A Wearable Brain-Computer Interface for Mitigating Car Sickness via Attention Shifting.

Area of Science:

• Neuroscience
• Biomedical Engineering
• Human-Computer Interaction

Background:

• Car sickness is a common problem with limited effective treatments.
• Current pharmacological options for car sickness have side effects.
• Non-pharmacological alternatives for motion sickness are needed.

Purpose of the Study:

• To introduce and evaluate a novel wearable mindfulness brain-computer interface (BCI) for alleviating car sickness.
• To assess the efficacy of an AI-driven attention-shifting method using electroencephalography (EEG).
• To explore the neurobiological underpinnings of car sickness and BCI intervention.

Main Methods:

• Development of a closed-loop, AI-driven wearable BCI using a mindfulness attentional task.
• Real-time analysis of EEG data via a convolutional neural network to monitor mindfulness state.
• Real-world testing with over 100 participants susceptible to car sickness during short and long car rides.

Main Results:

• Over 83% of participants found the BCI-based attention shifting effective in reducing car sickness.
• Significant reductions in car sickness severity were observed, especially in severely affected individuals.
• EEG analysis identified a neurobiological signature of car sickness, offering mechanistic insights.

Conclusions:

• The proposed wearable, non-pharmacological BCI intervention shows significant potential for alleviating car sickness.
• The study provides a large-scale, real-world validation of BCI technology for motion sickness.
• This approach offers a promising new avenue for improving travel experiences for those suffering from car sickness.