Amplitude and Temporal Dynamics of Motion Sickness

Abstract

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.

Optimal Trajectory Planning for Mitigated Motion Sickness: Simulator Study Assessment

“…This implies that MSSQ is not a reliable metric to predict the susceptibility of an individual to motion sickness in the conditions tested. This is coherent with [36] reporting a moderate correlation with MSSQ (ρ = 0.5, p = 0.05) in 0.3 Hz fore-aft motion.…”

The role of vision in sensory integration models for predicting motion perception and sickness

“…For longitudinal (fore-aft) motion, Irmak et al ( 2020 ) have used motion perturbations at a peak acceleration of 2 ms − 2 and frequencies of 0.15, 0.2, 0.3, 0.4, and 0.5 Hz to measure motion sickness measured in terms of the MIsery SCale (MISC). Also, Irmak et al ( 2022 ) have conducted experiments at a fixed frequency of 0.3 Hz and varying amplitudes of 1.0, 1.5, 2.0 and 2.5 ms − 2 to collect MISC ratings. Furthermore, Golding and Markey ( 1996 ) and Golding et al ( 1997 ) have perturbed subjects with lateral motion with a peak acceleration of 3.6 ms − 2 and frequencies of 0.2, 0.35, 0.5, 0.7 and 1.0 Hz.…”

“…In motion sickness models, the ‘ sensory conflicts ’ that are assumed to cause sickness (Reason 1978 ) are generally defined as the difference between the sensed and expected sensory signals. Hence, these models are often referred to as ‘ sensory conflict models ’, due to their ability to quantitatively predict the conflicts that, when accumulated over time, lead to the worsening of motion sickness symptoms (Oman 1990 ; Bos and Bles 1998 ; Kufver and F¨orstberg 1999 ; Irmak et al 2020 , 2022 ). For example, Bos and Bles ( 1998 ) conceptualized the Subjective Vertical Conflict (SVC) model, which is based on the assumption that motion sickness is caused by conflict in the sensed vertical (i.e., orientation with respect to gravity).…”

“…In this paper, we focus on comparing only the most recent versions of the motion sickness and motion perception models that include visual rotational velocity and visual orientation perception, namely the Subjective Vertical Conflict (SVC) model (Wada et al 2020 ; Liu et al 2022 ; Inoue et al 2022 ), and the Multi-Sensory Observer Model (MSOM) (Newman 2009 ; Clark et al 2019 ), as the most promising candidates. Similar to Irmak et al ( 2023 ), we present a two-part analysis, where we first focus on these models’ match to well-known frequency and amplitude sensitivity characteristics of motion sickness (McCauley et al 1976 ; Golding and Markey 1996 ; Irmak et al 2021 , 2022 ; Griffin and Mills 2002b ; Howarth and Griffin 2003 ). Furthermore, the extent to which the models can replicate the effect of vision conditions in the real-world sickening drive study of Irmak et al ( 2020 ) is analyzed.…”

Validating models of sensory conflict and perception for motion sickness prediction

“…Moreover, there may be individual differences in the temporal dynamics of sickness (Irmak et al. 2022 ). Lastly, motions below a certain amplitude may often fail to elicit any sickness (Lawther and Griffin 1988 ).…”