Psychology, 2017, 8, 978-986
http://www.scirp.org/journal/psych
ISSN Online: 2152-7199
ISSN Print: 2152-7180

Continuous Estimation of Stress Using
Physiological Signals during a Car Race
Wen Wen1, Daisuke Tomoi1, Hiroshi Yamakawa1, Shunsuke Hamasaki1, Kaoru Takakusaki2,
Qi An1, Yusuke Tamura1, Atsushi Yamashita1, Hajime Asama1
Department of Precision Engineering, University of Tokyo, Tokyo, JapanThe Center for Brain Function and Medical Engineering, Asahikawa Medical College, Asahikawa, Japan1
2

How to cite this paper: Wen, W., Tomoi,D., Yamakawa, H., Hamasaki, S., Takakusaki, K., An, Q., Tamura, Y., Yamashita, A.,& Asama, H. (2017). Continuous Estimation of Stress Using Physiological Signals
during a Car Race. Psychology, 8, 978-986.
https://doi.org/10.4236/psych.2017.87064
Received: April 5, 2017
Accepted: May 16, 2017
Published: May 19, 2017
Copyright © 2017 by authors andScientific Research Publishing Inc.
This work is licensed under the Creative
Commons Attribution International
License (CC BY 4.0).
http://creativecommons.org/licenses/by/4.0/
Open Access

DOI: 10.4236/psych.2017.87064

Abstract
Mental stress refers to the feeling of strain and anxiety caused by internal
and/or external factors. Stress may have both positive and negative influenceson cognitive performance. For example, small amounts of stress may improveconcentration, athletic performance, and reaction speed. However, excessive
stress may harm health, and disturb concentration and motor control. Furthermore, increase in short-term stress has a considerable effect on physiological processes such as heart rate and sweating. However, to our knowledge,
so far no study has estimated mental stress through continuous monitoring ofphysiological signals under a situation with various stressors. Therefore, itremains unclear how different physiological signals correlate with each otherand how they change continuously in response to the changes in stressors.
Here, we measured heart rate variability, galvanic skin response, and activityof the masseter muscle in a professional racer during a real car race. Car racing is one of the most dangerous sports, and the competition with other racers
and physical discomfort during the race induce great short-term stresses. We
used factor analysis to examine the relation between the three types of physiological signals, and clarified the events associated with stress (e.g., acceleration, competing car in vision, overtaking). The results showed that the heart
rate variability and galvanic skin response correlated with each other, andwere associated with the event of competition, which brought great mental
stress. In contrast, activity of the masseter muscle did not correlate with theother two physiological signals, but was associated with the events of acceleration or deceleration, which brought great physical discomfort. We concluded
that heart rate variability and galvanic skin response reflect mental stress,
which is associated with an internal desire to win and is triggered by changes
in the external world (e.g., the appearance of competing cars). In contrast,
masseter muscle activity reflects the endurance of body discomfort, which is
not linked to any internal state. Our results indicated that internal and external stressors may be dissociated from each other, and may affect different or-

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W. Wen et al.

gans and physiological receptors.

Keywords
Stress, Physiological Signals, Heart Rate, Galvanic Skin Response,
Masseter Muscle Activity, Factor Analysis

1. Introduction
In psychology, stress refers to the mental state of feeling strain and anxiety, andis usually caused by changes in the environment or internal desire. Small
amounts of stress could be helpful to improve concentration and athletic performance. However, excessive or chronic stress usually causes depression, harms
health, and results in errors in decision-making or motor control. There aremany types of stressors, such as crises, threats, daily annoyances, and life events.
In the present study, we focused on short-term stress, which arises from rapid
environmental changes such as threat, cognitive load, and emotions.
Stress is a significant subjective experience that is difficult to estimate quantitatively from a subjective perspective. An individual may be able to report
whether he/she is undergoing great or small stress, but is not able to quantify it,or to compare the amount of stress between different stressors. However, previous studies have attempted to measure physiological reactions such as heartbeat, sweating, muscle activities, and blood pressure in stressful situations as an
approach to detect or estimate the amount of stress (Hidaka, Yanagi, & Takada,
2004b; Hjortskov et al., 2004; Kurniawan, Maslov, & Pechenizkiy, 2013; Shi et al.,2007; Thayer, Ahs, Fredrikson, Sollers, & Wager, 2012; Yemm, 1969). Previous
studies have revealed useful links between some physiological signals and stress.
However, none of these studies has examined physiological signals in a situation
with multiple and dynamically changing stressors.
In the present study, we focused on the situation of a real car race. We continuously measured three types of physiological signals in a professional driverduring a real race. Car racing is one of the most dangerous sports, and requires
continuous and rapid decisions during a relatively long duration. Both the competition and physical discomfort could be stressors, and multiple stressors maychange rapidly. The present study aimed to clarify the relations between multiple
physiological signals (i.e. heartbeat, sweating, and masseter muscle activity) insuch a situation, and to elucidate the relation between physiological signals anddifferent stressors. Our present findings could not only provide useful estimation of stress during the specific situation of car race but also contribute to theunderstanding of the subjective experience of stress.

2. Methods
2.1. Participant and Experimental Environment
The present study focused on within-individual correlation in a highly specific979

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situation. Therefore, we invited a professional race driver (male, age 27 years) totake part in a real car race, and measured physiological signals during the race.
The study was approved by the ethics committee of the Faculty of Engineering at
the University of Tokyo, and written informed consent was obtained from theparticipant prior to the experiment.
The experiment was performed during a practice session of a race, in which all
racers took part in order to get used to the racing course in advance of the actual
race. The racing condition was the same as the actual one, in which the racers
were free to overtake other cars. Figure 1 illustrates the map of the racing courseof the present study. The racing course contained 12 corners and two slopes, andtherefore required highly precise control of speed and direction.

2.2. Equipment
The present study measured the participant’s heart rate variability (HRV), galvanic skin response (GSR), and muscle activity of the masseter (MAM). All threephysiobiological signals have been reported to be associated with stress (Hidaka
et al., 2004b; Hjortskov et al., 2004; Kurniawan et al., 2013; Shi et al., 2007;
Thayer et al., 2012; Yemm, 1969). However, previous studies used different signals in different stressful conditions, and the relation between these signals anddifferent stressors remains unknown.
The three physiobiological signals were measured using galvanic skin response(GSR) sensors (DL-340, S&ME), heartbeat (electrocardiogram [ECG]) sensors(DL-310, S&ME), and electromyography (EMG) sensors (DL-41, S&ME), andwere recorded in a data logger (DL-3100, S&ME), which was attached to the participant’s waist. The sensors were attached to the participant’s skin using medical tape, and were referenced to the right wrist. Figure 2 illustrates the measuring positions of all three signals.

2.3. Preprocessing of the Physiobiological Signals
All three physiobiological signals were recorded at a frequency of 1000 Hz. The
heart rate variability was recorded from ECG electrodes, which were placed at

Figure 1. Racing course used in the experiment.
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Figure 2. Positions of the sensors. GSR, galvanic skin response; EMG,
electromyogram (to measure muscle activities); ECG, electrocardiogram(to measure heart rate).

the distal part of the sternum and at the sixth rib in the left axilla. An offline
band filter of 0.16 - 500 Hz was applied to the ECG signals. From the ECG, wecalculated the intervals between peaks (R-R intervals), standard deviation of the
R-R intervals (SDNN), and root mean squared successive differences of R-R intervals (RMSSD). The ratio of SDNN to RMSSD was used as the index of HRV.
The GSR was recorded using GSR sensors placed at the left and right mastoids.
Most previous studies placed the GSR sensors on the hand or foot (e.g., Healey &Picard, 2000; Nourbakhsh, Wang, Chen, & Calvo, 2012). However, in the real
car racing, this may disturb the driver’s sensation on hands and feet, and has therisk of causing fatal mistakes. Therefore, we avoided these positions and chosemastoids as the measuring site instead. Finally, the MAM was recorded from twopairs of EMG sensors placed at the left and right masseters. Activities of facialmuscles are useful objective indices of emotion (Cacioppo, Petty, Losch, & Kim,
1986), and jaw muscles in particular are susceptible to mental stress (Hidaka,
Yanagi, & Takada, 2004a; Hidaka et al., 2004b). However, unlike HRV and GSR,
masseters can be activated by consciousness or habit; therefore, the role of the
MAM sensor as an anchor of stress may be different from the former two sensors.

2.4. Procedure
Physiological signals were recorded during the practice session of a real race.
The participant raced over the entire racing course six laps without break. The
race was recorded with a video camera that was installed in the racing car andrecorded the view of the driver. The position of the participant’s racing car wasrecorded using global positioning system (GPS) sensors attached to the car.

3. Results
According to the results of an interview with the participant, the first and second
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laps were considered as a warming up phase and were therefore excluded fromthe analysis. Only the results from the third and sixth laps were included in theanalysis. We used factor analysis to examine the relations between the threephysiological signals. The analysis revealed two factors: the first factor 1) influenced both HRV and GSR, while the second factor 2) influenced MAM. Table 1
summarizes the coefficients of the two factors. The factor coefficient shows theextent to which a factor influences a variable.
In order to determine the events that were associated with the observed activities of the two factors, we abstracted two events from the video and GPS recordsof the car: 1) competition and 2) acceleration/deceleration. The event of competition refers to the time when another car appeared in the visual field of the participant (Figure 3). The event of acceleration/deceleration was calculated fromthe GPS recordings. Figure 4 illustrates the plots of the factor scores in functionof time. The events of competition greatly overlaid with the high scores of factor
1 (i.e. HRV and GSR), while the events of acceleration/deceleration greatly overlaid with high scores of factor 2 (i.e. MAM). Furthermore, a qualitative analysis
showed that 92% of the events of competition consisted of high scores of factor 1(>2.5 standard deviation), but only 37% contained high scores of factor 2. In
contrast, 54% of the events of acceleration/deceleration contained high scores offactor 1, while 63% contained high scores of factor 2. In summary, the results
showed that factor 1 influenced HRV and GSR and was associated with the eventof competition, while factor 2 influenced MAM and was associated with theevent of acceleration/deceleration.
Table 1. Coefficients of the two factors.
Factor 1

Factor 2

HRV

0.362

0.154

GSR

0.346

−0.207

MAM

0.015

0.355

Figure 3. An example of a competition event.
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Figure 4. The scores of factor 1 (a) and 2 (b) plotted in function of time, and the overlay with the events of competition and acceleration/deceleration.

4. Discussion
The present study measured three different physiological signals, all of which areconsidered to reflect mental stress, in a professional driver during a real car race.
We examined the relations between the three physiological signals using factor
analysis, and the association with significant events during the race. The results
showed that HRV and GSR were highly correlated with each other, and were associated with the events of competition. On the other hand, MAM was not correlated with the other two physiological signals, and was associated with the983

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events of acceleration/deceleration. Our present findings suggested that, although all the three physiological signals are somehow affected by stress, they
probably reflect different types of stressors. In particular, HRV and GSR areprobably closer to mental stress, which is mainly the result of internal state ofdesire and triggered by changes in the external world. On the other hand, MAM
may be triggered by physical discomfort, which could also result in stress, but ismore bottom-up and does not require an internal state.
To our knowledge, the present study is the first that measured multiple physiological signals from an extremely dangerous and stressful situation in real life.
Most previous studies examined stress under experimental conditions, and the“real” stress may have not been accurately simulated. The stressors examined inprevious studies were more controlled and had less variability. For example,
cognitive load (Hjortskov et al., 2004; Lattimore & Maxwell, 2004; Shi et al.,2007), unfriendly attitude (Hjortskov et al., 2004; Montirosso, Provenzi, Calciolari, Borgatti, & Group, 2011), and emotion (Kim, Bang, & Kim, 2004) are themost common stressors used in experimental tasks. However, none of them provides continuous and diverse changes in stress, and therefore could not reveal
the relationship between different physiological signals during such changes.
During the car race, the driver was not only under high cognitive load but also
faced a life-threatening situation, and was inspired by the desire to win at every
moment. In addition, because of the high velocity and g-force during acceleration/deceleration, the driver also suffered from stress resulting from physicaldiscomfort. Therefore, the situation of car racing provided an ideal environmentof multiple sources of stress and continuous changes, allowing us to examine thecontinuous changes in physiological reactions that are associated with different
stressors.
The most important finding of our results was that stressors associated withan internal state, such as the desire to win, and that are only linked to external
stimuli may result in different physiological reactions. During the race, acceleration/deceleration brought discomfort to the body because of large g-force, andprobably resulted in a stressful situation. However, both HRV and GSR were notsensitive to such condition, indicating that, although the participant might besuffering from a physical discomfort, his mental stress associated with the interval state did not change significantly. This does not necessarily mean that themental stresses resulted from internal and external states have to be dissociated.
Instead, in most occasions, they might be linked to each other, but learning (e.g.,long-term exposure to a specific physical discomfort) may be able to separate
them, thus controlling mental stress from the bottom-up physical stimuli.

5. Conclusion
The present study showed that competition and physical discomfort may resultin different physiological reactions during a real car race. In particular, we foundthat the event of competition triggered an increase in HRV and GSR, while theacceleration/deceleration event triggered MAM. The results indicated that dif984

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ferent stressors, associated with internal or external states or stimuli, may resultin disparate physiological reactions.

Acknowledgements
This work was supported in part by JSPS KAKENHI (Grant Numbers 26120005).

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