Stress Level Monitoring in Car Racing

Examples of Measurements during Races

Joachim Taelman

, Pieter Joosen

, Jean-Marie Aerts

, Vasileios Exadaktylos

and Daniel Berckmans

BioRICS nv., Technologielaan 3, 3001 Heverlee, Belgium

M3-BIORES, Division Animal and Human Health Engineering, Department of Biosystems, KU Leuven,

Kasteelpark Arenberg 30, 3001 Heverlee, Belgium

Keywords: Stress Monitoring, Racing, Physiological Monitoring, Psychophysiology.

Abstract: Car racing at a high level is a physically and mentally intensive sport. Despite the fact that a large number of

variables are measured on the car during racing, nothing is measured on the driver. It is well known that to

achieve peak performance in competitive sports it is important that the athlete is at their peak both physically

and mentally. The objective of this work is to monitor the mental state of the driver in real-time and provide

this information to the pit crew. A number of interesting cases are presented that show the potential of real-

time stress monitoring in race car driving as a means for driver performance optimisation and as a means to

reduce accidents.

1 INTRODUCTION

Car racing on a circuit is a complex and challenging

sport. Many aspects are influencing the potential

success of winning the race: Not only does the driver

need a competitive car which is pushed to the limits,

but also the driver needs to have the skills to push the

car during the complete race.

In practice, considerable effort and money is spent

by teams to monitor each part in the car with a very

high accuracy: Gears, engine rotations, engine and oil

temperature, accelerations and decelerations,

suspensions, tyre pressure, steering wheel angles, etc.

This information is used to modify and setup the car

perfectly. However, no information is collected from

the driver who is assumed to be sufficiently prepared

while driving this fully monitored car.

Racing is not only a very skilful sport, it is also

very demanding mentally. Each small error can have

a significant impact not only on performance (e.g.

losing the race) but also on safety (e.g. crashing with

potential risks for severe injuries of the driver) and

economic (e.g. financial losses for the team).

Therefore, it is important that not only the car, but

also the (mental) status of the driver is monitored.

Knowing the actual mental state (focused, distracted,

stressed, etc.) of the driver can help improve the

performance of the team in terms of both results and

safety. Monitoring both the car and driver is therefore

beneficial for the individual driver as well as the

team.

Due to the complex conditions, limited research

has been conducted during actual racing situations

(e.g. the works of Schwaberger (1987) and of

Tsopanakis et al. (1998) have looked at stress

hormones, while Matsumura et al. (2011) has focused

on karting) while simulator studies are also limited

(e.g. Katsis et al. (2008) and Katsis et al. (2011)). As

a result, no system is available to monitor the mental

state and the stress levels of race drivers in real-time,

and much less provide this information to the race-

engineers in the pit box for improving performance of

the driver.

In this study, a system was developed and tested

that is monitoring the stress level of the driver in real-

time while the driver is in the race and transmitting

this information to the pit crew. The system is

measuring the stress levels of the drivers and

translates these stress levels to a performance

measure. This is a follow-up of earlier research that

focused on horses (Jansen et al. (2009), Piette et al.,

(2015)) and football (Smets et al., 2013).

The rest of the paper, briefly addresses the system

and methodology while focusing on presenting

interesting cases where the potential of such a system

is shown in relation to increasing performance and

safety in car racing.

Taelman, J., Joosen, P., Aerts, J-M., Exadaktylos, V. and Berckmans, D.

Stress Level Monitoring in Car Racing - Examples of Measurements during Races.

DOI: 10.5220/0006084500590062

In Proceedings of the 4th International Congress on Sport Sciences Research and Technology Support (icSPORTS 2016), pages 59-62

ISBN: 978-989-758-205-9

2 MATERIAL AND METHODS

2.1 System Description

The stress monitoring system consists of the Mio

ALPHA (Mio Global, Canada) heart beat monitoring

device and the Wiko GOA (Wiko SAS, France)

smartphone.

The heartbeat of the driver is measured by the Mio

ALPHA and is sent via Bluetooth to the smartphone

with a frequency of 1 Hz. A custom built app is

combining the heartbeat of the user with the internal

3D accelerometer of the smartphone to calculate the

stress level of the driver as is described below.

Subsequently, this information is sent to a server via

the 4G network where the information is further

processed to calculate the focus zone of the driver as

described below. Finally, the information is

communicated to the pit crew via a custom made app

on a tablet.

This is depicted in Figure 1.

Figure 1: Schematic diagram of the system.

2.2 Stress Level Monitoring

The principle of stress level monitoring of the driver

is the same as the one presented by Piette et al. (2015)

for monitoring the stress level of the horse rider (with

the model adapted for the car driver). More

specifically, the Heartbeat of the driver is

decomposed into the different components (basic

metabolism, thermoregulation, physical and mental)

and subsequently, the mental component is used to

estimate the stress level of the driver.

The mathematical model used for the estimation

of the physical component of the heartbeat has the

form of a first order input/output transfer function

with activity as input and heart rate as output.

2.3 Focus Zone

In sports applications, some minimum stress level is

required to perform, as shown in Figure 2. If there is

too much stress, the athlete is in a distress stress zone,

while if the athlete is not stressed, the athlete might

be too calm and is not performing as well (Diamond

et al., 2007).

For each driver, the curve, as shown in Figure 2,

is made and the optimal performance zone is

estimated.

Figure 2: Relationship between stress and performance in

sports. The optimal performance zone is highlighted.

During the race, the stress levels of the drivers are

shown in real time in 3 different zones: calm or

distracted zone, optimal performance zone and

distressed zone (Figure 3). The stress level of the

driver is projected in these three zones.

Figure 3: Mapping of the stress level in three zones relating

to focus.

2.4 Data Collection

The system was used in collaboration with the

GetSpeed racing team over more than 2 seasons of the

VLN competition (www.vln.de) and 24h races at the

Nürburgring in Germany on the 28km long track.

Fragments of interesting cases are selected and shown

here.

3 INTERESTING CASES

Several interesting cases are presented to here to

show the potential.

icSPORTS 2016 - 4th International Congress on Sport Sciences Research and Technology Support

3.1 Battle with Competitor in Eustress

Zone

Figure 4 shows a signal during a close battle between

the monitored driver and his closest competitor. The

top graph is showing the time difference in seconds

between both cars. The lower graph is showing the

stress levels of the driver, projected in his optimal

performance zone (green). After a pit stop in lap 25,

the car is back on the track about 25 seconds behind

his competitor (driving at the first place). The driver

is than for a longer period driving in his optimal

performance zone gaining back time. While

overtaking his competitor, the driver is going in his

distressed zone, but is going back to his optimal zone

once he has taken some advantage.

Figure 4: Top graph shows the time difference with the

competitor, bottom graph shows the performance indicator.

Figure 5: Crash of driver 1 after being in the distracted zone

for 2.5 minutes.

3.2 Crash While the Driver Is Not

Focused

Figure 5 and Figure

6 show two similar events with

different drivers on different moments in the season.

Figure 6: Crash of driver 2 after being in the distracted zone

for 4 minutes.

On both figures, the driver is for a longer period, (2.5

minutes and 4 minutes respectively), in their distracted or

‘under focused’ zone. In these two cases, the car crashed

because of a driver mistake, leading in both cases to a total

loss of the car.

3.3 Personal Best during a Race

This last example (Figure 7) is showing the graph of

a young driver while he was leading the race with a

difference of more than 2 minutes. He was asked by

his race engineer to drive in a controlled way to avoid

any accidents. The graph starts while the driver is

very low in his performance curve. At a certain

moment, the projected stress level of the driver is

increasing to the top of his optimal performance zone

and even crossing. At the end of the lap, the driver has

driven his fastest lap ever on the circuit, breaking his

previous record with 5 seconds. It is clear that the

driver was pushing the car and himself to the limits,

leading to potential risks as his was in the distressed

zone for quite some time.

Figure 7: Young driver outperforming himself and

achieving his fastest lap on the track.

Stress Level Monitoring in Car Racing - Examples of Measurements during Races

4 DISCUSSION

In this paper, several interesting cases of using a

mental monitor in car racing are presented. These are

cases monitored during a real competition at the VLN

competition and the 24h races at the Nürburgring. in

Germany.

The system is measuring the mental activity of the

race driver using an optical heart rate sensor on the

wrist of the driver and the internal sensors of a

smartphone.

From these activity and heart rate signals, the

mental activity of each driver is calculated in real-

time. From each driver, three different performance

zones, distracted or under focused, optimal perfor-

mance or eustress and distressed, are calculated.

The cases discussed in this text show the potential

of this approach, by revealing interesting information

of the driver. Being in the optimal zone show that the

driver is performing at this best. By going out of this

optimal zone, the driver is not necessarily performing

at his best level. Both cases with the crashes reveal

that in racing, being too relaxed or under focused is

potentially a serious risk leading in these two specific

cases to a severe accident with a total loss of the car.

The next step of this development is proving the

value of this system with more of these cases. The

potential value is to assist the driver to prevent errors,

which can occur when the driver is out of his optimal

performance zone for a long enough period and to

help the driver to improve his overall driving

performance. Being too stressed for a long period can

also cause problems.

The performance of this system is continuously

improved by adding more car information to calculate

the stress and the optimal performance zone.

ACKNOWLEDGEMENTS

The authors would like to thank the drivers and team

crew of the GetSpeed racing team for their full

collaboration during this work.

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icSPORTS 2016 - 4th International Congress on Sport Sciences Research and Technology Support