Stress and Heart Rate Variability

Prashant Suryanarayanan

and Dinesh Kant Kumar

School of Electrical and Computer Engineering,

RMIT University,

PO Box 2476V

Melbourne,

Australia - 3001

Abstract. Do people get accustomed to stress? Do people react differently to

a stressful environment when they have experienced the situation earlier? This

paper reports research to determine whether the above is a myth. It reports the

measurement of heart rate variability (HRV) of people when subjected to con-

trolled stress conditions and these conditions are repeated over different days.

The results indicate that while there is a large variability between different par-

ticipants, there is a consistent reduction in the heart rate variability from the ﬁrst

experience of the stress condition to the subsequent applications of similar stress

conditions.

1 Introduction

Autonomic responses in psychologically challenging situation are a major area of psy-

chophysiological study and research. Psychophysiology is deﬁned as the study of rela-

tions between psychological manipulations and resulting physiological responses, and

has developed over the years to promote better understanding between psychological

and physiological processes [1]. There are number of anecdotal evidences suggesting

the change in heart rate (HR) with stress of the person. Patients suffering from cardiac

conditions are often asked to reduce their anxiety and psychological stress. Changes

in cardiac activity had been observed by early scientists related to psychological phe-

nomena [1]. In the recent past, researchers have used heart rate and its variability as a

measure of mental load [2]. Variability of heart rate has also been used for ‘lie detector’

applications.

While the phenomena of change in heart rate with stress of people seems to be

widely accepted, Indian society has known the use of techniques such as yoga and med-

itation to control the cardiac activity for thousands of years. In our modern technology

driven society, biofeedback is being considered for helping individuals have some con-

trol on their cardiac activity. In each of these, the individual makes a conscious effort

and often undertakes training to develop a control over their heart rate.

Social health scientists believe that this stress causes increased cardiac stress and

results in long term damage to the body of the individuals living under these conditions

Suryanarayanan P. and Kant Kumar D. (2005).

Stress and Heart Rate Variability.

In Proceedings of the 1st International Workshop on Biosignal Processing and Classiﬁcation, pages 68-77

DOI: 10.5220/0001194000680077

 SciTePress

[3], [4], [5]. But in our modern society, some of us are regularly exposed to stress and

anecdotal evidence suggests that we get accustomed to this stress. It is then arguable

that people who are used to living under stress may be developing immunity from the

stress at their physiological levels. It has been argued that stressful environment be-

comes less challenging to an individual who is used to working in such an environment

and such an individual will have little change in their heart rate when under stress.

Thus, it maybe suggested that the bodies of people who work in stressful and challeng-

ing professions would be able to cope with the stress easily with little changes to their

cardiac activity compared with other people. This paper reports experimental research

to test the above commonly held beliefs. The paper reports tests conducted on differ-

ent days to determine the correlation between changes to heart rate as the participants

became accustomed to the controlled stress conditions. For this purpose, controlled ex-

periments were conducted where electrocardiogram of the participants was recorded

and correlated with the controlled stress conditions.

1.1 Electrocardiogram

Electrocardiogram (ECG) is the electrical potentials of the heart and generally recorded

non-invasively from the surface of the body. The ﬁrst known equipment to record ECG

was invented by Williem Einthoven. The origin of the electrical activity measured by

ECG is in the cardiac muscle ﬁbres. ECG can be divided in phases of depolarization and

repolarization of different sections of the heart. The most signiﬁcant section of ECG is

the QRS complex, the peak of which is ’R’ wave. QRS corresponds to the contraction

of the left ventricle.

ECG is a repetitive signal and corresponds with the beating of the heart. The rate

of repetition of ECG, measured using QRS peak, corresponds with the heart rate. The

HR of different people is not comparable due to differences such as body size, age

and genetics. Heart rate of an individual varies with number of factors including stress

and physical exercise. Due to these reasons, there is a very large inter and intra subject

variability and hence heart rate and ECG repetition are not useful for comparison. But

variation of heart rate is a more reliable measure of changes to the cardiac activities [6].

1.2 Heart Rate Variability

The heart rate variability (HRV) has been recognized as a non-invasive means to as-

sess the state of autonomic nervous system [7]. The autonomic nervous system (in-

voluntary nervous system) consists of two components; the Sympathetic and the Para-

sympathetic branch. Increased activity of sympathetic branch causes an increase in the

heart rate while increase in Para-sympathetic branch causes the slowing of heart rate.

When the individual is under stress, the sympathetic activity is more profound than

the Para-sympathetic activity causing an imbalance in the autonomous nervous system

(ANS) and hence the HR of the person increases [8]. HRV analysis is a measure of the

variability in heart rate; speciﬁcally, variability in intervals between successive R waves

- ”RR intervals”. This is also called as Interbeat Interval (IBI) and is deﬁned as time in

milliseconds between two normal R to R waves of an ECG. The variations of the heart

rate are affected by a diverse number of factors such as the metabolic activity (related

to physical activity) and emotional activity. The change in heart rate affects the overall

well-being of the person including their physical abilities and mental and emotional

capabilities. Drastic change in HR is known to affect the individual’s capability to take

decisions, solve problems, and the overall perception of the events and environment

[9]. The relationship between mental stress and HRV is a very active area of research

for human-machine interface. Number of studies have been reported that have analyzed

HRV with mental stress to identify the impact of various factors on our wellbeing such

as during physical work [10], with controlled breathing [11], with and without vocaliza-

tion [4], [12], effect of individual differences on stress responsivity [13], with electrical

stimuli [1]. The studies suggest that HRV is an effective, objective and non-intrusive

measure for mental stress evaluation.

This paper reports the study conducted to determine whether repeated exposure to

stress reduces the impact of emotional and psychological stress on the HRV of the

individuals. For this study, mental tasks have been used as the laboratory emotional

and psychological stressors. Based on other reported studies, tasks requiring mental

arithmetic (MA) have been used (e.g. [10]; [11]; [12]). The mental tasks that were

applied as stimuli ranged from simple to difﬁcult mathematical operations, and memory

tests (e.g. English sentence reordering etc.).

2 Methodologies

The aim of this research was to identify the changes in HR due to emotional and psy-

chological stress. Towards this aim, controlled experiments were conducted where the

HR was recorded when the participant were made to undertake the mental tasks, with

all other conditions kept unchanged. These experiments were repeated for three days.

Participants performed ﬁve minute simple mental tasks on three consecutive days.

For each day, participants were asked to solve a series of mental tasks that are detailed

below.

2.1 Mental Tasks

The participants were given a number of mental tasks on each day, design of these tasks

adopted from [1]. These tasks consisted of three set of tasks; word memory, numeric

and tasks requiring planning. The set of these tasks were repeated three times (one par-

ticipant did this four times). Between each stimulus, the participants were encouraged

to relax for about one minute. In accordance with [12], the participants were asked to

vocalize their responses to the mental tasks. The mental tasks stimulus to which the

participants were subjected is described below:

2.2 Day 1

The ﬁrst mental task that was given to the participants was a ’memory task’. The par-

ticipants were given eight randomly selected commonly used mid-size English words

and were asked to read these aloud (excluding 3 punctuation marks). Ten seconds after

this was completed, they were asked to repeat the eight words in the same order.

The second mental task for the day was a quantitative problem involving one step,

single digit multiplication. This required the participant to calculate the hourly speed of

the car, given the distance the car travelled for 15 minutes.

The third task required the participant to unscramble a jumbled word. The word was

selected randomly, it was ﬁve or six characters long, and of common usage.

2.3 Day 2

The tasks on the second day were similar to that of the ﬁrst day, but were in a different

order and of greater complexity. The ﬁrst task was a numeric task, similar to the second

task of day one, where the participant was given a simple single digit multiplication

task.

The second task for the second day was also a numeric task where the participant

was asked to divide a randomly generated ﬁve digit number by ’7’ to the second decimal

places orally. The third task was a two digit oral multiplication. The fourth task was a

memory test, similar to task one on day one.

2.4 Day 3

The tasks and the order of the tasks used on the earlier two days were randomly selected

for the third day. The actual words and numbers were changed for each experiment.

3 Participants

Sixteen (male and female) University students volunteered to participate in the study.

All participants were in good health with no history of cardiovascular disease and were

not under any medications that may affect their cardiovascular functions. All partici-

pants were advised to abstain from caffeine, alcohol and nicotine for at least 2 hours

before testing.

4 Apparatus

Electrocardiogram (ECG) were measured using a BIOPAC ECG100C ampliﬁer. The

ECG was measured using Ag-AgCl disposable sensors with a high conductivity wet

gel. AcqKnowledge (Biopac) software was used to record the ECG. The sampling rate

was 200 samples/sec. The analysis was done ofﬂine using MATLAB.

5 Procedure

The experiments were conducted in accordance with the University Human Ethics

Committee approval. The participants were informed that they were free to stop the ex-

periment when they so wished without giving any reason. The participants were made

aware of the details of the experimental procedure, the overall aim of the project and

were made familiar with the laboratory and the apparatus. The participants were pro-

vided with the plain language statement of the experiments. They were included in the

experiments after they signed the consent form. The room was air-conditioned with

temperature maintained between 20

C and 22

C throughout all the experiments.

At the start of each session, the participants washed their hands using warm wa-

ter and soap free cleanser; they sat down in a comfortable chair. Disposable Ag/AgCl

electrodes were attached in the 3-lead conﬁguration. The location of the electrodes was

marked to ensure repeatability over the different experiments. The apparatus was cali-

brated to ensure reproducibility.

The participant was asked to relax for ﬁve minutes after the electrodes were attached

to them. At this end of this period, the participant continued to relax for another ﬁve

minutes, and during this time their ECG was recorded. This ECG corresponded to the

relaxed state and HR during this period was taken as the base level for all other com-

parisons. At the completion of this period, the participant was given a series of mental

tasks while their ECG was being continuously recorded. The instants when the stimu-

lus (mental task) was administered and when the participant completed the task were

recorded.

The experiments were repeated on three different days. The experiments were con-

ducted at the same time each day to reduce variability due to the time of the day.

6 Data Analysis

The ﬁrst step of the analysis involved identifying the QRS complex. This involved a

series of band-pass ﬁlters, differentiators and squaring the differentiated signal, a tech-

nique described by Pan and Tompkins [14], [15]. This algorithm is based on the slope,

amplitude and width of the ECG. An auto-threshold selection was done using two clus-

ter unsupervised learning using nearest neighbour criteria described in [16].

Heart rate (HR) was computed by measuring the R-R intervals from the ECG signals

using the QRS detected above. Heart rate variability (HRV)was subsequently calculated

using the software package Advanced HRV Analysis [17].

For the purpose of studying the inter-day variation, data was normalized by consid-

ering the ﬁrst day as the reference point.

7 Statistical Analysis

After extracting the HR from the ECG recordings, statistical analysis was performed

to identify the variability and the signiﬁcance due to the stimulus. The analysis was

performed using the Data Analysis tool-pack add-in provided with Microsoft Excel. A

Student t-test was performed on the data, which gives the probability that the difference

between the two means is caused by chance. It is customary to say that if this probability

is less than 0.05, then the difference is ’signiﬁcant’ and it is not caused by chance. The

t-test analysis is appropriate whenever one needs to compare the means of two groups.

The t-test is a ratio, with the numerator being difference between the two means or

averages and denominator being measure of the variability or dispersion of the scores

as expressed below:

t − value =

Dif ference Between the Group M ean

V ariability of the Groups

To ﬁnd the numerator, the difference between the means of the groups is calculated.

To ﬁnd the denominator, which is also called as the standard error of the difference, the

variance of each group is calculated and is divided by number of people in the group.

By taking the square root of the sum of both the variances we get the standard error.

The variance is the average of the square of the distance of each data point from the

mean. It is also known as mean squared deviation.

The t-value will be positive if the ﬁrst mean is larger than the second and negative

if it is smaller. Once you compute the t-value you have to look it up in a table of sig-

niﬁcance to test whether the ratio is large enough to say that the difference between the

groups is not likely to have been a chance. To test the signiﬁcance, you need to set a

risk level called the alpha level. Alpha level is the risk of rejecting the Null Hypothesis

when in fact it is true. In other words, stating a difference exists where actually there is

none. Alpha risk is stated in terms of probability (such as 0.05 or 5%). The p-value is

the probability of ﬁnding a difference between the two group means and as explained

above if this p-value is less than 0.05, then the difference is ’signiﬁcant’ and it is not

caused by chance.The alpha level was always set to 0.05 for all the t-test performed. A

Paired t-test was performed on the mean HR for all the participants paired for:

– The same question position on different days.

– Between different question on the same day.

A Paired t-test is normally used to compare means on the same or related subject

over time or in differing circumstances and it does not assume that the variance of both

populations are equal. A two sample t-test with unequal variance was also conducted on

the heart rate for each of the participants to determine the overall HRV for an individual

on different days.

8 Results

There was a variation of the total number of questions that were answered by the dif-

ferent participants on different days. The minimum questions answered were nine, and

hence the ﬁrst nine questions for each experiment were considered for the paired t-test

analysis. The two samples t-test with unequal variance to identify changes between the

different days was considered for all the questions answered by the participants on each

of the days. Table 1 lists the mean heart rate of all the participants for all the three days.

The mean heart rate here implies the average of the participants’ heart rate during all the

mental tasks conducted on that day. The tables (2, 3, 4) list the p-values for two-tailed

distribution analysis of the data for the following

– Table 2 for identifying changes due to different questions on each of the three days.

– Table 3 for identifying changes due to different days.

– Table 4 for identifying changes due to each of the questions on different days.

Table 1. Mean Heart Rate of the all the participants during the mental tasks.

Participant Day 1 HR Day 2 HR Day 3 HR Day 2/Day 1 Day 3/Day 1

1 100.11 99.96 86.21 0.998 0.861

2 83.43 77.96 75.57 0.934 0.906

3 88.39 81.22 80.27 0.919 0.908

4 75.37 71.34 67.26 0.947 0.892

5 87.92 88.97 84.30 1.012 0.959

6 86.71 78.13 72.59 0.901 0.837

7 86.48 73.55 73.78 0.850 0.853

8 79.98 86.47 70.57 1.081 0.882

9 83.04 83.74 82.29 1.008 0.991

10 89.07 93.23 80.77 1.047 0.907

11 98.43 87.09 81.07 0.885 0.824

12 75.79 68.59 69.08 0.905 0.911

13 82.10 82.25 85.36 1.002 1.040

14 96.52 86.24 95.97 0.894 0.994

15 79.08 75.18 68.89 0.951 0.871

16 78.72 71.49 74.97 0.908 0.952

Table 2. p-values of Paired t-test Between Questions on Same Day for all the participants

Question Day 1 Day 2 Day 3

Q1/Q2 0.0685 0.8166 0.6055

Q2/Q3 0.6044 0.9455 0.0376

Q3/Q4 0.6876 0.2782 0.2611

Q4/Q5 0.4037 0.0996 0.0489

Q5/Q6 0.5541 0.6431 0.1137

Q6/Q7 0.5429 0.9761 0.6027

Q7/Q8 0.5813 0.8892 0.0990

Q8/Q9 0.5937 0.7124 0.4410

Table 3. p-values of Paired t-test Between the Mean Heart Rate for all the participants

T-Test Day 1/Day 2 0.013578121

T-Test Day 2/Day 3 0.243691025

T-Test Day 1/Day 3 0.000128381

Table 4. p-values of Paired t-test Between the Same Task Order on Different Days for all partic-

ipants

Question Day 1 / Day 2 Day 2 / Day 3 Day 1 / Day 3

Q1 0.357610 0.460882 0.035439

Q2 0.055732 0.422769 0.000077

Q3 0.076067 0.228351 0.000106

Q4 0.200562 0.085746 0.000898

Q5 0.018164 0.270949 0.000823

Q6 0.031875 0.596949 0.003855

Q7 0.024736 0.712155 0.013709

Q8 0.022571 0.533416 0.001042

Q9 0.025960 0.728800 0.038138

9 Observations

From Table 1, it is clear that there is a consistent reduction of Heart rate from Day 1 to

Day 2 to Day 3 for a signiﬁcant number of participants. From Table 2, it can be seen

that there is no statistically signiﬁcant change between the HR between two questions

on the same day, although there is drop in the HR of the participant over the experiment

period.

From Table 3, it is observed that there is a signiﬁcant reduction in HRV from day

one to day two. The change from day two to the third day is much smaller and not

signiﬁcant. This is also conﬁrmed by the two sample T-test of unequal variance. It is

also observed (not tabulated) that the average heart rate change between questions on

the same day for each participant considering all participants was found to reduce from

±3.69 on Day 1 to ±2.60 on Day 3. The two sample T-test assuming unequal variance

on the heart rate was also performed for all the questions between the following day

pairs (Day 1/Day 2, Day 2/Day 3, Day 1/Day 3), and it showed a weak relationship of

HR with all subjects considered.

From Table 4, it is observed that between different days, for the same order of the

task, there is small but relatively higher relationship between the HRV compared to the

comparison between different questions on the same day.

10 Conclusion

From the experimental results, it has been observed that the mental tasks do cause a

variation in the heart rate of the participants. It is also observed that this variation is the

greatest on the ﬁrst day. On the subsequent days, even when the tasks are made more

difﬁcult, the variation is smaller. It is also observed that the changes to the variation of

the heart rate is from the ﬁrst day to the second, but from the second to the third the

change is relatively small. It is also observed that the intra-day variation of HR for is

maximum for the ﬁrst day, and minimum for the third day, from ±3.69 to ±2.60. It is

also observed that the HR for different participants was signiﬁcantly different. For the

same participant, the HR for the three days was comparable, even though a reduction

from the ﬁrst day was observed.

Based on the above, the authors conclude that:

– Absolute values of HR of different people should not be compared.

– The HRV reduces when the individual has experienced the experimental stress prior

to the experiment.

– It is suggested that HRV should not be used to measure the emotional impact of

a stimulus on a person as it is possible that they may have got accustomed to the

stress and the experiments.

– It is not possible for the authors to conﬁrm whether people would get accustomed

to overall stressful situations, but it can be stated that when a new stress condition

is reapplied, the impact is less than the ﬁrst application.

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