SUGISAKAMASANORI

Journal of Robotics, Networking and Artificial Life
Vol. 10(3); December (2023), pp. 242–246
ISSN (Online): 2352-6386; ISSN (Print): 2405-9021
https://alife-robotics.org/jrnal.html

Research Article

An Empirical Research Using Data Science Analysis of Kinetosis
Satoshi Ikeda1, Tsutomu Ito2, Seigo Matsuno2, Makoto Sakamoto1, Takao Ito3

Faculty of Engineering, University of Miyazaki, 1-1 Gakuen Kibanadai-Nishi, Miyazaki, 889-2192, Japan
Department of Business and Administration, Ube National College of Technology, 2-14-1 Tokiwadai, Ube, Yamaguchi, 755-0096, JapanGraduate School of advanced Science and Engineering, Hiroshima University, 1-4-1 Kagamiyama, Higashi-Hiroshima, 739-8527, Japan

123ARTICLE INFO
Article History
Received 06 December 2022
Accepted 01 May 2024
Keywords
Data-science analytics
Kinetosis
Car sickness
QoL
Statistical analysis

ABSTRACTCar sickness often causes dizziness and discomfort that lasts for several days, accompanied byvomiting and headaches. Countermeasures and symptoms have been studied from various
perspectives, but there are no comprehensive and unique countermeasures. In this study, data on
motion sickness were taken from a random sample of drivers and passengers in a car. This study
proposed a new measure to prevent motion sickness that does not depend on the performance ofthe car, and clarified that the rapid rotational movement of the head that occurs in the car is
considered to be one of the causes of kinetosis.
© 2022 The Author. Published by Sugisaka Masanori at ALife Robotics Corporation Ltd.
This is an open access article distributed under the CC BY-NC 4.0 license(http://creativecommons.org/licenses/by-nc/4.0/).

•1. Introduction
Vehicles have contributed to humanity as a means ofpublic transportation such as private cars, buses, andtrucks. Car sickness occurs when using a vehicle. It
manifests itself as dizziness and discomfort while
traveling in a moving vehicle, and some people may
experience nausea and headaches that last for several
days. Countermeasures and onset mechanisms have beenstudied from various perspectives, but no effective
countermeasure has yet been established. This researchdeveloped a new method by using data science analysis
to derive indicators related to motion sickness in people
traveling by vehicle. The main purpose of this research isto propose a new method to prevent motion sickness thatis not caused by vehicle performance.

••••

2. Related research•With regard to Kinetosis, a plethora of studies have been
conducted to identify remedies and preventive measures
to combat motion sickness. According to a study bySchmidt et al. [1], Kinetosis is a symptom experienced
by approximately 2 out of 3 persons, and has thefollowing characteristics.
Corresponding author E-mail: bisu@cs.miyazaki-u.ac.jp•242

Those who are completely deaf do notexperience car sickness. Interestingly, patientswith Meniere’s disease, also referred to as innerear disorders, can also develop visual motion
while not physically moving.
Blind people get Kinetosis, and sighted people
get Kinetosis even with their eyes closed.
Reading a book or looking at a PC screen in amoving car is likely to cause car sickness.
Kinetosis is reduced when looking at an open
car window, such looking at the road ahead. Carsickness is more likely when sitting backwards
in a car.
Kinetosis is more likely to occur in the back seatof a car and less likely to be experienced by adriver. (Specifically, by 46.3% in the rear seat,
36.7% in the front seat, and 17.2% in the driver.)54.5% of people who are afflicted by Kinetosis
develop it even if they are looking outside theauto.
More than 70% of passengers develop
symptoms of Kinetosis within 25 minutes after
alighting the car.

•experiment would be considered sufficient. The
instructor drives the test vehicle, and the subject sits inthe back seat. The randomly selected subjects comprisedof 25 male and female students aged 17 to 23 at NITUBE.

62.1% of people experience Kinetosis asseasickness when traveling by ships.

To identify the conditions under which Kinetosis
occurs, research on the onset mechanism [2] and research
on a judgment method based on eye movement [3] havebeen investigated. What’s more, in recent years, studies[4] focusing on identifying countermeasures for "visualsickness" accompanying the development of VR
technology have been promoted, but no clear
countermeasures against auto sickness have beenproposed. In considering Kinetosis, research [5] on thedriving state of a vehicle has been conducted, but it isconsidered necessary to pay attention to the movement of
the passenger that is afflicted by car sickness.
Accordingly, in this study, we focus on riding postureand vehicle movement, and verify the characteristics ofcar sickness based on the difference between passenger's
motion and motion of the vehicle.

Table 1. Specification of Accelerometer
M anufacturer

Witmotion

M odel

BET901CL-E

Communication method

Bluetooth

Baud rate115200

Outp ut frequency

0.1～200Hz

Acceleration range±16g

Angular velocity range±2000°/s

3. Objective of this research
The main purpose of this research is to propose riding
positions and driving routes that will prevent car sickness.
An experiment was conducted to collect time-series dataon the movement of the heads of cars and passengers
under acceleration conditions. The proposed method uses
these data to find common characteristics of people who
experience movement syndrome. There are various
factors that cause motion sickness, such as the smell andsight of a car, but this research focused on motion
sickness caused by moving vehicles and developed a newmethod.
Fig. 1 Experiment Route around NIT-Ube
Depicted on Google Earth

4. Proposed method
4.1. Experiment
An acceleration sensor (Witmotion BET901CL-E) wasattached to the cranium of each passenger to collect dataon the movement of the head while the car is in motion.
The sensor specifications are shown in Table 1.
In a similar vein, the same sensor was fixed on thefloor of the vehicle. In addition, a GPS data logger(Digspaiceⅲ) was attached to the vehicle to record theoperation information of the vehicle. For the operationroute of the experiment, we used an open road near NITUbe.
Fig. 1 shows an example of an operating route. Since
this research aims to prevent car sickness independent on
the performance of the vehicle, the official car of NITUbe was used, although a general car used for theFig. 2 Time Series Results for Lateral Acceleration
on Passenger and Vehicle

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Table 2. List of Average Values of Acceleration and Rotational Speed Generated at the Passenger's Head Obtained
2222No.

Ride Time (m)Sy mp tomax(m/s )ay (m/s )az(m/s )a(x,y ,z)(m/s )wx(deg/s)wy (deg/s)wz(deg/s)

No.3

24.6

-

-0.095-0.189

0.054

0.003

-4.503-4.561-3.096No.6

30.0--0.006

0.160-0.042-0.003

7.731

8.093

7.788

No.11

28.0

M ild

0.070

0.152

-0.056-0.00210.755

7.623

9.585

No.19

25.7

-

0.007

0.215

-0.049-0.003

4.150

4.032

4.851

No.20

28.7

-

-0.0390.197-0.031-0.002

4.167

3.960

3.720

No.21

27.1

-

0.134

0.649

-0.412-0.006

5.492

4.205

3.854

No.22

29.2

-0.0310.184-0.064

0.001

5.151

4.936

6.254

No.23

28.1

Severe

0.133

0.157

-0.056-0.001

8.476

8.337

15.637

No.24

27.4

-0.0620.320-0.110-0.002

6.410

6.059

5.215

M ean

27.6

-0.0330.205-0.085-0.002

5.314

4.743

5.979

4.2. Experimental result

into 6-level numerical values by adding 0 to completely
asymptomatic. The results shown in Table 4 based onclassification reveal a high correlation coefficient of
0.934 for the difference in rotational speed around the Zaxis. This means that the occupant rotates his/her head in
the horizontal direction quickly with respect to the yaw
generated in the vehicle.

Fig. 2 shows the time-series data of acceleration of thevehicle and the passenger's head movement obtained by
the experiment. As shown in Fig. 2, it is evident that thepassenger’s head and the vehicle floor recorded different
movement patterns. Only two cases, No. 11 (19-year-oldfemale) who developed mild dizziness, and No. 23 (23year-old male) developed car sickness during the test.

Table 3. The Difference of the Average RotationalSpeed of the Passenger's Head and Symptoms

5. Analysis and discussion

No.

Table 2 shows the acceleration and rotation speed in
the XYZ direction obtained from the ride experiment.
Table 2 summarizes the data for ride durations of 20 to
30 minutes. It is difficult to ascertain the occurrence ofcar sickness from the movement of the vehicle and thepassenger's head. According to the study by Okuyama etal. [3], considering that motion sickness-like symptoms
occur even with visual information that does not involve
movement, the difference of motion of the car andpassenger’s movement should be taken intoconsideration. Here, let the motion of the vehicle be (V),and the motion of the passenger's head be (H). To
calculate the index (I), the difference between themovement predicted by the passengers from visual
information and the actual movement can be calculated
as follows:

No.3

-

-0.81

-0.18

-2.88

No.6

-

2.42

3.35

1.81

No.11

Mild

5.44

2.88

3.61

No.19

-

-1.16

-0.71

-1.13

No.20

--1.15

-0.78

-2.26

No.21

-

0.18

-0.54

-2.12

No.22

-

-0.16

0.19

0.28

No.23

Severe

3.16

3.59

9.66

No.24

-

1.10

1.32

-0.76

(𝐼𝐼) = (𝐻𝐻) − (𝑉𝑉)Symptom wx(deg/s) wy(deg/s) wz(deg/s)

Table 4. Correlation between the differences fromthe average value of the evaluation index related torotation speed and symptoms
Symptom(1)

Table 3 shows the difference from the average valueof index (I) for each direction of rotation. From Table 3,
it is conceivable that in the experiments that caused
motion sickness, the rotational speed of the passenger's
head tended to be faster in one direction than the average.
Next, the quantification of motion sickness symptoms isperformed to compute the inter-correlations among thefocal constructs. For quantification, the 5-levelevaluation items established by NASA were classified

wx(deg/s)wy(deg/s)

Symptom

1.000

wx(deg/s)

0.633

1.000

wy(deg/s)

0.667

0.887

1.000wz(deg/s)

0.934

0.744

0.838

wz(deg/s)

1.000

Seemingly, these findings are congruent with the results
reported in other studies that motion sickness is causedby the discrepancy between sensory motion and actualmotion.
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6. Conclusion
Authors Introduction

In order to clarify the riding posture that does not cause
kinetosis, we conducted an experiment to identify themovements while riding that are common to people whosuffer from this condition. The results revealed that therapid rotational movement of the head that occurs inside
a vehicle is one of the factors that causes kinetosis. On
the other hand, in order to identify the characteristics ofmovements that cause kinetosis from a data science
perspective, we need experimental data on subjects whoexperience car sickness. Therefore, in the future,additional data will need to be collected fromexperiments. Analysis of the motion factors that cause
car sickness requires frequency estimation using FFT,
which has been found to be useful in increasing
knowledge of kinetosis.

Dr. Satoshi Ikeda
He received PhD degree from Hiroshima
University. He is an associate professor
in the Faculty of Engineering, Universityof Miyazaki. His research interest
includes graph theory, probabilistic
algorithm, fractal geometry and measure
theory.
Dr. Tsutomu Ito
He is an Associate Professor of theDepartment of Business Administration
at National Institute of Technology, Ube
College, Japan. His current researchinterests include internet of things (IoT),
mechanicalengineering,artificial
intelligence (AI), automata theory,quantitative analysis of Japanese
Keiretsu. Dr. Ito earned his doctor degree of Engineeringfrom Hiroshima University, Japan in 2018

References
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Kaname Hirayanagi, A present state and perspective ofstudies on motion sickness, Ergonomics, Vol. 42, No.3,
200-211, 15 June 2006.
Shohta Okuyama, Jun Toyotani, Nae Urata, and Yuto
Omae, Automatic Recognition Model of Motion
Sickness and Hierarchical Classification by Random
Forest of Line of Sight, Japan Society of Directories,
Journal of Japan Information Directory Society Vol. 19,
No.1, 2-9, 31 march 2021.
Hiroyasu Ujike, Developing an evaluation system ofvisually induced motion sickness for safe usage ofmoving images, Synthesiology, English edition, Vol.5,No.3, 139-149, December 2021.
Kouhei Matsumoto, Norihiro Fujii and Kousuke Ohnishi,
Method of motion Sickness Evaluation for Vehicle taking
account of Running Condition, The Japan Society ofMechanical Engineers, Proceedings of the Japan Societyof Mechanical Engineers Kansai Branch Annual General
Meeting Vol. 80, 14.1-14.2, 18 March 2005.

Dr. Seigo Matsuno
He is Professor of the Department ofBusiness Administration at National
Institute of Technology, Ube College,
Japan. He received his Ph.D. degree in
Economics from Kyushu University,
Japan in 2004. His current researchinterests are in the areas of IT management
and strategy, information systems outsourcing, and interfirm
relationship management.
Dr. Makoto Sakamoto
He received the Ph.D. degree incomputerscienceandsystems
engineering
fromYamaguchi
University. He is presently Professor in
the Faculty of Engineering, Universityof Miyazaki. He is a theoreticalcomputer scientist, and his current main
research interests are automata theory,languages, and computation. He is also interested in digital
geometry, digital image processing, computer vision,
computer graphics, virtual reality, augmented reality,
entertainment computing, complex systems and so on.

245

Dr. Takao Ito

He is Professor of Management ofTechnology (MOT) in Graduate Schoolof Engineering at Hiroshima University.
His current research interests include
automata theory, artificial intelligence,and systems control, quantitative analysis
of interfirm relationships using graphtheory, and engineering approach of organizational structuresusing complex systems theory.

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