Does EMG Noise Affect the Readings of Heart Rate Monitors? Sistania Bong, Andrew Choe, Lauren Gardner, Hsiang Hsu, Nikki Jackson, Tyler Rice,

Malvika Sanghvi, Jin Eun Shin Facilitators: Dr. Julia Babensee, Rhoades Sturkie

Group C6

Abstract

Objective: This study was carried out to determine whether EMG noise causes an

error in heart rate measurement when using a household heart rate monitor. The Sportline

S7 heart rate monitor watch was the device used to determine the effects. Our null

hypothesis is that the EMG noise will not cause a significant difference in the heart rate

measurements. Our alternative hypothesis is that the EMG noise will significantly

increase the heart rate measurements. Methods: Our procedure will include 16

participants. To have a constant EMG noise we will be using a TENS unit to cause the

muscles to contract. Results: Our results show that there is a significant increase in heart

rate caused by muscle contraction. Our p-value is 1.13745e-0.6, which is lower than our

value is 0.05. Because of this we are able to reject our null hypothesis. Conclusion: In

conclusion, our first recommendation is that the company should improve the filter used

in the wrist watch that is suppose to filter out the EMG noise caused by muscle

contraction. Our second recommendation is that the user should not be using the device

while exercising, which causes muscle contraction.

Introduction

The Electrical Conductivity of the Heart, Mechanical Events in The Heart, and The

Electrocardiograms

The electrical and mechanical events in the heart correspond to a waveform called

electrocardiogram (ECG)(OpenStax College,2013). This is used to record the electrical

activity of the circulatory system through the use of electrodes placed on several different

locations on the body. The ECG signal is comprised of P, Q, R, S, and T waves which

visually reflects the sum of electrical activity found in the heart. This triggers the heart to

contract and relax, producing heartbeats (Figure 1).

Figure 1: Normal ECGs (Silverthorn, D. U., 2013).

The electrical conductivity in the heart is divided into two major events:

depolarization and repolarization. Depolarization starts at the sinoatrial node (SA node)

in the right atrium of the heart. The SA node is a pacemaker cell, and has the ability to

depolarize the cell by itself without being triggered by the action potential from adjacent

cells. Since the SA node is located in the right atrium, depolarization first occurs in the

right atrium and is followed by the left atrium. This causes the both atria to contract.

Atrial depolarization and contraction is indicated in the P wave (Phase 2 and Phase 3).

The depolarization wave is then transferred to the atrioventicular node (AV node)

through internodal tracts. The AV node is composed of bundle of His, also called the

atrioventricular bundle, which will branches out into two further bundles: the left and

right bundle. The right and left bundles consist of branches called Purkinje fibers. The

right and left bundles consist of branches called Purkinje fibers. The depolarization wave

is then transferred to the right and left ventricle through the Purkinje fibers that then

release electrical signals into ventricular myocardium and depolarize the ventricles. The

depolarization of the myocardium will trigger the ventricles to contract. The events in

which the depolarization wave is transferred to the ventricle and allows for the ventricles

to contract and eject blood out of the heart are represented in the QRS wave (QRS

complex) (Phase 4) and S wave (Phase 5). The atrial repolarization is not specifically

emphasized but incorporated in the starting of the QRS complex. After the blood

ejection, the ventricles start to repolarize which causes the ventricles to relax. The

repolarization of the ventricles followed by the ventricular relaxation is indicated in the T

wave. Lastly, the interval between the T and P wave indicates that there is no electrical

activity in the heart during this brief time because the SA node will begin the

depolarization process over again (Phase1) (OpenStax College,2013) (Silverthorn, D.

U.,2013).

Figure 2: Electrical and Mechanical Events of the Cardiac Cycle (OpenStax College,

2013)

The electrical signal that is detected by the heart rate monitor reflects the change

of cell membrane potential due to the charged ions activities in the cardiac muscle cell.

The changes of the cell membrane potential generate an action potential that enables the

cell to depolarize. There are two types of cardiac muscle cells, myocardial contractile cell

and myocardial autorhythmic cells, each with different action potentials. The action

potential in the myocardial contractile cells (Figure 3) is initiated by the depolarization

wave from the adjacent cells. Because of the wave of depolarization, the membrane

potential becomes more positive. The voltage-gated Na+ channels open, and Na+ ions

diffuse into the cell and depolarize the cell until the membrane potential reaches its peak

at +20mV and Na+ channels close. When the Na+ channels close, the voltage-gated K+

channels open, allowing K+ ions to leave the cell, thus repolarizing the cell. This

repolarization occurs for a brief moment because two events take place: the membrane

permeability of K+ decreases while the membrane permeability of Ca2+ increases. The

voltage-gated Ca2+ channels open and Ca2+ ions enter the cell. The increased of Ca2+

influx and the decreased of K+ efflux causes the action potential to flatten as it is shown

in the diagram (Figure 3). After the plateau, the permeability of K+ increases and

permeability of Ca2+ decreases. The voltage-gated K+ channels open, and K+ ions rapidly

leave the cell repolarizing it back to its resting membrane potential.

The action potential in the myocardial autorhythmic cells (Figure 4) are initially

generated by the SA node in the right atrium. The membrane potential of the SA node

(pacemaker potential) starts at -60mV and depolarizes the cell to threshold at -40mV. As

soon as the cell reaches -40mV, the SA node will fire the action potential and trigger the

voltage-gated Ca2+ channels to open allowing Ca2+ ions to flow in to the cell and

depolarize the cell to the peak of its membrane potential, which is almost +20mV. At the

peak of the membrane potential, the Ca2+ channels close and the voltage-gated K+

channels open. The opening of the K+ channel allows the K+ to exit the cell resulting in

repolarization of the cell back to -60mV and stimulates the SA node to start the

depolarization process all over again.

Figure 3: Action Potential of a Cardiac Contractile Cell

Figure 4: Action Potentials in Cardiac Autorhythmic Cells (Silverthorn, D.

U.,2013)

Muscle Contractions (Electromyographic Interference / EMG Noise)

The electromyographic (EMG) signal is associated with the electrical activity in

the muscle fibers that reflects muscle contraction and relaxation. EMG signals have a

high potential of corrupting ECG signals. This is called electromyographic intereference

or EMG noise. According to the U.S. Patent for S-Pulse Technology wristband heart rate

monitor, EMG noise potentially interferes with the ECG signal due to the similarity of

EMG signal characteristics with the characteristics of the ECG signal. EMG noise falls

into the same range of frequency as the ECG signal (Lo, T. Y.-C., & Tsai, Y. S., 1998).

Consequently, EMG noise overlaps the frequency spectrum of the QRS complex

(Friesen, G. M., et al, 1990).

Figure 5: ECG Corrupted with EMG (Friesen, G. M., et al, 1990)

The Device: Sportline S7 Heart Rate Watch

Sportline S7 Heart Rate Watch is an Any Touch Heart Rate Monitor,

commercially used to track the intensity of workouts. It is essentially like being

connected to a low-cost, portable ECG/EKG. It is based on Any-touch technology, a

patented technology of the Sportline company, which makes use of S-PULSE

technology. Further, it also helps in monitoring calorie burn and the fat-burning zone.

Mechanism of the Device

The digital watch employs a three contact approach, in which two of the electrical

contacts are positioned on the front of the watch, where the user places his fingers, while

the third contact is at the back of the watch. All three contacts are connected to a differential

amplifier. The heartbeat signal is picked up when the front contacts are brought in contact

with the user’s touch and then made to pass through the differential amplifier. This

amplifier amplifies signals while also suppressing common mode noise ( unwanted input

signals). Referring to Figure 6 the differential amplifier is represented by 68. Next, the

output of the differential amplifier enters the pass-band filter (#64). This filter consists of

the following two types of filters, which essentially filter out noises above and below the

frequency range in which the desired heartbeat rate will lie:

1. Low Pass Filter –which has a threshold of 25-40 Hz; all signals with frequencies that

fall in that range get filtered

2. High Pass Filter-which has a threshold of 5-15 Hz; all signals with frequencies that

fall in this range get filtered.

Next, the analog signal is amplified in amplifier 66 dB that has a gain of 50-1000 dB so

that the overall gain is about 1000-10,000 dB. Finally, after filtering the signals so that they

may be refined, the signals will be eliminated as much noise as possible. Then the analog

output of the amplifier 66 is applied to the input of the analog-to-digital converter (68),

which is integrated onto the microcontroller integrated circuit. From here, the digital

signals will be input into the microcontroller (#70) for further signal processing. The digital

samples are then filtered to further remove remnants of frequencies above and below the

range of frequencies in which heartbeat will lie. This is done to suppress power-line hum at

approximately 50-60 Hz so as to generate filtered digital samples. Finally, the signals are

subject to the enhancement signal processor. This processor enhances heartbeat peaks in

the filtered digital samples to generate enhanced digital samples. It comprises of 3 different

units:

1. Differentiator : Determines the slope of peaks in the filtered data and generates a

slope signal which defines the magnitudes and signs of the slopes of each portion

of each peak.

2. The squaring processor : Squares the results from the differentiator by looking up

results in a lookup table that shows the squares of possible values that could be

output from the differentiator

3. The moving average processor : Computes the moving average of the positive

values signal and outputting a moving average signal which defines the moving

average over time. Finally, the enhanced digital samples are again processed to

determine the individual’s heartbeat rate.

4.

Figure 6: Detailed Flowchart of the Mechanics of the Heart Rate Monitor

Figure 7: Detailed Flowchart of the Enhancement Signal Processor

Figure 8: Sportline S7 Heart Rate Monitor Transcutaneous Electrical Nerve Stimulation (TENS)

For our experiment we wanted to create a constant EMG regulation and eliminate

any experimental variations, such as the difference of muscle contraction by using stress

balls. In order to achieve the regulation, we selected a supplementary device that was

provided by one of our group members, Omron HV-F128.

The HV-F128 uses the TENS technology to massage the muscles and relieve the

pain. The TENS technology works similar to how an electronic muscle stimulator (EMS)

does. Both stimulators generate electrical impulses that stimulate the targeting nerves

through the skin, which in turn cause the muscles controlled by those nerves to react and

contract (Jones, I., & Johnson, M. I., 2009). However, the only difference between EMS

and TENS is their targeting nerves. While EMS are designed to stimulate muscle motor

nerves, TENS devices are designed to stimulate sensory nerve endings. Even though the

TENS device targets to stimulate the sensory nerves, it also stimulates the muscle motor

nerves, which lie near the sensory nerves, and cause the muscles to contract passively.

The TENS device, HV-F128, makes muscle contract passively and generate a constant

EMG noise that we desire.

From the user manual, we obtained that the frequency HV-F128 generates is 1 ~

1200Hz and the power consumption is about 85 mA. Maximum output voltage is less or

equal to 90V and maximum output current is less or equal to 10 mA (during 1kilo-omega

load).

Method and Materials

Materials

This experiment required the use of two separate material sets: materials to

prepare the participant and devices for reading heart rate and stimulating the participant’s

forearm.

To perform the study, the participant was sprayed with one spray bottle of tap

water and was then wiped down with sterile cotton balls. This adhered to our proper

method of preparing the participant. In terms of devices used for reading heart rate and

stimulating muscle contraction, the Sportline S7 heart rate watch and the Omron HV-

F128 TENS device were used. The Sportline S7 watch uses one-touch technology and

was purchased at Walmart (Walmart.com, 2013). The Omron HV-F128 massager was

imported from Japan (Omron Healthcare Co., Ltd.), and the English manual was found at

Omron-healthcare.com.

Preparation of the Participant

The participant was prepared by being notified of the exclusion criteria of the

experiment. Participants with metal implants or pacemakers and those who were not

members of the Georgia Institute of Technology’s BMED 1300 course were asked to not

take part in the study. Eligible candidates to be participants were given a consent form

that outlined the risks and benefits of participating in this study. Once consent was given,

the participant gained entrance to the testing area where they were asked to roll up their

sleeves (if necessary) and expose their left forearm. From here, the experimenter sprayed

the wrist of the participant and wiped the area with a cotton ball to wipe off any materials

that would affect the conductivity of participant’s wrist and forearm.

Control Measurement

The participant was asked to take a control measurement. The experimenter

placed the Sportline S7 wristwatch on the left wrist of the participant, and the participant

was asked to place their index and middle finger of their right hand onto the device’s

touch sensor. The experimenter recorded this heart rate measurement (heartbeats/minute)

in a secure document for analysis at a later point. The watch was then reset using a reset

button on the side of the watch.

Experimental Measurement

The watch remained on the participant as a second modified measurement was

taken. The experimenter applied the two silicone pads of the TENS device onto the

forearm of the participant. Using the device settings (tap-mode, 35 Hz), the experimenter

turned on the TENS device massager and set the intensity to a level of four. After twenty-

five seconds, the participant again was asked to place their index and middle finger of

their right hand onto the device’s touch sensor. The experimenter then recorded the heart

rate (heartbeats/minute) and removed the watch and massager from the participant’s left

arm. This concluded the experiment, and the participant was released.

Statistical analysis

Based on the literature previously described, the sample size of this experiment

used was 16. This was found by using a power of .97, an effect size of .95, and a level of

significance or alpha of 0.05 when using a statistical program called G*Power (Faul,

Erdfelder, Lang & Buchner, 2007).

To determine the significance of the difference between the control and

experimental heart rate measurements, a one-tailed matched pairs t-test was used. Alpha

was set to 0.05 and p values smaller than alpha were considered significant.

Results

Based on the results our raw data in Fig. 1 ( see Appendix) of the 16 participants

of the study, the P-value, the mean differences, the standard deviation of differences and

standard error of differences between the experimental group and control group were

found to be 1.1375e-6, 63.6875, 34.4978, and 8.6244, respectively as shown in the table 1

(see Appendix for formulas).We decided to use a one-sided matched pairs t-test to

analyze our data, as we needed a good test for a smaller samples size (<30) with a large

difference. We used the match-pairs t-test because the same participant was used for both

the control and experimental trials. We used the one-sided t-test based on the one-sided,

positive results we found in the research. In addition, our results also further endorse our

assumption for the one-sided t-test with a positive, one-sided trend.

The box plot and graph 2 depicts that our data was slightly skewed to the left

based on the five number summary in reference to the mean. Table 2 shows the five

number summary: median, minimum, maximum, first quartile, and third quartile which

were, respectively, 72, 2, 110, 45.75, and 92.5. When the mean of 63.6875 lies to the left

of the median of 72, the bulk of the points are to the right of the center, giving a left

skew. The interquartile range of the box plot can be easily seen in the histogram where

the dense region occurs (heart rate between ~45.75 and ~92.5). The histogram uses

intervals of 2 to receive the most normal-looking distribution. The general appearance of

a normal distribution in our data is shown as a dotted line in the graph. Our Q-Q plot,

Fig.3 (see Appendix), had a r2 value of .96, giving a high correlation with little variance

from the trend line and therefore, a fairly normal distribution.

Graph 3 shows that the control mean without EMG noise, is almost half of the

experimental mean with EMG noise. The significance level of <.05 is denoted with ***.

Our error bars represent standard error.

Graph 4 shows the p-value, the area under the curve in the direction of the hypothesis, in

our case, to the right of the t-statistic. The p-value is the fraction of the total area under

the curve where the null hypothesis is correct. The blue region is the area to the right of

the t-score and the red region represents the area of our p-value (our p-value is too small

to be graphically visible). Our p-value was too small for the program we used to

calculate the graph (the lower threshold on this program is p=.0001). We are able to

reject the null hypothesis with 99.99988625% ((1-p)X100%) confidence.

One-tailed Matched

Pairs t-test

p-value 1.1275e-6

Standard Deviation of

Differences

34.4978

Standard Error of

Differences

8.6244

Variance of Differences 1190.096

Mean of Differences 63.6875

t 7.384536226

Table 1

Population Size 16

Median 72

Minimum 2

Maximum 110

First Quartile 45.75

Third Quartile 92.5

Interquartile

Range

46.75

Outerliers None

Table 2

Graph 1: Box and Whisker Plot

Graph 2: Histogram

Graph 3: Mean Change

Graph 4: T-Score (Hypothesis Test Graph Generator)

Discussion

After the data was all collected, we noticed a few trends in the data. All of the

experimental points were either reoccurring values of 150, 152, or 189, with the

exception of three lower points with the values of 68, 75, and 79; while the control values

were almost completely unique. These reoccurring values could have been explained by

error in the TENS device or the wristband. One potential error we considered in using the

TENS device was that the frequency, translating close to that of ECG signal and

hypothesized EMG noise, could have directly influenced the heart rate reading. We could

only standardize the TENS device within a frequency range, so the slight change in those

recurring frequencies could have been just that, for example the heart rate monitor could

have picked up the electrical signal directly from the TENS device, and not from the

actual EMG noise created by skeletal muscles from the TENS stimulation, which is what

we were attempting to mimic. Another concern with the use of the TENS device was

whether or not the device stimulated only skeletal muscles or also increased the heart rate

by stimulating the heart muscle as well. In the case that the TENS device stimulated the

actual heart muscle, the heart rate monitor could have given a true reading without error.

Although we did not collect data to calibrate the actual heart rate, the participants stayed

in a sitting position throughout the experiment and no one showed any sign of increased

heart rate while taking the second reading. Had a participant’s heart rate actually

increased by about 70 beats per minute in approximately 10 seconds (about the time in

between readings) , physical changes would be apparent.

Another potential explanation for the three reoccurring values could have been the

wristband and its filtering systems. It may be possible that over a certain frequency

reading, over the normal range, the watch may error. There could be a chance that the

filters could error and display randomly those three values. This seemed very unlikely,

however, as the device is meant for exercise and values around 150 beats/minute are not

completely out of the question while exercising. The smaller three experimental values

also struck curiosity when analyzing the data. When taking these readings, we noticed the

participants complained of not feeling the TENS massager’s stimulation. These

participants also had more hair on their arms, which could have led to an error in

applying the muscle stimuli. Though the smaller values did skew the data slightly left,

they were still positive differences and were not calculated as outliers. Some of the

smaller increases show a more realistic change for heart rate in about a 10 second

interval, but considering that the participants did not seem to be affected by the TENS

device, the increase was most likely due to other variables such as anxiety from the test.

Regardless, the use of a TENS device caused error in the wristband monitor, increasing

the heart rate readings above the actual level.

Conclusion

According to articles and patents we researched, the EMG noise which is

produced by muscle contractions significantly influences the heart rate that is measured

by our device due to the one of the characteristics of EMG signals, which is EMG noise

falls in the same range of frequency of the ECG signal. Using the data gathered in our

experiment, we conducted statistical analyses, and found our p value to be 1.1375e-6.

Because the p value was substantially lower than our value (0.05), we rejected the null

hypothesis in favor of alternative hypothesis, therefore supporting the idea that EMG

noise causes a significant increase in heart rate measurements. The origin of the error,

which is EMG interference that causes the device to give a less accurate heart rate

reading is the limitation of the learning process in the mechanism to suppress the noise.

Because the learning process of our device has a low threshold, it is set to allow for other

signals like the EMG noise to be considered as heart rates. Therefore, we recommend that

the producer of this device increases the ability of the learning processor to better

distinguish ECG signals from any other ECG-like noise such as EMG noise and to

improve the sensitivity of the filter to suppress any unwanted noise.

Citations

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Appendix

Subject Number Control Reading TENS Reading Difference

1 70 150 80

2 92 189 97

3 77 152 75

4 79 189 110

5 74 79 5

6 95 189 94

7 105 150 45

8 73 75 2

9 96 189 93

10 86 152 66

11 84 150 66

12 61 152 91

13 102 150 48

14 79 150 71

15 79 152 73

16 65 68 3

Table 3: Raw data

Formulas:

Standard deviation: s = where the mean is mean of our data

Mean:

Standard Error:

t-statistic:

t-score: This was found using the t-table in the appendix. The t-score was taken at the .05

alpha level with 15 degrees of freedom.

P value: P-value was calculated in excel as a 2 array, matched pairs, one-sided TTEST.

(Young, K.)

Graph 5: Bar graph of plotted differences

Graph 6: Q-Q plot of data