Heart rate variability as a physiological marker of motion sickness in real-world driving conditions

This study investigated the utility of heart rate variability (HRV) metrics derived from electrocardiogram (ECG) signals for assessing motion sickness (MS) during real-world driving. While motion sickness is commonly evaluated through subjective reports or multimodal physiological measurements, previous studies have predominantly relied on simulator-based experiments or multimodal physiological sensing, which limit ecological validity and practical deployment in everyday vehicles. In this study, twenty-four female participants were exposed to systematically varied acceleration and deceleration profiles across 13 predefined driving conditions in an electric vehicle. Motion sickness symptoms were measured using the Misery Scale (MISC), and ECG data were segmented into 120-s epochs to extract heart rate, the low-frequency to high-frequency (LF/HF) ratio, and pNN50 (the percentage of successive normal-to-normal intervals differing by more than 50 ms). Using a threshold corresponding to symptom onset (MISC of 2 or above), pNN50 was significantly lower in the high-MS group than in the low-MS group (16.5% versus 24.6%, p < 0.001, Cohen's d = -0.53), indicating reduced parasympathetic (vagal) modulation in the presence of motion sickness symptoms. Heart rate did not differ significantly between groups, and the LF/HF ratio showed a statistically significant but negligible difference. Mean pNN50 values did not, however, decline monotonically across individual MISC scores, indicating that the metric distinguishes the presence of symptoms rather than grading their severity. These findings suggest that pNN50 is the most sensitive of the examined HRV indices and may reflect individual differences in susceptibility to motion sickness. The study demonstrates that motion sickness can be assessed using a single, widely accessible physiological signal such as ECG, providing a foundation for future wearable and in-vehicle motion sickness monitoring systems.