Changes in Electroencephalography Activity of Sensory Areas Linked to Car Sickness in Real Driving Conditions

Abstract

Car sickness is a major concern for car passengers, and with the development of autonomous vehicles, increasing numbers of car occupants are likely to be affected. Previous laboratory studies have used EEG measurements to better understand the cerebral changes linked to symptoms. However, the dynamics of motion in labs/simulators differ from those of a real car. This study sought to identify specific cerebral changes associated with the level of car sickness experienced in real driving conditions. Nine healthy volunteers participated as front passengers in a slalom session inducing lateral movements at very low frequency (0.2 Hz). They were continuously monitored via EEG recordings and subjectively rated their level of symptoms after each slalom, using a 5-point likert scale. Car-sickness symptoms evolved concomitantly with changes in theta and alpha power in the occipital and parietal areas. These changes may reflect altered sensory integration, as well as a possible influence of sleepiness mitigating symptoms.

Keywords: EEG activity; car passenger; car sickness; real driving; sensory integration.

FIGURE 1

Representation of (A) test set-up and timeline of the test session with each period: two baseline periods (parked and straight road), slaloms and recovery period; (B) the six time intervals per session analyzed for EEG signal recordings: baseline parked (BasP), baseline straight road (BasS), slaloms (comprising RT_start, RT₊₊, RT_stop) and recovery (Recov); see section “Data Acquisition and Processing”.

FIGURE 2

Illustration of (A) electrode positioning based on a modified International 10–20 Electrode Placement System; (B) EEG headset (14 dry and active Conscious Labs electrodes (https://conscious-labs.com)) with the OpenBCI (http://openbci.com) acquisition card (right).

FIGURE 3

(A) LFP Z-scored trace for frontal, central, parietal and occipital electrodes; (B) Spectrogram of O2 electrode signal during the entire baseline parked (300 s). Note the emergence of alpha burst (8–12 Hz range) during the 1 min with eyes closed (from minute 2 to 3); (C) Time-resolved power spectral density (PSD, using complex Morlet wavelet transform); (D) resulting PSD.

FIGURE 4

Distribution of maximum ratings reached by participants: white (0–1); light gray (1–2); dark gray (2–3) and black (>3).

FIGURE 5

Car-sickness subjective ratings observed for each test period (BasP, RT_start, RT₊₊, RT_stop and Recov) (mean ± SEM; n = 9; *p < 0.05 and **p < 0.01 at risk α = 0.05).

FIGURE 6

Power observed in alpha (A–C) and theta bands (B–D) for parietal (A,B) and occipital areas (C,D) for each test period (BasP, RT_start, RT₊₊, RT_stop and Recov) (mean ± SEM; n = 9; *p < 0.05, **p < 0.01, and ***p < 0.001 at risk α = 0.05).