Biometric sensor fusion to classify vehicle passenger state

US10867218B2 · kind B2 · utility

Assignee

• Lear Corporation · US

Inventors

• David Gallagher · Sterling Heights, US
• Francesco Migneco · Saline, US
• Arjun Yetukuri · Rochester Hills, US
• Jasmine Pizana · Scottville, US
• Steven T. Stavropoulos · Novi, US
• Pat Carlsen · Grosse Pointe, US
• Abhay Prakash · Mumbai, IN

Key dates

• Filing date: Apr 26, 2018
• Grant date: Dec 15, 2020
• Expiry date: Nov 30, 2038

Classification

• Technology area (CPC G): Physics
• CPC primary: G06V20/593
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

A neural network is used in a vehicle component to determine the stress level or arousal level of a vehicle occupant. Sensors in the vehicle cabin, e.g., the seat, sense biological characteristics of the occupant, e.g., neuro-electrical signals, cardiac characteristics, body temperature and the like. The neural network can compute and classify the emotional state of the occupant in real-time. The vehicle can trigger warnings, indicators and stress counter-measures when the occupant exceeds a threshold. The counter-measures can include visual and audio feedback within the vehicle cabin. The neural network can provide historical occupant emotional states that can be used by the navigation system to avoid travel segments that may trigger undesired emotional states in the occupant.