Motion Sickness Detection Using Physiological and Vehicle Data
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Solution Overview
Problem
Autonomous vehicles face challenges in detecting motion sickness in passengers, which can lead to nausea, discomfort, and cognitive and emotional disturbances, especially when passengers engage in activities like reading or texting, due to the conflict between vestibular, proprioceptive, and visual senses, affecting safety and comfort.
Innovation Solution
A system that combines physiological data (heart rate, skin conductance, temperature) with vehicle motion data (accelerometers, gyroscopes) and eye gaze data to classify the degree of motion sickness, allowing for early detection and activation of remedial actions such as adjusting driving dynamics or the sensory environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If passengers engage in activities like reading or texting in autonomous vehicles, then passenger comfort and relaxation are improved, but motion sickness susceptibility increases due to sensory conflict
Solution Approach 1:
The system performs preliminary detection of motion sickness symptoms by continuously monitoring physiological parameters (heart rate, skin conductance, temperature) and vehicle motion data before full-blown motion sickness occurs. This early detection enables preventive actions to be taken, such as adjusting vehicle motion or notifying the passenger, thereby resolving the contradiction by allowing passengers to remain relaxed while preventing motion sickness onset.
2Measurement precision
If the system monitors multiple physiological parameters and vehicle motion data continuously, then motion sickness detection accuracy is improved, but system complexity increases
Solution Approach 1:
The system merges multiple data sources including physiological parameters (heart rate, skin conductance, temperature), vehicle motion data (accelerometers, gyroscopes), and environmental sensors into a unified detection framework. By combining these diverse data streams and analyzing them collectively through a single processing system, the patent achieves high detection accuracy while avoiding the complexity of multiple separate monitoring systems.
3Reliability
If the system detects motion sickness early and activates remedial actions, then passenger safety and comfort are improved, but system response time requirements increase
Solution Approach 1:
The system is designed to detect motion sickness symptoms in their early stages by continuously monitoring physiological parameters and comparing them against baseline values. By identifying subtle changes in heart rate, skin conductance, and temperature before full-blown motion sickness occurs, the system enables early intervention with remedial actions such as adjusting vehicle motion or notifying the passenger, thereby ensuring safety while maintaining appropriate response times.
Data Source
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AI summary
Techniques described herein include detecting a degree of motion sickness experienced by a user within a vehicle. A suitable combination of physiological data (heart rate, heart rate variability parameters, blood volume pulse, oxygen values, respiration values, galvanic skin response, skin conductance values, and the like), eye gaze data (e.g., images of the user), vehicle motion data (e.g., accelerometer, gyroscope data indicative of vehicle oscillations) may be utilized to identify the degree of motion sickness experienced by the user. One or more autonomous actions may be performed to prevent an escalation in the degree of motion sickness experienced by the user or to ameliorate the degree of motion sickness currently experienced by the user.