ArticleSensors (Basel, Switzerland)2021
Electrogastrography in Autonomous Vehicles-An Objective Method for Assessment of Motion Sickness in Simulated Driving Environments.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 40 citations in OpenAlex.
- A Study on Autonomous Driving Motion Sickness from the Perspective of Multimodal Human Signals.Sensors (Basel, Switzerland) · 2026Article
- Sensory conflict in simulator sessions - measuring biosignals to predict the onset of disorderly symptoms: a brief literature review.International journal of occupational medicine and environmental health · 2024Review
- Quantitative study on objective indicators for assessing motion sickness susceptibility based on Vestibulo-Ocular Reflex experiments.Scientific reports · 2024Article
- Data augmentation for generating synthetic electrogastrogram time series.Medical & biological engineering & computing · 2024Article
- Classification of Visually Induced Motion Sickness Based on Phase-Locked Value Functional Connectivity Matrix and CNN-LSTM.Sensors (Basel, Switzerland) · 2024Article
- Article
- Electrogastrogram-Derived Features for Automated Sickness Detection in Driving Simulator.Sensors (Basel, Switzerland) · 2022Article
- Relating individual motion sickness levels to subjective discomfort ratings.Experimental brain research · 2022Article
- Multi-Dimensional and Objective Assessment of Motion Sickness Susceptibility Based on Machine Learning.Frontiers in neurology · 2022Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
Abstract
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.
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Registered trials
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