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Amplitude and Temporal Dynamics of Motion Sickness
The relationship between the amplitude of motion and the accumulation of motion sickness in time is unclear. Here, we investigated this relationship at the individual and group level. Seventeen participants were exposed to four oscillatory motion stimuli, in four separate sessions, separated by at l...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9126086/ https://www.ncbi.nlm.nih.gov/pubmed/35615427 http://dx.doi.org/10.3389/fnsys.2022.866503 |
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author | Irmak, Tugrul Kotian, Varun Happee, Riender de Winkel, Ksander N. Pool, Daan M. |
author_facet | Irmak, Tugrul Kotian, Varun Happee, Riender de Winkel, Ksander N. Pool, Daan M. |
author_sort | Irmak, Tugrul |
collection | PubMed |
description | The relationship between the amplitude of motion and the accumulation of motion sickness in time is unclear. Here, we investigated this relationship at the individual and group level. Seventeen participants were exposed to four oscillatory motion stimuli, in four separate sessions, separated by at least 1 week to prevent habituation. Motion amplitude was varied between sessions at either 1, 1.5, 2, or 2.5 ms(−2). Time evolution was evaluated within sessions applying: an initial motion phase for up to 60 min, a 10-min rest, a second motion phase up to 30 min to quantify hypersensitivity and lastly, a 5-min rest. At both the individual and the group level, motion sickness severity (MISC) increased linearly with respect to acceleration amplitude. To analyze the evolution of sickness over time, we evaluated three variations of the Oman model of nausea. We found that the slow (502 s) and fast (66.2 s) time constants of motion sickness were independent of motion amplitude, but varied considerably between individuals (slow STD = 838 s; fast STD = 79.4 s). We also found that the Oman model with output scaling following a power law with an exponent of 0.4 described our data much better as compared to the exponent of 2 proposed by Oman. Lastly, we showed that the sickness forecasting accuracy of the Oman model depended significantly on whether the participants had divergent or convergent sickness dynamics. These findings have methodological implications for pre-experiment participant screening, as well as online tuning of automated vehicle algorithms based on sickness susceptibility. |
format | Online Article Text |
id | pubmed-9126086 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91260862022-05-24 Amplitude and Temporal Dynamics of Motion Sickness Irmak, Tugrul Kotian, Varun Happee, Riender de Winkel, Ksander N. Pool, Daan M. Front Syst Neurosci Neuroscience The relationship between the amplitude of motion and the accumulation of motion sickness in time is unclear. Here, we investigated this relationship at the individual and group level. Seventeen participants were exposed to four oscillatory motion stimuli, in four separate sessions, separated by at least 1 week to prevent habituation. Motion amplitude was varied between sessions at either 1, 1.5, 2, or 2.5 ms(−2). Time evolution was evaluated within sessions applying: an initial motion phase for up to 60 min, a 10-min rest, a second motion phase up to 30 min to quantify hypersensitivity and lastly, a 5-min rest. At both the individual and the group level, motion sickness severity (MISC) increased linearly with respect to acceleration amplitude. To analyze the evolution of sickness over time, we evaluated three variations of the Oman model of nausea. We found that the slow (502 s) and fast (66.2 s) time constants of motion sickness were independent of motion amplitude, but varied considerably between individuals (slow STD = 838 s; fast STD = 79.4 s). We also found that the Oman model with output scaling following a power law with an exponent of 0.4 described our data much better as compared to the exponent of 2 proposed by Oman. Lastly, we showed that the sickness forecasting accuracy of the Oman model depended significantly on whether the participants had divergent or convergent sickness dynamics. These findings have methodological implications for pre-experiment participant screening, as well as online tuning of automated vehicle algorithms based on sickness susceptibility. Frontiers Media S.A. 2022-05-09 /pmc/articles/PMC9126086/ /pubmed/35615427 http://dx.doi.org/10.3389/fnsys.2022.866503 Text en Copyright © 2022 Irmak, Kotian, Happee, de Winkel and Pool. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Irmak, Tugrul Kotian, Varun Happee, Riender de Winkel, Ksander N. Pool, Daan M. Amplitude and Temporal Dynamics of Motion Sickness |
title | Amplitude and Temporal Dynamics of Motion Sickness |
title_full | Amplitude and Temporal Dynamics of Motion Sickness |
title_fullStr | Amplitude and Temporal Dynamics of Motion Sickness |
title_full_unstemmed | Amplitude and Temporal Dynamics of Motion Sickness |
title_short | Amplitude and Temporal Dynamics of Motion Sickness |
title_sort | amplitude and temporal dynamics of motion sickness |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9126086/ https://www.ncbi.nlm.nih.gov/pubmed/35615427 http://dx.doi.org/10.3389/fnsys.2022.866503 |
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