Engineering, 2013, 5, 6-9
doi:10.4236/eng.2013.55B002 Published Online May 2013 (
Study of Situation Based Environment towards Noise
Reduction during ECG Acquisition
Noraini Abdul Samad, Rubita Sudirman, Nasrul Humaimi Mahmood, Yoong Yee Yan
INFOCOMM Research Alliance, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Johor Bahru, Johor, Malaysia
Received 2013
Even with the development of more advanced technology of ECG, there are still problems on interference to ECG sig-
nals. Many attempts have been made to detect and eliminate the source of noises and artifacts from the original ECG
signals. Several studies have been done to observe and study the EMI effect, however, most of them only focus on the
EMI effect of mobile phone during ECG acquisition. Thus, this study is emphasized on the interference prob lem when
other medical devices were being used together with the ECG device. The R-R peak distance of the ECG signal was
detected by using QRS detection algorithm invented by J. Pan and W. J. Tompkins. The data from the experiment
showed that even the EMI from the medical devices did not affect the physical shape of ECG, but it does affect the R-R
peak distance of the ECG signal.
Keywords: Electrocardiogram; Electromagnetic Interference; R-R Peak Distance
1. Introduction
The increasing number of medical devices used in health
care facilities [1] has guided many researchers to study
about the potential problem of electromagnetic interfer-
ence on medical device [2]. This study is done due to the
concern towards the possibility of malfunction of life
supporting system, such as electrocardiogram and elec-
troencephalogram when it is being used in a close prox-
imity with other medical devices. Electrocardiogram
(ECG or EKG) is a simple yet painless test that used to
record the electrical activity of the heart [3]. ECG device
is used to detect and amplify the tiny electrical changes
on the skin that caused when the heart muscle depolar-
izes during each heartbeat. Those tiny electrical changes
on the skin will then convert into wavy lines to be ana-
lyzed by the doctor. Since ECG was able to record the
electrical activity of the heart, it is being used in diagno-
sis for the heart disease. Generally, the recorded ECGs
and EEGs signal will always be contaminated with many
types of noise and artifact. In this stu dy, the concern will
be emphasized on the interference problem from other
medical devices that being used together or nearby with
the ECG and EEG device. It is important to ensure that
there will be no interference problem occurs when it is
being used together with other medical device since
some equipment used in healthcare centre is designed to
emit electromagnetic energy [4]. Several studies have
been done to observe and study the interference effect,
however, most of them only focus on the effect of mobile
phone during EEG and ECG acquisition. Those types of
studies always treat medical devices as the ‘victim’ and
mobile phone as the ‘source’ of electromagnetic inter-
ference. [5-7].
2. Literature Review
Since numerous types of Electromagnetic Interference,
EMI were introduced, the effect of the EMI on the elec-
tronic device performance being studied. The study in-
cludes the tests of radiofrequency susceptibility on 8
types of medical devices [5] which shows that all 8 de-
vices being tested is easily affected by the emitted elec-
tric field at frequencies varies from 1 MHz to 2000 MHz
with electric field intensity at 10 V/m. Most of the tested
devices such as Fetal Monitor and Infant Incubator
showed incorrect presentation of data when the electric
field intensity was as low as 0.012 V/m. Based on the
result of the study, the electric field intensity emitted by
cellular phone or two ways radio undoubtedly can affect
the performances of medical devices since the electric
field of those two devices are 15 V/m and 5 V/m respec-
tively. Even it is hard to foretell the occurren ce of failure
causes by EMI, it is highly recommended to avoid or
reduce the usage of cellular phone and two ways radio in
hospital area especially the area that equipped with life
supporting system and in intensive care unit since it is
the most critical area.
Copyright © 2013 SciRes. ENG
In order to strengthen the idea to ban the usage of cel-
lular phone in hospital area, there is a study done to iden-
tify the susceptibility areas in the hospital by performing
immunity test on medical devices [6]. The immunity test
was done by subjecting several medical devices to elec-
tric field generated by cellular phone that operates in its
maximum power. The result from the study shows that
80% of medical devices that being tested was affected by
the radiated electric field.
As many researchers only focusing on the EMI effect
cause by cellular phone, few of them study on the effect
of interference of medical device when it is used in close
proximity to other medical devices [8]. The study in-
cludes several case studies on performances degradation
on apnea monitors, automatic implantable cardioverter
defibrillators (AICD) and Cobalt 60 therapy system.
Based on the result of each type of study, almost every
author comes up with the same conclusion and recom-
mendation such as the needs to establish clear policies
for the usage of mobile phone in critical area in the hos-
pital. They also emphasize on the safety distance be-
tween medical devices and any other type electronic de-
vice especially the one that emit powerful electromag-
netic signal.
3. Methodology
The measurement was taken in the situation where dif-
ferent types of medical devices operated during ECG
data acquisition within 1 meter range of distance. KL-
75001 Electrocardiogram Module was used to take ECG
signal from a healthy subject (a female, aged 20 years old)
and with the assistance of oscilloscope to display the
signal. As a precaution, the subject was ensured to be in a
good health condition and not taking any medication
before the experiment. The acquired signal was saved
in .txt format for further observation and investigation
through Matlab. The signal was compared with the ref-
erence signal (free from noise) in term of the wave pat-
tern and RR Peak Distance.
Data analysis was done to emphasize that EMI from
other medical devices when being used in the same area
with the ECG does affect the ECG data. There are 8
types of medical device that being tested during the ex-
periment (one at a time). The duration of experiment for
each type of medical device is 10 second. Table 1 and
Figure 1 below shows the list of medical device and the
block diagram of the experiment respectively.
4. Result and Discussion
Several testing had been conducted to observe the ECG
signal patterns. All data from those testing were obtained.
From those data, analysis was made to clearly state the
comparison between the reference signal and the ac-
quired signal.
Table 2 showed the signal acquired from the experi-
ment. Physically, there is no obvious alteration towards
the wave shape. The shape of the ECG signal is still
maintained. The noise is hardly compared or extracted
from the ECG signal. Unlike the electric field intensity
that radiated from cellular phone or two ways radio,
electric field intensity emitted by medical devices is
definitely low. Even the signal does contain several type
of noise; it does not alter the amplitude of PQRS of the
Table 1. Types of medical device that being tested during
the experiment.
Figure 1. QRS Detection algorithm [9].
Copyright © 2013 SciRes. ENG
Table 2. Signal acquired from experiment.
Medical Device Signal produce
Reference signal
Wacom Tablet
Non Invasive Blood
Pressure Cuff
Electro muscle
Ultrasound Thera-
peutic Device
Infusion Pump
Micro spirometer
Table 3. R-R peak signal of each device.
Medical device R Peak Signal
Wacom Tablet
Electro muscle stimu-
Non Invasive Blood
Pressure Cuff
Infusion Pump
Micro spirometer
Since the reference signal and the test signal are hard
to differentiate in term of physical shape, the average of
Copyright © 2013 SciRes. ENG
R-R peak distance of each signal were compared. In or-
der to calculate the R-R peak of the ECG, th e QRS com-
plex detection was done by using Pan & Tompkins algo-
rithm. The detection of R-R peak is important during
ECG signal analysis as its can be used to show th e condi-
tion of the heart, calculation of heart rate and even can be
used to define various heart defectiveness [10-11].
As stated previously in introduction section, even the
electric field intensity emitted by medical devices is low;
it does affect the ECG signal. This phenomenon is
proved by the graph of R-R peak distance of each tested
medical device shown in Table 3. The detection of R-R
peak was done based on the Pan & Tompkins’s algorithm
as shown in Figure 1. As the R-R distance of the test
signal and the reference signal was compared, it shows
that the space between each R peak is not evenly spaced
and its include 6 of 8 (75%) tested medical devices such
as ultrasound, infusion pump, Wacom tablet, EEG, and
blood pressur e cuff.
5. Conclusions
Different approaches in analyzing ECG signal should be
done to get better observation on the effect of EMI to-
wards the signal. As described in [3], the author calcu-
lated the peak to peak value of noise embedded in the
signal and many other authors that observed any changes
in device function, including failure, distortion of dis-
played informatio n, erroneou s readout or activation of an
alarm. However, some types of analysis may be unable to
detect the effect of EMI on ECG signal. Thus for this
study, analysis was done by observing the RR peak dis-
tance in order to strengthen the fact that EMI from other
medical device can definitely affect the ECG signal data.
Even all medical devices are certified with their own
electromagnetic compatibility standard, some of them
still being affected by the EMI within or lower than the
standard value [5]. In spite of the simplicity of the analy-
sis, the result however emphasized the need of separating
the easily susceptible medical device from the other
medical device for better performance. Several precau-
tions must be taken in order to avoid any harmful effect
caused by device malfunction due to EMI.
6. Acknowledgements
The author would like to express our appreciation to
Ministry of Higher Education (MoHE), MyBrain15 and
Universiti Teknologi Malaysia for supporting and fund-
ing this project under vote Q.J130000.2623.09J28 .
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