= ~TI_CC_GDO0_PIN;
// Clear Receive flag
}
char compare_hrate (long inthr_df_output )
{
//char df_output;
char hr_df_cmp;
const long int hr_threshold_1 = 00000000;
const long int hr_threshold_2 = 15000000;
static char hr_step_1 = 1;
static char min_pk_spc = 0;
static char hr_step_2;
static char hr_step_3;
//char dsc_step1;
// df_cmp_f is the flag indicating completion of digital filtering.
hr_df_cmp = 1;
min_pk_spc ++ ;
hr_step1:
if (hr_step_1)
if (hr_df_cmp)
{
if ( hr_df_output< hr_threshold_1 )
{
hr_step_2 = 1;
hr_step_1 = 0;
hr_step_3 = 0;
}
else
{
hr_step_2 = 0;
hr_step_1 = 1;
hr_step_3 = 0;
}
}
else
goto hr_step1 ;
hr_step2:
if ( hr_step_2 )
if (hr_df_cmp)
{
if ( min_pk_spc> 64 )
{
if ( hr_df_output> hr_threshold_2 )
86
{
hr_step_2 = 0;
hr_step_1 = 1;
hr_step_3 = 0;
min_pk_spc = 0;
return 1;
// Call function to send the data in sample no to Receiver
}
else
{
hr_step_2 = 1;
hr_step_1 = 0;
hr_step_3 = 0;
}
}
}
else
goto hr_step2 ;
hr_step3:
if ( hr_step_3 )
if (hr_df_cmp)
{
if ( hr_df_output< hr_threshold_1 )
{
hr_step_2 = 0;
hr_step_1 = 1;
hr_step_3 = 0;
}
else
{
hr_step_2 = 0;
hr_step_1 = 0;
hr_step_3 = 1;
}
}
else
goto hr_step3 ;
return 0;
}
char compare_brate (long signed intbr_df_output )
{
//char df_output;
char br_df_cmp;
const long signed int br_threshold_1 = 0000000;
const long signed int br_threshold_2 = 11000000;
static char br_step_1 = 1;
static char br_step_2;
static char br_step_3;
//char dsc_step1;
87
// df_cmp_f is the flag indicating completion of digital filtering.
br_df_cmp = 1;
br_step1:
if (br_step_1)
if (br_df_cmp)
{
if ( br_df_output< br_threshold_1 )
{
br_step_2 = 1;
br_step_1 = 0;
br_step_3 = 0;
}
else
{
br_step_2 = 0;
br_step_1 = 1;
br_step_3 = 0;
}
}
else
goto br_step1 ;
br_step2:
if ( br_step_2 )
if (br_df_cmp)
{
if ( br_df_output> br_threshold_2 )
{
br_step_2 = 0;
br_step_1 = 1;
br_step_3 = 0;
return 1;
// Call function to send the data in sample no to Receiver
}
else
{
br_step_2 = 1;
br_step_1 = 0;
br_step_3 = 0;
}
}
else
goto br_step2 ;
br_step3:
if ( br_step_3 )
if (br_df_cmp)
{
if ( br_df_output< br_threshold_1 )
{
br_step_2 = 0;
br_step_1 = 1;
88
br_step_3 = 0;
}
else
{
br_step_2 = 0;
br_step_1 = 0;
br_step_3 = 1;
}
}
else
goto br_step3 ;
return 0;
}
void filterlp(int sample)
{
static intindexlp = 0;
inti,j;
j = indexlp;
bufflp[indexlp] = sample;
for (i=0;i<tapslp;i++)
{
MACS = coefflp[i];
if (j == 0)
{
OP2 = bufflp[j];
j = tapslp - 1;
}
else
{
OP2 = bufflp[j];
j--;
}
//index which gives the first location of the circular array
}
if (indexlp == 118)
indexlp = 1;
else
indexlp++;
dataoutlp = RESHI;
dataoutlp<<= 16 ;
dataoutlp += RESLO;
dataoutlp_low = RESLO;
dataoutlp_high = dataoutlp<< 16 ;
return;
}
void filterbp(int sample)
{
static intindexbp = 0;
//index which gives the first location of the circular array
89
inti,j;
j = indexbp;
buffbp[indexbp] = sample;
for (i=0;i<tapsbp;i++)
{
MACS = coeffbp[i];
if (j == 0)
{
OP2 = buffbp[j];
j = tapsbp - 1;
}
else
{
OP2 = buffbp[j];
j--;
}
}
if (indexbp == 128)
indexbp = 1;
else
indexbp++;
dataoutbp = RESHI;
dataoutbp<<= 16 ;
dataoutbp += RESLO;
dataoutbp_low = RESLO;
dataoutbp_high = RESHI;
return;
}
#include "msp430xG46x.h"
#include "spi.h"
#include "msp430_hw_board.h"
#include "CC2500_reg.h"
#include "CC2500.h"
#include "lcd.h"
#include "lowpass_fir_filter_coefficients.h"
#include "bandpass_fir_filter_coefficients.h"
#include "lee_pvdf_data_sub6.h"
#include "adc_config.h"
#include "timerA0_config.h"
#include "include.h"
#include "spi.h"
// Description of each function is given below.
//---------------------------------------------------------------------------// void TI_CC_SPISetup(void)
//
// DESCRIPTION:
// Configures the assigned interface to function as a SPI port and
// initializes it. For the MSP430 Board USART1 is used.
//----------------------------------------------------------------------------
90
void TI_CC_SPISetup(void)
{
TI_CC_CSn_PxOUT |= TI_CC_CSn_PIN;
TI_CC_CSn_PxDIR |= TI_CC_CSn_PIN;
// /CS disable
ME2 |= USPIE1;
// Enable USART1 SPI mode
UCTL1 |= CHAR + SYNC + MM;
// 8-bit SPI Master **SWRST**
UTCTL1 |= CKPL + SSEL1 + SSEL0 + STC; // SMCLK, 3-pin mode
UBR01 = 0x02;
// UCLK/2
UBR11 = 0x00;
// 0
UMCTL1 = 0x00;
// No modulation
TI_CC_SPI_USART1_PxSEL |= TI_CC_SPI_USART1_SIMO | TI_CC_SPI_USART1_SOMI |
TI_CC_SPI_USART1_UCLK;
// SPI option select
TI_CC_SPI_USART1_PxDIR |= TI_CC_SPI_USART1_SIMO + TI_CC_SPI_USART1_UCLK;
// SPI TXD out direction
UCTL1 &= ~SWRST;
// Initialize USART state machine
}
// void TI_CC_SPIWriteReg(char addr, char value)
//
// DESCRIPTION:
// Writes "value" to a single configuration register at address "addr".
//---------------------------------------------------------------------------void TI_CC_SPIWriteReg(char addr, char value)
{
TI_CC_CSn_PxOUT&= ~TI_CC_CSn_PIN;
// /CS enable
while (TI_CC_SPI_USART1_PxIN&TI_CC_SPI_USART1_SOMI);// Wait for CCx250 ready
IFG2 &= ~URXIFG1;
// Clear flag
U1TXBUF = addr;
// Send address
while(!(U1TCTL&TXEPT));
// Wait for TX to finish
U1TXBUF = value;
// Load data for TX after addr
while(!(U1TCTL&TXEPT));
// Wait for end of addr TX
TI_CC_CSn_PxOUT |= TI_CC_CSn_PIN;
// /CS disable
}
// void TI_CC_SPIWriteBurstReg(char addr, char *buffer, char count)
//
// DESCRIPTION:
// Writes values to multiple configuration registers, the first register being
// at address "addr". First data byte is at "buffer", and both addr and
// buffer are incremented sequentially (within the CCx250 and MSP430,
// respectively) until "count" writes have been performed.
//---------------------------------------------------------------------------void TI_CC_SPIWriteBurstReg(char addr, char *buffer, char count)
{
char i;
91
TI_CC_CSn_PxOUT&= ~TI_CC_CSn_PIN;
// /CS enable
while (TI_CC_SPI_USART1_PxIN&TI_CC_SPI_USART1_SOMI);// Wait for CCx250 ready
U1TXBUF = addr | TI_CC2500_WRITE_BURST; // Send address
while (!(IFG2&UTXIFG1));
// Wait for TX to finish
for (i = 0; i < count; i++)
{
U1TXBUF = buffer[i];
// Send data
while (!(IFG2&UTXIFG1));
// Wait for TX to finish
}
while(!(U1TCTL&TXEPT));
TI_CC_CSn_PxOUT |= TI_CC_CSn_PIN;
}
// /CS disable
// char TI_CC_SPIReadReg(char addr)
//
// DESCRIPTION:
// Reads a single configuration register at address "addr" and returns the
// value read.
//---------------------------------------------------------------------------char TI_CC_SPIReadReg(char addr)
{
char x;
TI_CC_CSn_PxOUT&= ~TI_CC_CSn_PIN;
// /CS enable
while (TI_CC_SPI_USART1_PxIN&TI_CC_SPI_USART1_SOMI);// Wait for CCx ready
U1TXBUF = (addr | TI_CC2500_READ_SINGLE); // Send address
while(!(U1TCTL&TXEPT));
// Wait for addr to be sent
U1TXBUF = 0;
// Load dummy byte for TX after addr
while(!(U1TCTL&TXEPT));
// Wait for end of dummy byte TX
x = U1RXBUF;
// Read data
TI_CC_CSn_PxOUT |= TI_CC_CSn_PIN;
// /CS disable
return x;
}
// void TI_CC_SPIReadBurstReg(char addr, char *buffer, char count)
//
// DESCRIPTION:
// Reads multiple configuration registers, the first register being at address
// "addr". Values read are deposited sequentially starting at address
// "buffer", until "count" registers have been read.
//---------------------------------------------------------------------------void TI_CC_SPIReadBurstReg(char addr, char *buffer, char count)
{
unsigned int i;
92
TI_CC_CSn_PxOUT&= ~TI_CC_CSn_PIN;
// /CS enable
while (TI_CC_SPI_USART1_PxIN&TI_CC_SPI_USART1_SOMI);// Wait for CCx250 ready
U1TXBUF = (addr | TI_CC2500_READ_BURST); // Send address
while (!(IFG2&UTXIFG1));
// Wait for TXBUF ready
U1TXBUF = 0;
// Dummy write to read 1st data byte
// Addr byte is now being TX'ed, with dummy byte to follow immediately after
//while (!(IFG2&URXIFG1));
// Wait for end of addr byte TX
while(!(U1TCTL&TXEPT));
// First data byte now in RXBUF
for (i = 0; i < (count-1); i++)
{
U1TXBUF = 0;
//Initiate next data RX, meanwhile..
buffer[i] = U1RXBUF;
// Store data from last data RX
while (!(IFG2&URXIFG1));
// Wait for end of data RX
}
buffer[count-1] = U1RXBUF;
// Store last RX byte in buffer
TI_CC_CSn_PxOUT |= TI_CC_CSn_PIN;
// /CS disable
}
// char TI_CC_SPIReadStatus(char addr)
//
// DESCRIPTION:
// Special read function for reading status registers. Reads status register
// at register "addr" and returns the value read.
//---------------------------------------------------------------------------char TI_CC_SPIReadStatus(char addr)
{
char x;
TI_CC_CSn_PxOUT&= ~TI_CC_CSn_PIN;
// /CS enable
while (TI_CC_SPI_USART1_PxIN&TI_CC_SPI_USART1_SOMI);// Wait for CC250x ready
U1TXBUF = (addr | TI_CC2500_READ_BURST); // Send address
while(!(U1TCTL&TXEPT));
U1TXBUF = 0;
// Wait for addr to be sent
// Dummy write so we can read data
while(!(U1TCTL&TXEPT));
// Wait for end of dummy byte TX
x = U1RXBUF;
// Read data
TI_CC_CSn_PxOUT |= TI_CC_CSn_PIN;
// /CS disable
return x;
}
// void TI_CC_SPIStrobe(char strobe)
//
93
// DESCRIPTION:
// Special write function for writing to command strobe registers. Writes
// to the strobe at address "addr".
//---------------------------------------------------------------------------void TI_CC_SPIStrobe(char strobe)
{
TI_CC_CSn_PxOUT&= ~TI_CC_CSn_PIN;
// /CS enable
while (TI_CC_SPI_USART1_PxIN&TI_CC_SPI_USART1_SOMI);// Wait for CC250x ready
U1TXBUF = strobe;
// Send strobe
// Strobe addr is now being TX'ed
while(!(U1TCTL&TXEPT));
// Wait for end of addr TX
TI_CC_CSn_PxOUT |= TI_CC_CSn_PIN;
// /CS disable
}
// Delay function. # of CPU cycles delayed is similar to "cycles". Specifically,
// it's ((cycles-15) % 6) + 15. Not exact, but gives a sense of the real-time
// delay. Also, if MCLK ~1MHz, "cycles" is similar to # of useconds delayed.
void TI_CC_Wait(unsigned int cycles)
{
while(cycles>15)
// 15 cycles consumed by overhead
cycles = cycles - 6;
// 6 cycles consumed each iteration
}
void TI_CC_PowerupResetCC2500(void)
{
TI_CC_CSn_PxOUT |= TI_CC_CSn_PIN;
TI_CC_Wait(30);
TI_CC_CSn_PxOUT&= ~TI_CC_CSn_PIN;
TI_CC_Wait(30);
TI_CC_CSn_PxOUT |= TI_CC_CSn_PIN;
TI_CC_Wait(45);
TI_CC_CSn_PxOUT&= ~TI_CC_CSn_PIN;
// /CS enable
while (TI_CC_SPI_USART1_PxIN&TI_CC_SPI_USART1_SOMI);// Wait for CC250x ready
U1TXBUF = TI_CC2500_SRES;
// Send strobe
// Strobe addr is now being TX'ed
IFG2 &= ~URXIFG1;
// Clear flag
while (!(IFG2&URXIFG1));
// Wait for end of addr TX
while (TI_CC_SPI_USART1_PxIN&TI_CC_SPI_USART1_SOMI);
TI_CC_CSn_PxOUT |= TI_CC_CSn_PIN;
// /CS disable
}
/// spi.h
#ifndef SPI_H_
#define SPI_H_
94
extern void TI_CC_SPISetup(void);
extern void TI_CC_PowerupResetCC2500(void);
extern void TI_CC_SPIWriteReg(char, char);
extern void TI_CC_SPIWriteBurstReg(char, char*, char);
extern char TI_CC_SPIReadReg(char);
extern void TI_CC_SPIReadBurstReg(char, char *, char);
extern char TI_CC_SPIReadStatus(char);
extern void TI_CC_SPIStrobe(char);
extern void TI_CC_Wait(unsigned int);
#endif /*SPI_H_*/
// timer.c
#include "include.h"
void timerA0_config()
{
TACCTL0 = CCIE;
TACCR0 = 257 - 1;
TACTL = TASSEL_1 + MC_1;
// Compare-mode interrupt
// 128 samples per second
// ACLK, Up Mode
}
// timer.h
#ifndef TIMERA0_CONFIG_H_
#define TIMERA0_CONFIG_H_
extern void timerA0_config();
//timer A0 configuration
#endif /*TIMERA0_CONFIG_H_*/
// adc_config.c
#include "include.h"
void adc_config()
{
ADC12CTL0 = ADC12ON + SHT0_0;
// ADC12 ON, set sample time
ADC12CTL1 = SHP + ADC12DIV_3 + ADC12SSEL_2;
// Use Sampling timer, Set
ADC12CLK divider
ADC12MCTL0 = INCH_11 + SREF_0;
// ref+=AVcc, channel = A0
ADC12IE = BIT0;
// Enable interrupt for ADC12 MEM0
ADC12CTL0 |= ENC;
// Enable conversions
}
#ifndef ADC_CONFIG_H_
#define ADC_CONFIG_H_
extern void adc_config();
//ADC configuration
95
#endif /*ADC_CONFIG_H_*/
/*
* Filter Coefficients (C Source) generated by the Filter Design and Analysis Tool
*
* Generated by MATLAB(R) 7.5 and the Signal Processing Toolbox 6.8.
*
* Generated on: 07-Nov-2010 22:30:29
*
*/
/*
* Discrete-Time FIR Filter (real)
* ------------------------------* Filter Structure : Direct-Form FIR
* Filter Length : 129
* Stable
: Yes
* Linear Phase
: Yes (Type 1)
*/
/* General type conversion for MATLAB generated C-code */
/*
* Warning - Filter coefficients were truncated to fit specified data type.
* The resulting response may not match generated theoretical response.
* Use the Filter Design & Analysis Tool to design accurate
* int16 filter coefficients.
*/
static const char tapsbp = 129;
static const signed intcoeffbp[129] = {
25,
4, 7, 25,
0, -11, 11, -14, -38,
-5, -18, -51, 0, 14, -30, 32, 75,
5,
49, 113,
0, -8, 77, -67, -134,
2, -116,
-223, 0, -25, -169, 124, 207, -25, 239, 394,
0, 117, 333, -212, -282, 84, -461, -663,
0,
-331, -639, 358, 348, -221, 908, 1163, 0, 882,
1367, -695, -393, 669, -2392, -2937,
0, -4244, -7350,
5748, 16785, 5748, -7350, -4244,
0, -2937, -2392, 669,
-393, -695, 1367, 882,
0, 1163, 908, -221, 348,
358, -639, -331,
0, -663, -461, 84, -282, -212,
333, 117,
0, 394, 239, -25, 207, 124, -169,
-25,
0, -223, -116, 2, -134, -67, 77, -8,
0, 113, 49, 5, 75, 32, -30, 14,
0,
-51, -18, -5, -38, -14, 11, -11, 0, 25,
7,
4, 25
};
/*
* Filter Coefficients (C Source) generated by the Filter Design and Analysis Tool
*
* Generated by MATLAB(R) 7.5 and the Signal Processing Toolbox 6.8.
*
* Generated on: 07-Nov-2010 22:28:16
96
*
*/
/*
* Discrete-Time FIR Filter (real)
* ------------------------------* Filter Structure : Direct-Form FIR
* Filter Length : 119
* Stable
: Yes
* Linear Phase
: Yes (Type 1)
*/
/* General type conversion for MATLAB generated C-code */
/*
* Warning - Filter coefficients were truncated to fit specified data type.
* The resulting response may not match generated theoretical response.
* Use the Filter Design & Analysis Tool to design accurate
* int16 filter coefficients.
*/
static const char tapslp = 119;
static const signed intcoefflp[119] = {
15, 16, 17, 19, 21, 23, 26, 29, 32,
37, 41, 47, 53, 59, 66, 74, 82, 91,
101, 111, 122, 134, 146, 158, 172, 185, 199,
214, 229, 244, 260, 276, 292, 308, 325, 341,
357, 374, 390, 405, 421, 436, 451, 466, 479,
493, 505, 517, 528, 539, 548, 557, 565, 571,
577, 582, 586, 588, 590, 590, 590, 588, 586,
582, 577, 571, 565, 557, 548, 539, 528, 517,
505, 493, 479, 466, 451, 436, 421, 405, 390,
374, 357, 341, 325, 308, 292, 276, 260, 244,
229, 214, 199, 185, 172, 158, 146, 134, 122,
111, 101, 91, 82, 74, 66, 59, 53, 47,
41, 37, 32, 29, 26, 23, 21, 19, 17,
16, 15
};
97
APPENDIX C
C program for microcontroller in the bedside unit
#ifndef INCLUDE_H_
#define INCLUDE_H_
#include "msp430xG46x.h"
#include "spi.h"
#include "msp430_hw_board.h"
#include "CC2500_reg.h"
#include "CC2500.h"
#include "lcd.h"
//#include "lcd_include.h"
#endif /*INCLUDE_H_*/
//---------------------------------------------------------------------------// Demo Application for MSP430/CC1100-2500 Interface Code Library v1.0
//
// Pritam Chopda
// CSUS
// CC studio
//---------------------------------------------------------------------------#include "include.h"
char compare_df (char df_output );
extern char paTable[];
extern char paTableLen;
char status[2];
char txBuffer [6];
char rxBuffer [6];
extern char status_ind [2];
const char sampling_rate = 0x64;
const char per_min = 0x3C ;
const char br_data_id = 0xbb;
const char hr_data_id = 0xff ;
const char er_data_id = 0xcc ;
const UInt16 ADC_CHECK = 0xffff;
intbr_temp_product ;
inthr_temp_product ;
char data_id;
char no_data_rec;
//intrec_value;
//intrec_hrate [2];
//intrec_brate [2];
//static intsample_no = 0x0000;
//static char df_output = 0x04;
unsigned inti,j;
inthr_temp_sample;
intbr_temp_sample;
98
intbyte_low ;
intsample_number ;
inthr_interval_ ;
intbr_interval_ ;
char heart_rate;
char breath_rate;
char pck_rec;
char signal_str;
char SOUND_ALARM;
void main (void)
{
WDTCTL = WDTPW + WDTHOLD;
// Stop WDT
FLL_CTL0 |= XCAP18PF;
// Set load cap for 32k xtal
TI_CC_SPISetup();
// Initialize SPI port
TI_CC_PowerupResetCC2500();
// Reset CC2500
writeRFSettings();
// Write RF settings to configreg
TI_CC_SPIWriteBurstReg(TI_CC2500_PATABLE, paTable, paTableLen);//Write PATABLE
// Configure ports -- switch inputs, LEDs, GDO0 to RX packet info from CC2500
TI_CC_SW_PxIES = ~(TI_CC_SW1+TI_CC_SW2);
// Int on falling edge
TI_CC_SW_PxIFG&= ~(TI_CC_SW1+TI_CC_SW2); // Clear flags
TI_CC_SW_PxIE = TI_CC_SW1+TI_CC_SW2;
// Activate enables
TI_CC_LED_PxDIR = TI_CC_LED1 + TI_CC_LED2; // Port to LED set to Outputs
TI_CC_LED_PxOUT = TI_CC_LED1 + TI_CC_LED2; // Turn on LED at the beginning
TI_CC_GDO0_PxIES |= TI_CC_GDO0_PIN;
// Int on falling edge (end of pkt)
TI_CC_GDO0_PxIFG &= ~TI_CC_GDO0_PIN;
// Clear flag
TI_CC_GDO0_PxIE |= TI_CC_GDO0_PIN;
// Enable int on end of packet
initLCDPortPins();
// Initialize port pins
initBasicTimer();
// Initialize basic timer
initLCD_A();
// Initialize LCD_A
//initCCPortPins();
// Intialize the port pins
hr_temp_sample = 0;
br_temp_sample = 0;
no_data_rec = 0;
SOUND_ALARM = 1;
heart_rate = 0;
breath_rate = 0;
TI_CC_SPIStrobe(TI_CC2500_SRX);
// Initialize CCxxxx in RX mode.
// When a pkt is received, it will
// signal on GDO0 and wake CPU
for (i=0;i<20;i++)
{
for(j=0;j<5000;j++)
{}
TI_CC_LED_PxOUT ^=(TI_CC_LED1 + TI_CC_LED2);// LED flashing during startup
}
TI_CC_LED_PxOUT =0;
// Initialize LED to OFF
// rec_brate[0] = 0;
99
// rec_hrate[0] = 0;
_BIS_SR(LPM3_bits + GIE);
}
// Enter LPM3, enable interrupts
// The ISR assumes the interrupt came from a press of one of the four buttons
// and therefore does not check the other four inputs.
#pragma vector=PORT1_VECTOR
__interrupt void port1_ISR (void)
{
if(P1IFG & TI_CC_GDO0_PIN)
// Command received from RF
{
// RX active
char len=7;
// Len of pkt to be RXed (only addr
P5OUT ^= PIN1;
// plus data; size byte not incl b/c
// stripped away within RX function)
if (RFReceivePacket(rxBuffer,&len))
// Fetch packet from CCxxxx
// TI_CC_LED_PxOUT ^= rxBuffer[1];
// Toggle LEDs according to pkt data
data_id = rxBuffer[3] ;
byte_low = rxBuffer[2] ;
sample_number = rxBuffer[1] ;
pck_rec = 9;
signal_str = status[0];
/* testChar(rxBuffer[2], 0,0);
testChar(rxBuffer[2], 1,1);
testChar(rxBuffer[1], 0,2);
testChar(rxBuffer[1], 1,3);
testChar(rxBuffer[3], 0,5);
testChar(rxBuffer[3], 1,6); */
// Call the function to measure the heart rate.
sample_number<<= 8;
sample_number = byte_low + sample_number;
//
no_data_rec = 1;
//
sample_number - rec_value
if (data_id == hr_data_id )
{
// P3IN = PIN5;
if ( sample_number>hr_temp_sample )
{
hr_interval_ = sample_number - hr_temp_sample;
}
else
{
hr_temp_sample = 0xffff - hr_temp_sample;
hr_interval_ = sample_number + hr_temp_sample;
}
hr_temp_sample = sample_number ;
// Now to calculate the heart rate;
// Now once you have the interval you divide it by 100 to get per second value
hr_temp_product = sampling_rate * per_min ;
heart_rate = hr_temp_product / hr_interval_ ;
}
100
else if (data_id == br_data_id )
{
if ( sample_number>br_temp_sample )
{
br_interval_ = sample_number - br_temp_sample;
}
else
{
br_temp_sample = 0xffff - br_temp_sample;
br_interval_ = sample_number + br_temp_sample;
}
br_temp_sample = sample_number ;
// Now to calculate the heart rate;
// Now once you have the interval you divide it by 100 to get per second value
br_temp_product = sampling_rate * per_min ;
breath_rate = br_temp_product / br_interval_ ;
}
else if ( data_id == er_data_id )
{
// Wait for other test result to pour in
// if all ok sound the buzzer danger!!
if ( sample_number == ADC_CHECK )
{
// Change the timer value so it
// BTCTL = BT_fCLK2_DIV128 | BT_fCLK2_ACLK_DIV256;
SOUND_ALARM = 0 ;
}
else
//
{
dispChar(0, 12);
dispChar(1, 13);
dispChar(2, 10);
display ADC on screen
}
}
P1IFG &= ~TI_CC_GDO0_PIN;
// Clear Receive flag
}
}
#pragma vector=BASICTIMER_VECTOR
__interrupt void basic_timer_ISR(void)
{
if ( pck_rec> 0 )
{
if (no_data_rec )
{
dispbcd(breath_rate);
101
dispChar(3, 15);
dispChar(4, 8);
testChar(signal_str, 0 , 5);
testChar(signal_str, 1 , 6);
P2OUT ^= PIN1;
P2OUT ^= PIN2 ;
}
else
{
dispbcd(heart_rate);
dispChar(3, 15);
dispChar(4, 16);
testChar(signal_str, 0 , 5);
testChar(signal_str, 1 , 6);
P2OUT ^= PIN2 ;
P2OUT ^= PIN1 ;
}
no_data_rec ^= 1;
pck_rec-- ;
// Toggle P2.2,1
}
else
{
if (SOUND_ALARM)
{
// Activate error correction algorithm
// The algorithm sends a self test word 0xABCD and waits for an ack this tests for the
// RF communcication. Also it waits for the ADC check by the transmitter.
// If all is perfect alarm is sounded.
txBuffer[0] = 2;
// Packet length
txBuffer[1] = 0x1;
txBuffer[2] = 0xAB;
//RFSendPacket(txBuffer, 2);
// Send value over RF
// It should display COM so thus wating for
// data to be sent.
dispChar(0, 18);
dispChar(1, 0);
dispChar(2, 12);
SOUND_ALARM = 0;
}
else
{
P3OUT ^= PIN5;
}
// P3OUT ^= PIN5;
}
}
// The ISR assumes the int came from the pin attached to GDO0 and therefore
// does not check the other seven inputs. Interprets this as a signal from
// CCxxxx indicating packet received.
102
APPENDIX D
MATLAB code for generating the coefficients and plotting the magnitude
response
clc;
N1 = 119; // Number of taps for low pass filter
N2 = 129; // Number of taps for Band pass filter
b1 = fir1(N1-1,0.0125,hamming(N1)); // Low pass FIR filter Hamming window
[h1,f1] = freqz(b1,1,512,128);
mag1 = 20*log10(abs(h1)); // Calculating the magnitude response
b2 = fir1(N2-1,[0.11875 0.63125],hamming(N2)); //Band pass FIR filter Hamming window
[h2,f2] = freqz(b2,1,512,128);
mag2 = 20*log10(abs(h2)); // Calculating the magnitude response
figure(1) // Plotting the magnitude response for low pass filter
plot(f1, mag1), grid on;
xlabel('Frequency (Hz)');
ylabel('Magnitude Response (dB)');
figure(2) // Plotting the magnitude for band pass filter
plot(f2, mag2), grid on;
xlabel('Frequency (Hz)');
ylabel('Magnitude Response (dB)');
figure(3)
plot(f1,mag1,f2,mag2), grid on;
xlabel('Frequency (Hz)');
ylabel('Magnitude Response (dB)');
103
APPENDIX E
Filter coefficients for the low-pass and band-pass filters
/*
* Filter Coefficients (C Source) generated by the Filter Design and
Analysis Tool
*
* Generated by MATLAB(R) 7.5 and the Signal Processing Toolbox 6.8.
*
* Generated on: 07-Nov-2010 22:28:16
*
*/
/*
* Discrete-Time FIR Filter (real)
* ------------------------------* Filter Structure : Direct-Form FIR
* Filter Length
: 119
* Stable
: Yes
* Linear Phase
: Yes (Type 1)
*/
constintorderlp = 119;
constintcoefflp[119] = {
15,
16,
17,
19,
37,
41,
47,
53,
101,
111,
122,
134,
214,
229,
244,
260,
357,
374,
390,
405,
493,
505,
517,
528,
577,
582,
586,
588,
582,
577,
571,
565,
505,
493,
479,
466,
374,
357,
341,
325,
229,
214,
199,
185,
111,
101,
91,
82,
41,
37,
32,
29,
16,
15
};
21,
59,
146,
276,
421,
539,
590,
557,
451,
308,
172,
74,
26,
23,
66,
158,
292,
436,
548,
590,
548,
436,
292,
158,
66,
23,
26,
74,
172,
308,
451,
557,
590,
539,
421,
276,
146,
59,
21,
29,
82,
185,
325,
466,
565,
588,
528,
405,
260,
134,
53,
19,
32,
91,
199,
341,
479,
571,
586,
517,
390,
244,
122,
47,
17,
/*
* Filter Coefficients (C Source) generated by the Filter Design and
Analysis Tool
*
* Generated by MATLAB(R) 7.5 and the Signal Processing Toolbox 6.8.
*
* Generated on: 07-Nov-2010 22:30:29
*/
104
/*
* Discrete-Time FIR Filter (real)
* ------------------------------* Filter Structure : Direct-Form FIR
* Filter Length
: 129
* Stable
: Yes
* Linear Phase
: Yes (Type 1)
*/
constintorderbp = 129;
constintcoeffBP[129] =
25,
4,
-14,
-38,
-5,
32,
75,
5,
-67,
-134,
2,
207,
-25,
239,
-212, -282,
84,
358,
348,
-221,
-695, -393,
669,
5748, 16785,
5748,
669,
-393,
-695,
348,
358,
-639,
-282,
-212,
333,
124,
-169,
-25,
67,
77,
-8,
-30,
14,
0,
-11,
0,
25,
};
{
7,
-18,
49,
-116,
394,
-461,
908,
-2392,
-7350,
1367,
-331,
117,
0,
0,
-51,
7,
25,
0,
-11,
-51,
0,
14,
113,
0,
-8,
-223,
0,
-25,
0,
117,
333,
-663,
0,
-331,
1163,
0,
882,
-2937,
0, -4244,
-4244,
0, -2937,
882,
0,
1163,
0,
-663,
-461,
0,
394,
239,
-223,
-116,
2,
113,
49,
5,
-18,
-5,
-38,
4,
25
11,
-30,
77,
-169,
-639,
1367,
-7350,
-2392,
908,
-25,
-134,
75,
-14,
124,
-221,
84,
207,
32,
11,
105
APPENDIX F
MATLAB code for testing the digital filters
clear all;
clc;
k = 1;
m = 1;
RESHI = 0;
tk1 = 0:1/1000:22.4;
tk2 = 0:1/125:22.4;
tapsbp = 129
coeffbp = importdata('bandpasscoefficients.txt') //importing band pass filter coefficients
tapslp = 119;
coefflp = importdata('lowpasscoefficients.txt') //importing low pass filter coefficients
for i = 1:tapsbp
buffbp(i) = 0;
end
for i = 1:tapslp
bufflp(i) = 0;
end
ppg_samples = importdata ('sub1_ppg.txt'); // importing ppg samples
spg_samples = importdata ('sub1_spg.txt'); //importing spg samples
pvdf_samples = importdata('sub1_pvdf.txt'); //importing pvdf samples
for i = 1:22401
x1(i) = pvdf_samples(i) - 2044;
x2(i) = ppg_samples(i) - 2044;
x3(i) = spg_samples(i) - 2044;
106
end
indexlp = 1; //index which gives the first location of low pass filter circular buffer
indexbp = 1; //index which gives the first location of band pass filter circular buffer
for i = 1:8:22401 // storing every eighth PVDF sample array
sample = x1(i)
RESHI = 0;// initializing the result variable
// LOW PASS FILTER
j = indexlp;//save the current sample location in variable j
bufflp(indexlp) = sample//store the current sample
for i=1:tapslp// for loop which iterates to provide the coefficients which further depends on number of
taps
MACS = coefflp(i)//load the coefficient in MACS as operand1
if (j == 1)//determines whether we are at beginning of circular buffer
OP2 = bufflp(j)//If yes then load the sample in OP2 pointed by variable j
RESHI = RESHI + (MACS * OP2)
j = tapslp //Variable j is then set to point to the end of the circular buffer the
// previous sample will be stored at the end of the circular buffer
else //else then
OP2 = bufflp(j)//load the sample in OP2 pointed by variable j as operand 2
RESHI = RESHI + (MACS * OP2)
j = j-1// then set variable j to point to the previous sample which is to the left side of current sample in
the
// circular buffer
end
end
breathing(k) = RESHI //store the result in array labeled as breathing
k = k + 1;
if (indexlp == 119) //if index has reached the end of the circular buffer
indexlp = 1 //set it to point to the first location
107
else
indexlp = indexlp + 1 //else increment it to point to the next location
end
RESHI = 0;
// BAND PASS FILTER
j = indexbp; //save the current sample location in variable j
buffbp(indexbp) = sample;//store the current sample
for i=1:tapsbp// for loop which iterates to provide the coefficients which further depends on number of
taps
MACS = coeffbp(i);//load the coefficient in MACS as operand1
if (j == 1)//determines whether we are at beginning of circular buffer
OP2 = buffbp(j); //If yes then load the sample in OP2 pointed by variable j
RESHI = RESHI + (MACS * OP2);
j = tapsbp; //Variable j is then set to point to the end of the circular buffer the
// previous sample will be stored at the end of the circular buffer
else //else then
OP2 = buffbp(j);//load the sample in OP2 pointed by variable j as operand 2
RESHI = RESHI + (MACS * OP2);
j = j-1;// then set variable j to point to the previous sample which is to the left side of current sample in
the
// circular buffer
end
end
heart(m) = RESHI ////store the result in array labeled as heart
m = m + 1;
if (indexbp == 129) //if index has reached the end of the circular buffer
indexbp = 1; //set it to point to the first location
else
108
indexbp = indexbp + 1; //else increment it to point to the next location
end
end
% Create the complex number array of DFT values, Xk.
xk1 = fft(x1);
xk2 = fft(breathing);
xk3 = fft(heart);
xk4 = fft(x3);
% Create the arrays of magnitudes and phases of Xk.
MXk1 = abs(xk1);
MXk2 = abs(xk2);
MXk3 = abs(xk3);
MXk4 = abs(xk4);
% Create the array of frequency values, fk.
fk1 = 1000*(0:22400)/22401;
fk2 = 125*(0:2800)/2801;
figure(1)
plot(tk1,x1)
xlabel('Time')
ylabel('Magnitude')
title('Time domain plot of Lee Weissman PVDF signal for subject six')
figure(8)
plot(tk2,breathing)
xlabel('Time')
ylabel('Magnitude')
title ('Time domain plot of extracted breathing activity by low pass filter')
109
figure(9)
plot(tk2,heart)
xlabel('Time')
ylabel('Magnitude')
title ('Time domain plot of extracted heart activity by band pass filter')
figure(2)
plot(tk1,x2)
xlabel('Time')
ylabel('Magnitude')
title ('Time domain plot of Lee Weismann ppg signal for subject six')
figure(3)
plot(tk1,x3)
xlabel('Time')
ylabel('Magnitude')
title ('Time domain plot of Lee Weismann spg signal for subject six')
figure(4)
plot(fk1, MXk1)
title('Pvdf frequency plot');
xlabel('Frequency (Hz)');
ylabel('Magnitude');
figure(5)
plot(fk2, MXk2)
title('breath frequency plot');
xlabel('Frequency (Hz)');
ylabel('Magnitude');
figure(6)
plot(fk2, MXk3)
110
title('heart frequency plot');
xlabel('Frequency (Hz)');
ylabel('Magnitude');
figure(7)
plot(fk1, MXk4)
title('spg frequency plot');
xlabel('Frequency (Hz)');
ylabel('Magnitude');
111
APPENDIX G
Plots of digital signal processing
1500
1000
500
Amplitude
0
-500
-1000
-1500
-2000
0
5
10
15
20
25
Time (s)
Figure G.1. Time domain plot of PVDF signal for Subject 1.
150
100
Amplitude
50
0
-50
-100
-150
0
5
10
15
20
25
Time (s)
Figure G.2. Time domain plot of SPG signal for Subject 1.
112
500
400
300
Amplitude
200
100
0
-100
-200
0
5
10
15
20
25
Time (s)
Figure G.3. Time domain plot of PPG signal for Subject 1.
7
x 10
1.5
1
Amplitude
0.5
0
-0.5
-1
-1.5
0
5
10
15
20
25
Time(s)
Figure G.4. Output of the low-pass filter that represents the breathing signal in the PVDF
signal for Subject 1.
113
7
x 10
3
2
1
Amplitude
0
-1
-2
-3
-4
0
5
10
15
20
25
Time (s)
Figure G.5. Output of the band-pass filter that represents the heart signal in the PVDF
signal for Subject 1.
1500
1000
500
Amplitude
0
-500
-1000
-1500
-2000
-2500
0
5
10
15
20
Time (s)
Figure G.6. Time domain plot of PVDF signal for Subject 2.
25
114
200
150
Amplitude
100
50
0
-50
-100
0
5
10
15
20
25
Time (s)
Figure G.7. Time domain plot of SPG signal for Subject 2.
300
250
200
Amplitude
150
100
50
0
-50
-100
-150
0
5
10
15
20
25
Time (s)
Figure G.8. Time domain plot of PPG signal for Subject 2.
115
7
x 10
2
1.5
1
Amplitude
0.5
0
-0.5
-1
-1.5
-2
-2.5
0
5
10
15
20
25
Time(s)
Figure G.9. Output of the low-pass filter that represents the breathing signal in the PVDF
signal for Subject 2.
7
x 10
3
2
1
Amplitude
0
-1
-2
-3
-4
0
5
10
15
20
25
Time (s)
Figure G.10. Output of the band-pass filter that represents the heart signal in the PVDF
signal for Subject 2.
116
600
400
200
Amplitude
0
-200
-400
-600
-800
0
5
10
15
20
25
Time (s)
Figure G.11. Time domain plot of PVDF signal for Subject 3.
250
200
150
100
Amplitude
50
0
-50
-100
-150
-200
-250
0
5
10
15
20
25
Time (s)
Figure G.12. Time domain plot of SPG signal for Subject 3.
117
1200
1000
800
Amplitude
600
400
200
0
-200
-400
-600
0
5
10
15
20
25
Time (s)
Figure G.13. Time domain plot of PPG signal for Subject 3.
6
x 10
4
3
2
Amplitude
1
0
-1
-2
-3
0
5
10
15
20
25
Time(s)
Figure G.14. Output of the low-pass filter that represents the breathing signal in the
PVDF signal for Subject 3.
.
118
7
x 10
1.5
1
Amplitude
0.5
0
-0.5
-1
-1.5
0
5
10
15
20
25
Time (s)
Figure G.15. Output of the band-pass filter that represents the heart signal in the PVDF
signal for Subject 3.
2000
1500
1000
Amplitude
500
0
-500
-1000
-1500
-2000
-2500
0
5
10
15
20
25
Time (s)
Figure G.16. Time domain plot of PVDF signal for Subject 4.
119
1000
500
Amplitude
0
-500
-1000
-1500
-2000
0
5
10
15
20
25
Time (s)
Figure G.17. Time domain plot of SPG signal for Subject 4.
600
500
400
300
Amplitude
200
100
0
-100
-200
-300
-400
0
5
10
15
20
25
Time (s)
Figure G.18. Time domain plot of PPG signal for Subject 4.
120
7
x 10
2
1.5
Amplitude
1
0.5
0
-0.5
-1
0
5
10
15
20
25
Time(s)
Figure G.19. Output of the low-pass filter that represents the breathing signal in the
PVDF signal for Subject 4.
7
x 10
3
2
1
Amplitude
0
-1
-2
-3
-4
0
5
10
15
20
25
Time (s)
Figure G.20. Output of the band-pass filter that represents the heart signal in the
PVDF signal for Subject 4.
121
2500
2000
1500
1000
Amplitude
500
0
-500
-1000
-1500
-2000
-2500
0
5
10
15
20
25
Time (s)
Figure G.21. Time domain plot of PVDF signal for Subject 5.
1000
500
Amplitude
0
-500
-1000
-1500
-2000
0
5
10
15
20
25
Time (s)
Figure G.22. Time domain plot of SPG signal for Subject 5.
122
250
200
150
Amplitude
100
50
0
-50
-100
-150
0
5
10
15
20
25
Time (s)
Figure G.23. Time domain plot of PPG signal for Subject 5.
7
x 10
4
3
2
Amplitude
1
0
-1
-2
-3
0
5
10
15
20
25
Time(s)
Figure G.24. Output of the low-pass filter that represents the breathing signal in the
PVDF signal for Subject 5.
123
7
x 10
5
4
3
2
Amplitude
1
0
-1
-2
-3
-4
-5
0
5
10
15
20
25
Time (s)
Figure G.25. Output of the band-pass filter that represents the heart signal in the PVDF
signal for Subject 5.
2500
2000
1500
1000
Amplitude
500
0
-500
-1000
-1500
-2000
-2500
0
5
10
15
20
25
Time (s)
Figure G.26. Time domain plot of PVDF signal for Subject 6.
124
7
x 10
3
2
1
Amplitude
0
-1
-2
-3
-4
0
5
10
15
20
25
Time(s)
Figure G.27. Time domain plot of SPG signal for Subject 6.
250
200
150
Amplitude
100
50
0
-50
-100
-150
-200
0
5
10
15
20
25
Time (s)
Figure G.28. Time domain plot of PPG signal for Subject 6.
125
1200
1000
800
Amplitude
600
400
200
0
-200
-400
-600
0
5
10
15
20
25
Time (s)
Figure G.29. Output of the low-pass filter that represents the breathing signal in the
PVDF signal for Subject 6.
7
x 10
6
4
Amplitude
2
0
-2
-4
-6
0
5
10
15
20
25
Time (s)
Figure G.30. Output of the band-pass filter that represents the heart signal in the PVDF
signal for Subject 6.
126
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