Electrocardiogram analyser with a mobile phone
André Baptista1 and João Sanches2
1
Instituto Superior Técnico, Lisbon, Portugal
andrefsmbaptista@ist.utl.pt
2
Systems and Robotics Institute, Instituto Superior Técnico, Lisbon Portugal
jmrs@isr.ist.utl.pt
Abstract—The Electrocardiogram (ECG) signal
measures the potential of the heart and their beats. A
real normal ECG signal is composed for some
important waves that traduce the different states of the
heart at each beat, this waves are P, Q, R, S, T and U.
By using three electrodes located at bust, in particular
positions with a meticulous orders, it is possible to
measure the electrical activity of the heart.
This paper describes a system that detects cardiac
anomalies in ECG trace based on the mobile phone.
This system analyses the different periods and/or the
different durations of some waves, the P, the QRS
complex, de T wave, the QT interval, the RR period
and the rhythm cardiac. The goal is detect some
anomalies that could happen in a cardiovascular
patient and warn some entity with a message SMS
using the mobile phone.
The acquisition system inject a modulate signal in a
bluetooth headset to communicate and transmit with a
mobile phone that is paired the ECG signal of the
patient.
The mobile phone demodulates the PWM signal
containing the ECG, detect and store the different
waves and before this, the mobile phone find abnormal
intervals as periods in all of this waves.
The whole system and the corresponding hardware
and software modules are described and results are
presented for illustrative purposes in this paper.
Index Terms—ECG, opamp, PWM, python,
electrocardiogram, bluetooth.
1. INTRODUCTION
The acquisition of several physiological signals,
such as the electrocardiogram (ECG), is a current
practice since several decades, mainly for
diagnosis purposes. More recently these signals
are being used for control and interface purposes.
In this scope, the brain computer interface (BCI)
systems have received particular attention in the
last decades.
Currently, some types of systems are capable to
read the electrophysiological signals and make
possible a diagnosis of some diseases. To diagnose
the ECG diseases the most important systems are
the Holter, ECG at rest, ECG with exercise test
between others.
The cardiac diseases are one of the most causes
of death in occidental population. Is estimated that
cardiovascular diseases have caused the deaths of
26.3% of Portuguese people[1].
At this article is presented a modern type of
system that is capable to make diagnosis exams to
cardiovascular diseases. This cardiac anomalies
system detect works in mobile phone with a
particularity that is possible to use all day. With
this system, it is possible detect some different
types of cardiac diseases like Branch block,
Ventricular hypertrophy, Atrial tachycardia,
Wolff-Parkinson-White
syndrome,
Atrioventricular block 1st block, Atrial fibrillation
, bradycardia, tachycardia and arrhythmia[2].
This work was developed in Nokia N81 with
S60 series, a mobile phone with big computational
power that was made to run specific applications
like games. The decision to use this phone has
forced the SymbianOS operating system were and
that would be the python programming
language[3].
There are some equipment, both measurements
and monitoring the signal output, but none with
the features listed in the equipment described in
this article, namely, using the audio channel of the
bluetooth headset to transmit the ECG signal [7],
to analyze the ECG signal directly on the phone
and use the phone to make emergency call in case
of stroke [8].
This paper is organized as follows. In section 2
is described the electric cardiac system and some
of diseases verified. In section 3 is described the
system. In section 4 are described the
experimental results and the section 5 concludes
this paper.
chambers of the heart, the atria, which represents
activation in the P wave. Next, the electric current
flowing in the direction of inferior’s chambers of
the heart, the ventricles, thus creating the QRS
complex, is representing the activation of these.
The T wave represents the wave of recovery,
while the electrical current spreads back over the
ventricles in the opposite direction.
2. CARDIAC ELECTRICAL SYSTEM AND SOME OF
THEIR ANOMALIES
The heart is a modular organ in the middle of
the chest that has both the right and the left side, a
cavity higher (atrium) that receives the blood and
a lower cavity (ventricle) that takes him out. To
ensure that the blood flow in one direction, the
ventricles have a valve entrance and one exit.
The diagnosis of heart disease tends to become
established from the clinical history and physical
examination of the patient. There is a wide series
of tests and procedures to facilitate and make more
accurate the diagnosis. They include records of
electrical activity of the heart as the ECG, Holter,
echocardiography, magnetic resonance imaging,
positron emission tomography and cardiac
catheterization and the most used are the ECG and
these will be that the article will be based.
2.1. ECG
2.3. Anomalies
In this work, the anomalies that will be detected
are the Branch block, Ventricular hypertrophy,
Atrial
tachycardia,
Wolff-Parkinson-White
syndrome, Atrioventricular block 1st block, Atrial
fibrillation,
bradycardia,
tachycardia
and
arrhythmia [4] [6]. To detect all of this anomalies,
the system need to detect some characteristics in
ECG signal, this characteristics are:
 Wave P duration;
 QRS duration;
 Interval PR duration;
 Rhythm.
3. SYSTEM DESCRIPTION
The developed system is composed by the
components that could see in Fig. 1.
The ECG is a fast, simple and painless, in which
amplify the electrical impulses of the heart. To
identify the natural pacemaker that initiates each
new beating heart, the nerve pathways leading to
the stimuli, the speed (frequency) and heart
rate.[5]
To record an ECG arise small metal contacts
(electrodes) according to a given derivation,
obeying the triangle of Einthoven and according to
the derivation of type II.
2.2. ECG waves
An ECG represents the electrical current flows
through the heart during a contraction and every
part of this stream is designated alphabetically.
Each heartbeat starts with a boost primary
physiological pacemaker of the heart, the sinoatrial node. This impulse active first the upper
Fig. 1 - Circuit and their components.
The components of this system are:
1. Box with acquisition circuit and
amplifier circuit and with Bluetooth
headset;
2.
3.
4.
5.
On/Off button;
USB port to power the circuit;
Audio output for connection to PC;
Telephone token female used to entrance
of the three contacts of ECG signal
acquisition;
6. Telephone token male used for entry of
the three contacts of ECG signal
acquisition;
7. Pin positive;
8. Pin mass;
9. Pin negative;
10. Electrodes;
11. Audio cable for PC connection.
As described above, the developed system has
six main modules: the acquisition, the modulation
and transmission, the demodulation, the
processing and the alarm generation. Each of the
developed modules will be described in detail in
the following sections.
is used. The first stage is a voltage follower to
isolate the acquisition circuit from the
amplification chain. Each one of the other three
stages is a low gain low-pass filter to reduce the
high frequency noise.
After the buffering stage, it is placed a bandpass filter so that its frequency response can
capture only the ECG signal characteristics,
leaving a clean signal to amplify.
The gain and offset controls are important to
adjust the output dynamic range of the processed
signal to the input dynamic range of the modulator
[9].
Acquisition
circuit
Signal conditioning
Band-pass filter
[0.218, 113.532]Hz
First stage
K1=10
Second stage
K2<10
Third stage
K3=2.2
3.1. Acquisition system, hardware and signal
transmission
Fig. 2. Acquisition module block diagram.
According to the stated objectives, using a
bluetooth headset for the transmission of the signal
picked up by electrodes placed according to the
derivation chosen, the transmitted signal is an
audio signal. This signal is "injected" into the
microphone of the headset and will be sent with
bluetooth transfer to the phone, then this signal is
demodulated and analyzed.
The acquisition of the ECG signal is performed
by three electrodes, one electrode is placed below
the second vertebra towards right scapula, the
positive electrode, and one in the same direction
but on the left, the mass pin, the third electrode is
placed one inch below the electrode on the left, the
negative pin.
The system used consists of an acquisition
circuit, a band-pass filter where the bandwidth was
reduced, and three floors of amplification with a
final gain of 220. The ECG signal works in a band
ranging from 0.05 Hz up to 100Hz band passes
very close to ideal for an ECG signal, Fig. 2.
To do that, an amplification chain with four
stages (based on rail-to-rail operational amplifier)
The filtered and amplified ECG signal is used to
modulate in pulse (PWM) a 480𝐻𝑧 square wave
carrier to be transmitted by the audio channel.
The modulated signal is injected into the audio
input of the bluetooth headset and this signal is
transmitted to the mobile phone, which will be
analysed.
The PWM modulator is described in next
section.
3.2. PWM modulation
The PWM was created from the integrated
circuit NE555. The circuit was designed which is
in datasheet the same integrated circuit, that circuit
could be seen in the Fig. 3.
thus introducing a resistive divider in order to
lower the output voltage while ensuring no
overrun bluetooth headset microphone.
The signal was obtained to meet the objectives
set for an output frequency below 1𝑘ℎ𝑧 and with
an output voltage around 1𝑉 .
3.3. Demodulation
Fig. 3 - Modulation PWM circuit.
In developing this circuit, referred to the
Protel2004 program to create the design of printed
circuit board PWM modulator with the distinction
of being designed in order to use the space
previously occupied by the integrated circuit
LM331, packaging dip-8, developed to the FM
modulator which was used on this circuit board,
see Fig. 4.
The PWM signal is a signal modulated by pulse
width. To demodulate this signal it used one lowpass filter second order Butterworth, as it was
intended demodulation with a minimum number
of calculations possible.
The pass-band of the signal ECG it’s between
0.05ℎ𝑧 and 100ℎ𝑧 and because this, it was used a
cut frequency of the 100ℎ𝑧. With this cut
frequency and a 𝜉 = 0.9999 ≅ 1, we obtain the
next equations.
𝑤𝑛2
⟺
𝑠 2 + 2𝜉𝑤𝑛 ∙ 𝑠 + 𝑤𝑛2
(2)
1002
⟺
𝑠 2 + 2 × 1 × 100 ∙ 𝑠 + 1002
(3)
𝐻(𝑠) =
Fig. 4 – Design top and bottom of the circuit board
PWM modulator.
𝐻(𝑠) =
𝐻(𝑠) =
After the design to be used in printed circuit
board, went to the creation of its circuit, and the
board is on the Fig. 5
Fig. 5 - Circuit board PWM.
It was desired output frequency of less than
1𝑘ℎ𝑧, and scaled to the values of resistors and the
capacitor to archive this objective. It was used the
𝑅1 = 𝑅2 = 10𝑘Ω and 𝐶 = 100𝑛𝐹, this values are
shown in equation (1).
𝑓0 =
1.44
= 480ℎ𝑧
(𝑅1 + 2 × 𝑅2 ) × 𝐶
(1)
After completion of the circuit and the scaling
of output frequency, changed manually the circuit
𝑠2
10000
+ 200 ∙ 𝑠 + 10000
(4)
With a sampling frequency of the 8𝑘ℎ𝑧, the
discrete system is:
𝐻(𝑧) =
7.748 ⋅ 10−5 ⋅ 𝑧 + 7.684 ⋅ 10−5
𝑧 2 − 1.975 ⋅ 𝑧 + 0.9753
(5)
𝐻(𝑧 −1 ) =
7.748 ⋅ 10−5 ⋅ 𝑧 −1 + 7.684 ⋅ 10−5 ⋅ 𝑧 −2
1 − 1.975 ⋅ 𝑧 −1 + 0.9753 ⋅ 𝑧 −2
(6)
Using the Z transform, the equation low-pass
filter is given for equation
𝑦(𝑛) = 7.748 ⋅ 10−5 ⋅ 𝑥(𝑛 − 1) + 7.684 ⋅ 10−5
⋅ 𝑥(𝑛 − 2) + 1.975 ⋅ 𝑦(𝑛 − 1)
− 0.9753 ⋅ 𝑦(𝑛 − 2)
(7)
The results of the demodulation are in line with
expectations and in accordance with the desired
one. This demodulation made the phone work
quickly enough, and the system is only dependent
on the absence of current hypothesis of direct
access to stream audio bluetooth headset
3.4. Processing
The application has been developed in Python
programming language. Python is being used more
often by programmers, because it is a
programming language platform and operating
system independent.
Python also uses several modules, developed by
users from all around the world with all kind of
different purposes. Here, it is used mainly the
PyAudio module, for audio stream input
acquisition.
The application takes 3𝑠 of the ECG signal
modulated PWM and demodulates it renders the
detection algorithm of the various intervals,
checks for abnormalities and collects more 3𝑠
signal.
After receive and demodulate the ECG signal in
PWM, the mobile phone need to search some
periods and the different waves in the real signal
ECG. When all the wave intervals are discovered,
will find some combinations of the signal ECG
characteristics and will find if this signal has some
anomaly. If the system finds some anomaly, it will
send a SMS to a competent entity.
The relevant intervals discovered are the duration
of the P wave, the T wave, the QRS complex, the
PR interval and the QT interval. The system
discovered yet the RR, PP intervals and the
rhythm. In the Fig. 6 is represented the algorithm
used.
The algorithm begins by finding represented a
positive peak in the signal. When this peak is
found, the peak voltage, determines whether it is a
peak P, T, R, for each of these peaks is at different
levels of tension.
In the case of P and T waves, the program
through two cycles, one advancing and one
retreating into the signal, determines the limits of
the waves, looking for the point where it gives the
reversal of the slope on each side.
In the case of the QRS complex, the program
searches the limits of the R wave and hence the
peak Q and S using the algorithm described above,
but in this case, the algorithm searches for the
beginning of the Q wave and the end of the S
wave and thereby obtaining the QRS PR and QT.
For each signal cycle, all intervals are collected
for delivery and all conditions of all the anomalies
selected are checked. If the algorithm finds any
abnormalities in the ECG tracing, the program
collects information from the time and type of
fault to a log file. Next, the program sends the
same information to an authority by SMS in
accordance with the number set in your phone.
4. EXPERIMENTAL RESULTS
At this chapter it will be described the different
experimental signals, all of them are very
satisfactory like we will see. The acquisition
system is able to easily acquire the ECG signal,
filter it and amplify it. At the first step, when the
system acquire the real signal we obtain a signal
like a signal in Fig. 7 where we can be seen all the
important waves like P and T waves and the QRS
complex.
Fig. 6 - Flowchart that represents the algorithm to
detect the waves.
Fig. 7 - ECG signal acquired original.
When we obtain the original signal, this signal
will pass in the three amplifier steps in the
amplifier circuit. This circuit will clean some
noise at the signal and we will see the signal
amplified at the Fig. 8.
Fig. 10 - Signal ECG demodulated.
This signal is used to detect the important waves
to a correct detection of the cardiac anomalies. So,
to detect the waves, are used the different levels of
the signal like we could see in the next figure and
like is explained in the chapter before, see the Fig.
11.
Fig. 8 - Signal ECG amplified and filtered.
After the amplification step the signal are
modulated with PWM circuit described in the
chapter before. This signal is transferred and
received in the mobile phone. We could see the
signal in the Fig. 9.
Fig. 9 - Signal ECG modulated in PWM.
When the signal is received in the mobile phone,
the program use the algorithm described in the
chapter 3.3 and obtain the Fig. 10 signal.
Fig. 11 - Figure illustrates the tensions of the
levels chosen.
5. CONCLUSIONS AND FUTURE WORK
With this system it is possible to prove that
mobile phones are an important factor for the
continuous monitoring of cardiovascular patients
by giving them a better and more guarded quality
of life.
This system is still possible to create algorithms
for the detection of other cardiac anomalies.
We could tell that the mobile phones have a lot
of computational power at this time and this is
very important with biological and monitoring
systems.
This paper concludes that the use of
conventional bluetooth headset is possible, and
even a cost effective and robust, as evidenced in
the developed system.
For the portability of the system in future will
have to seek a solution that will pass through,
place the electrodes in order to be closer, making
the system more comfortable for the patient.
I predict that in future, with increased
computing power, this system can have better
results and it is also possible in the near future
direct access to streaming audio headset.
For the circuit of the acquisition, future work to
develop, is to create an even more dedicated
circuit, operating in a frequency band ideal for a
range of [0.05 Hz-100 Hz] and with a lower
sampling frequency in order to reduce volume of
calculations.
ACKNOWLEDGMENT
The authors of this paper would like to thank the
coach of the Laboratories of electronics Campus
Taguspark of the Instituto Superior Técnico, Mr.
João Pina dos Santos.His knowledge provided
vital support for the conclusion of this system.
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