Electrogastrography in Autonomous Vehicles—An Objective Method for Assessment of Motion Sickness in Simulated Driving Environments
Autonomous vehicles are expected to take complete control of the driving process, enabling the former drivers to act as passengers only. This could lead to increased sickness as they can be engaged in tasks other than driving. Adopting different sickness mitigation techniques gives us unique types o...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-01-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/21/2/550 |
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| author | Timotej Gruden Nenad B. Popović Kristina Stojmenova Grega Jakus Nadica Miljković Sašo Tomažič Jaka Sodnik |
| author_facet | Timotej Gruden Nenad B. Popović Kristina Stojmenova Grega Jakus Nadica Miljković Sašo Tomažič Jaka Sodnik |
| author_sort | Timotej Gruden |
| collection | DOAJ |
| description | Autonomous vehicles are expected to take complete control of the driving process, enabling the former drivers to act as passengers only. This could lead to increased sickness as they can be engaged in tasks other than driving. Adopting different sickness mitigation techniques gives us unique types of motion sickness in autonomous vehicles to be studied. In this paper, we report on a study where we explored the possibilities of assessing motion sickness with electrogastrography (EGG), a non-invasive method used to measure the myoelectric activity of the stomach, and its potential usage in autonomous vehicles (AVs). The study was conducted in a high-fidelity driving simulator with a virtual reality (VR) headset. There separate EGG measurements were performed: before, during and after the driving AV simulation video in VR. During the driving, the participants encountered two driving environments: a straight and less dynamic highway road and a highly dynamic and curvy countryside road. The EGG signal was recorded with a proprietary 3-channel recording device and Ag/AgCl cutaneous electrodes. In addition, participants were asked to signalize whenever they felt uncomfortable and nauseated by pressing a special button. After the drive they completed also the Simulator Sickness Questionnaire (SSQ) and reported on their overall subjective perception of sickness symptoms. The EGG results showed a significant increase of the dominant frequency (DF) and the percentage of the high power spectrum density (FSD) as well as a significant decrease of the power spectrum density Crest factor (CF) during the AV simulation. The vast majority of participants reported nausea during more dynamic conditions, accompanied by an increase in the amplitude and the RMS value of EGG. Reported nausea occurred simultaneously with the increase in EGG amplitude. Based on the results, we conclude that EGG could be used for assessment of motion sickness in autonomous vehicles. DF, CF and FSD can be used as overall sickness indicators, while the relative increase in amplitude of EGG signal and duration of that increase can be used as short-term sickness indicators where the driving environment may affect the driver. |
| first_indexed | 2024-03-09T04:46:14Z |
| format | Article |
| id | doaj.art-b622f4862b2146cca75f749147f1f0cb |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T04:46:14Z |
| publishDate | 2021-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-b622f4862b2146cca75f749147f1f0cb2023-12-03T13:15:37ZengMDPI AGSensors1424-82202021-01-0121255010.3390/s21020550Electrogastrography in Autonomous Vehicles—An Objective Method for Assessment of Motion Sickness in Simulated Driving EnvironmentsTimotej Gruden0Nenad B. Popović1Kristina Stojmenova2Grega Jakus3Nadica Miljković4Sašo Tomažič5Jaka Sodnik6Faculty of Electrical Engineering, University of Ljubljana, Tržaška c. 25, 1000 Ljubljana, SloveniaSchool of Electrical Engineering, University of Belgrade, B. kralja Aleksandra 73, 11000 Belgrade, SerbiaFaculty of Electrical Engineering, University of Ljubljana, Tržaška c. 25, 1000 Ljubljana, SloveniaFaculty of Electrical Engineering, University of Ljubljana, Tržaška c. 25, 1000 Ljubljana, SloveniaSchool of Electrical Engineering, University of Belgrade, B. kralja Aleksandra 73, 11000 Belgrade, SerbiaFaculty of Electrical Engineering, University of Ljubljana, Tržaška c. 25, 1000 Ljubljana, SloveniaFaculty of Electrical Engineering, University of Ljubljana, Tržaška c. 25, 1000 Ljubljana, SloveniaAutonomous vehicles are expected to take complete control of the driving process, enabling the former drivers to act as passengers only. This could lead to increased sickness as they can be engaged in tasks other than driving. Adopting different sickness mitigation techniques gives us unique types of motion sickness in autonomous vehicles to be studied. In this paper, we report on a study where we explored the possibilities of assessing motion sickness with electrogastrography (EGG), a non-invasive method used to measure the myoelectric activity of the stomach, and its potential usage in autonomous vehicles (AVs). The study was conducted in a high-fidelity driving simulator with a virtual reality (VR) headset. There separate EGG measurements were performed: before, during and after the driving AV simulation video in VR. During the driving, the participants encountered two driving environments: a straight and less dynamic highway road and a highly dynamic and curvy countryside road. The EGG signal was recorded with a proprietary 3-channel recording device and Ag/AgCl cutaneous electrodes. In addition, participants were asked to signalize whenever they felt uncomfortable and nauseated by pressing a special button. After the drive they completed also the Simulator Sickness Questionnaire (SSQ) and reported on their overall subjective perception of sickness symptoms. The EGG results showed a significant increase of the dominant frequency (DF) and the percentage of the high power spectrum density (FSD) as well as a significant decrease of the power spectrum density Crest factor (CF) during the AV simulation. The vast majority of participants reported nausea during more dynamic conditions, accompanied by an increase in the amplitude and the RMS value of EGG. Reported nausea occurred simultaneously with the increase in EGG amplitude. Based on the results, we conclude that EGG could be used for assessment of motion sickness in autonomous vehicles. DF, CF and FSD can be used as overall sickness indicators, while the relative increase in amplitude of EGG signal and duration of that increase can be used as short-term sickness indicators where the driving environment may affect the driver.https://www.mdpi.com/1424-8220/21/2/550electrogastrographyautonomous vehiclemotion sicknessdriving simulatorvirtual reality |
| spellingShingle | Timotej Gruden Nenad B. Popović Kristina Stojmenova Grega Jakus Nadica Miljković Sašo Tomažič Jaka Sodnik Electrogastrography in Autonomous Vehicles—An Objective Method for Assessment of Motion Sickness in Simulated Driving Environments Sensors electrogastrography autonomous vehicle motion sickness driving simulator virtual reality |
| title | Electrogastrography in Autonomous Vehicles—An Objective Method for Assessment of Motion Sickness in Simulated Driving Environments |
| title_full | Electrogastrography in Autonomous Vehicles—An Objective Method for Assessment of Motion Sickness in Simulated Driving Environments |
| title_fullStr | Electrogastrography in Autonomous Vehicles—An Objective Method for Assessment of Motion Sickness in Simulated Driving Environments |
| title_full_unstemmed | Electrogastrography in Autonomous Vehicles—An Objective Method for Assessment of Motion Sickness in Simulated Driving Environments |
| title_short | Electrogastrography in Autonomous Vehicles—An Objective Method for Assessment of Motion Sickness in Simulated Driving Environments |
| title_sort | electrogastrography in autonomous vehicles an objective method for assessment of motion sickness in simulated driving environments |
| topic | electrogastrography autonomous vehicle motion sickness driving simulator virtual reality |
| url | https://www.mdpi.com/1424-8220/21/2/550 |
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