Emotion Mapping Apparatus Using Multi-Sensor Segmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current vehicle technologies lack the ability to effectively determine and respond to a driver's emotional state in real-time, impacting driving comfort and safety.
Innovation Solution
An emotion mapping apparatus and method that uses sensors such as GSR, HR, EEG, face analyzers, and eye trackers to classify a driver's emotion state along positive and excitability axes, generating an emotion map and providing feedback to enhance the driving experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors (GSR, HR, EEG, face analyzer, eye tracker) are used to detect driver emotion, then measurement precision and reliability improve, but device complexity increases
Solution Approach 1:
The emotion detection system is segmented into multiple independent sensor modules, each responsible for detecting specific physiological or behavioral parameters (GSR for skin conductance, HR for heart rate, EEG for brain activity, face analyzer for facial expressions, eye tracker for eye movements). This segmentation allows each sensor to specialize in detecting particular emotion indicators, improving overall measurement precision while maintaining manageable system complexity through modular architecture
Solution Approach 2:
The controller integrates multiple sensor inputs and performs multiple functions: acquiring raw sensor data, filtering noise, determining emotion states through pattern recognition, generating emotion maps, and controlling various vehicle systems (climate control, entertainment, alerts). This multi-functional integration reduces the need for separate systems and resolves the contradiction by making the complex sensor array work cohesively as a unified emotion detection and response system
2Reliability
If real-time emotion detection and feedback systems are implemented, then driver comfort and safety improve, but energy consumption increases
Solution Approach 1:
The system processes and analyzes sensor data autonomously using onboard controllers and algorithms, determining driver emotion states and generating appropriate feedback without requiring constant external server communication or high-power processing. The controller self-manages the entire workflow from raw sensor acquisition to emotion map generation and vehicle system control, minimizing energy-consuming external dependencies while maintaining real-time safety monitoring
Solution Approach 2:
The emotion detection and feedback system operates periodically rather than continuously at maximum intensity, with the controller acquiring sensor data at optimized intervals, processing information through emotion determination algorithms, and providing feedback only when emotion changes are detected or at scheduled update cycles. This periodic operation reduces energy consumption compared to continuous full-power operation while maintaining adequate safety monitoring
Data Source
AI summary
An emotion mapping apparatus includes: a detector configured to sense a user's emotion state using at least one sensor; a storage in which information about a relationship between the at least one sensor and an emotion factor is stored; and a controller configured to acquire information about the user's emotion state based on a relevance that exceeds a preset reference value among user's emotion state values measured by the at least one sensor, and generates an emotion map in which information about the user's emotion state is classified according to a first emotion axis corresponding to a degree of positive and a second axis corresponding to a degree of excitability.