Motion Sickness Prevention

Use AI and sensors to prevent motion sickness and enhance passenger comfort during travel

Business impact

• Customer Satisfaction — Reduces discomfort leading to higher passenger approval and loyalty
• Product Differentiation — Innovative features distinguish vehicles and devices in competitive markets
• User Engagement — Enables longer and more comfortable use of in-vehicle or device features
• Adoption Rate — Improved comfort encourages acceptance of autonomous and electric vehicles
• Safety Metrics — Mitigating motion sickness reduces distraction and enhances passenger safety
• Product Usage — Reduced nausea increases time spent using vehicle infotainment and apps

Data requirements

• Vehicle motion sensors (Numeric) — Capture real-time acceleration and movement data to detect motion patterns
• Biometric wearables (Numeric) — Monitor passenger physiological signals indicating discomfort or nausea
• Visual input data (Image) — Analyze visual cues and display alignment to reduce sensory conflict
• User feedback and questionnaires (Text) — Collect subjective reports on motion sickness symptoms and relief
• EEG brainwave signals (Numeric) — Measure neural activity to predict and assess motion sickness states

AI methods and techniques

• Predictive AI — Forecast motion sickness onset from sensor and biometric data for proactive intervention
• Agentic AI — Autonomously adjust vehicle controls and environmental factors to mitigate symptoms
• Generative AI — Create adaptive visual or audio cues to align sensory inputs and reduce nausea

AI models and model families

GPT-4, Claude, Llama 2, Custom BPNN models for EEG analysis

Industries

Real-world evidence

5 documented case studies on record.

Companies using this: Apple, Citro, Kia, Tesla, Volvo AB.