Measuring Ocular Microtremor
Thomas Rutkowski
Vivian Phinney
Salman Al-Saif
Mark Hasemeyer
Steve Carroll
Ocular Microtremors (OMT)
-Low-amplitude, high-frequency
tremors of the eye. (20-100Hz)
-Caused by random, ground-state
signals on oculo-motor nerves
-Oculo-motor nerves originate in
brain stem. OMT indicates
brainstem health.
-OMT correlated with patient’s
level of consciousness.
-Gives strong indication of the
chances of recovery for coma
patients.
System
Module
Overview
System
Overview
Waveform
Generator
Test MUX
Bedside Monitor
(Philips MP-60/70
or Agilent V24/26)
OMT
Simulator
Philips
VueLink
Module –
M1032A
Sensor
(Provided)
Analog Input/
Preprocessing
Circuitry Amp
For MCU, currently looking
at Atmel AVR32 with 10-bit
A/D and integrated DSP
functions,50 MHz clock.
Power Supply
Microprocessor
with Integrated
A/D, UART, and
DSP
LCD
SD Card
Basic CPU Architecture and Connectivity
16-bit Parallel Interface
3.5” Graphic
LCD
Sensor
Signal
Conditioning
AVR32UC3B1256 Microcontroller
GPIO
Controller
10-bit A/D
UART
Controller
16-bit Timer
256kB Flash
PLL – 50 Mhz
CPU Clock
SPI Controller
16Mhz
Crystal
SD Card
MAX3380E
UART Level
Shifter
RealTerm/
Bedside
Monitor
3.3 V Power
Supply
Start Sampling
Buffer 0
Find OMT
frequency from
FFT output just
completed
Perform inverse
FFT on
frequencies
within valid
range.
Send frequency
and waveform
samples to
UART(monitor),
LCD, and SD card.
Processing Algorithm
Wait until Buffer 0
Full (1 sec)
Start Sampling
Buffer 1, Start FFT
on Buffer 0
Wait until Buffer 1 Full
(1 sec) – FFT on Buffer
0 finishes ~1 ms
Wait until Buffer 0 Full
(1 sec) – FFT on Buffer
1 finishes ~1 ms
Start Sampling
Buffer 0, Start FFT
on Buffer 1
Currently using 1024 sample buffer and
1024 kHz sampling frequency, giving 1 second of data in buffer.
Signal Processing – General Overview
 Using FFTs, much faster than DFT algorithms
 Atmel studio has several built in FFT algorithms that
require minimal modification
 But… it’s not working as we had anticipated
 Further work in DSP is needed
 Just recently got sampling, buffers, and FFT working
 Further testing required to find optimal DSP algorithm
Signal Sampling
 Using the built in ADC in the Atmel processor to sample
data
 The input voltage ranges from 0V to 3.3V (adjustable), the
signal needs to be scaled and clamped to avoid causing
damage to the processor
 Use of a 8:1 voltage divider, or an op-amp circuit with gain
K = 0.125, assuming a maximum 12V input from the sensor
IC
 A 3V zener diode is used to clamp the analog input, or a
comparator circuit
Signal Sampling (contd.)
-Sensor output is in the range ±12 V
-A/D takes 0 - 3.3 V
-First stage inverts and scales sensor output to ±1.5 V
-Second stage adds 1.5V DC offset for new range of 0 – 3 V for A/D
Signal to be sampled
 Frequency components at 15Hz, 90Hz, and 165Hz
Signal recreated with MATLAB
Sampled Signal, Frequency Content at 15Hz, 90Hz, 165Hz
280
270
Voltage [mV]
260
250
240
230
220
210
200
0
20
40
60
80
100
Time
120
140
160
180
200
FFT
 As with other things involving signal processing, we are
currently experimenting with the built in FFT functions
 The FFT routines functioned properly with minimal
modifications
 Going forward, two possible solutions to processing that we
are considering
 After determining the frequency of the OMT signal, a
sinusoidal wave is generated with varying amplitudes
proportional to the OMT
 Using wavelet processing
 We will know more once we’ve done more careful testing,
since our sensor is very sensitive, there is a lot of room for
error
FFT (contd.)
 Filtering and Noise Reduction
 As mentioned previously in PDR, the OMT frequency range
lies between 40Hz and 120Hz
 Use of a high pass filter at 20Hz, and a low pass filter at 150Hz
 We identified the main source of noise as that coming from
various power lines across the room
 A notch filter is used (bandstop) for the frequency range
57Hz-62Hz
 Sensor is sensitive, picks up the slightest movement, another
sensor might be used to provide a differential solution
 The other main artifact that affects the signal is heartbeat and
voice, we are still considering solutions to both problems
FFT (contd.)
 The following slide represents an example of the same
signal sampled above
 We used the FFT algorithms to represent the
frequency content of the analog signal
 Simple processing was done to filter out unwanted
frequency content (below 20Hz, above 150Hz, and
60Hz)
 The slide after that is a capture of Vivian’s OMT
frequency content
Processed signal
Fourier Transform of Processed Signal
2
1.8
1.6
1.4
Energy
1.2
1
0.8
0.6
0.4
0.2
0
0
50
100
Frequency [Hz]
150
Captured OMT Signal over 1
Second Interval
 We believe that thorough testing and experimentation
is very important to the success of our project
 After CDR, we will continue with OMT processing
Power Management
 Utilizing a medical grade power supply, since project is
not power centric, plus it is safer to go with this option
and avoid any risk or harm to the experimental
subjects (basically us)
 ELPAC MED113TT, provides three regulated outputs,
5V, ±12V
 LP2951 voltage regulator from TI will be used to power
the Atmel processor
Power Management (contd.)
Bedside Monitor
• Leasing from Medelco
• Lease will include:
Philips MP70 Touch Screen
Monitor
M1032A Vuelink Interface
Module
M8048A FMS (Flexible
Module Server)
M3001A MMS (Multiple
Monitoring System)
• Possibly:
 M1032A#K66 Cable with
DSUB-9 connector
VueLink Cable Pinout Showing UART Tx/Rx Lines
VueLink Connector
DB-9 Connector
Backup Plan - Analog Input Signals
LCD Display
-Parallel or SPI Interface to LCD
- 4-Wire Resistive Touch Panel
- Will display small waveform and OMT
frequency, in addition to bedside monitor
display.
-Touch-screen menu may allow user to
configure data-logging options, sampling
rate, and buffer size.
http://www.crystalfontz.com/product/C
FAF240320K-T-TS
SD Card Socket Board
Routes SD card pads to solder able
through-hole connector.
We will use SPI mode to read/write from
card.
Card requires 3.3 V
Data Logging can be started using touch
screen menu on LCD.
Breakout Board for SD-MMC Cards
http://www.sparkfun.com/commerce/produ
ct_info.php?products_id=204
Risks and Contingencies
 Blowing the sensor piezo-transistor or integrated IC amp
 Eyetect shipped a backup sensor earlier this week
 The FFT signal processing algorithm is a concern
 Waveform spiky and aperiodic
 Now that we have the sampling, buffers and basic FFT
working, can test other processing strategies:



Wavelets
FIR Filters on Buffer followed by Peak-Count Algorithm
Statistical Analysis
Current Budget
Product
Unit Cost
Amount
Total Cost
PROCESSING/MANUFACTURING
Atmel AVR32 Development Kit
4-layer PCB
Packaging
179.00
66.00
95.00
1
3
2
179.00
198.00
190.00
INTERFACE
Philips M3 Bedside Monitor
Vuelink M1032A
600.00/mo.
-
2.5
1
1,500.00
-
M3001A MMS (Multiple Monitoring System)
M8048A FMS (Flexible Module Server)
Vuelink connector to DSUB9 Cable
LEMO Circular Push Pull Connectors
2GB SD Flash Card Model CT2GBSD
175.00
24.92
7.99
1
1
1
3
1
175.00
74.76
7.99
http://www.dotmed.com/listing/594385
http://mouser.com/
http://www.newegg.com/
Breatkout Board for SD-MMC Card BOB-00204
LCD Display - CFAF240320K-T-TS
17.95
30.74
3
3
53.85
92.22
http://www.sparkfun.com/
http://www.crystalfontz.com/
Voltage Regulator LP2951_33 (3.3V)
Surface mount bypass capacitors (25
capacitors)
Surface mount resistors
Power Connector (5-pin)
ALPS_SKHUQBO56A Switch
0.96
5
4.80
http://www.newark.com/
4.50
0.20
5.50
2.00
2
30
2
2
9.00
6.00
11.00
4.00
http://www.ti.com/
http://www.amazon.com/
JB Saunders
http://www.allelectronics.com
Printing Manuals
Poster
40.00
12.00/ft.
1
4 feet
40.00
48.00
250.00
100.00
1
2
250.00
200.00
MEDICAL GRADE POWER SUPPLY
ADMINISTRATIVE COSTS
Rider Insurance Policy for Bedside Monitor
Shipping/Handling Fees
MARGIN
7%
213.05
TOTAL COSTS
OUTSIDE FUNDING
TOTAL FUNDING
3,256.67
Outside Funds
EyeTect
UROP
Northrop Grumman
3,000.00
800.00
200.00
4,000.00
Provider
http://mouser.com/
http://www.4pcb.com
http://www.firstcut.com/
http://www.medelco.com/patient_monitors.htm
Division of Labor
Tom
Vivian
Mark
Salman
Steve
Power
Power Supply
X
Powering Sensor
X
X
MCU
Signal Sampling - A/D
X
DSP of Signal
X
X
X
X
Interface
LCD Interface on Dongle
X
Data Capture on SD Card
X
Condition Sensor Output
Patient Bedside Monitor Interface
X
X
X
X
X
X
Manufacturing
PCB
X
Dongle
X
X
Documentation
Technical Manual
X
X
User's Manual
X
X
UROP
X
Extra (if time)
Data Mining/Trend Evaluation
X
X
Expo
Deliverables
• Bedside Monitor Interfaced
• LCD on Dongle Functioning
• Packaging Finalized
Milestone 2
• PCB
• Sized for Production
• SD Card reader Integrated
• Signal Processing Implemented
• CAD Design sent to Plastic Casing Company
Milestone 1
•
•
•
•
Obtain Bedside Monitor and Open Interface Specification
SD Card Interfaced with Microcontroller
Sample the Sensor Signal (save on SD Card)
Finalize which Sampling Algorithm to Use
Timeline
Questions?
In Order of Appearance:
Tom
Steve
Salman
Mark
Vivian