Affinity Detection via Vital Sign Time-Series Analysis
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Solution Overview
Problem
Existing methods struggle to precisely calculate relations between persons based on smiling levels in images, as they require extensive interaction time and are not accurate for short interactions.
Innovation Solution
An information processing system that acquires and analyzes time-series data of vital sign information, such as heart rates and facial expressions, from multiple individuals to determine emotional responses and specify affinities between them.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If smiling levels in images are used to calculate relations between persons, then the measurement process is simple, but the measurement precision is insufficient
Solution Approach 1:
The patent combines multiple measurement approaches: image processing for smiling levels, speech analysis for emotional states, and physiological sensor data (heart rate, skin conductance). By merging these diverse data sources, the system achieves high measurement precision while maintaining practical ease of implementation through integrated processing.
Solution Approach 2:
The system creates a composite measurement framework that integrates visual data (smiling levels from images), auditory data (speech emotion recognition), and physiological data (sensor measurements). This composite approach allows the system to overcome the limitations of any single measurement method and achieve both simplicity and precision.
2Loss of time
If only several-hour interaction data is collected, then the data collection time is short, but the reliability of affinity determination is insufficient
Solution Approach 1:
The patent changes the parameters being measured from simple smiling levels to a comprehensive set including physiological parameters (heart rate, skin conductance, temperature), speech characteristics, and emotional state indicators. By measuring multiple parameters simultaneously over short periods, the system achieves high reliability without requiring extended interaction times.
Solution Approach 2:
The system continuously collects and processes multiple types of data (images, speech, physiological signals) simultaneously throughout the interaction period. This continuous multi-dimensional measurement ensures that sufficient information is gathered even during brief interactions, maintaining high reliability while minimizing time loss.
3Measurement precision
If multiple data types are collected simultaneously, then the measurement precision is improved, but the device complexity increases
Solution Approach 1:
The patent implements a multi-functional information processing system that handles image processing, speech recognition, and physiological sensor data collection through integrated processing. The control unit performs multiple functions (data acquisition, synchronization, analysis, and affinity calculation) within a single system framework, reducing overall device complexity while maintaining high measurement precision.
Solution Approach 2:
The system uses an intermediary control unit that coordinates data collection from multiple sources (cameras, microphones, sensors) and synchronizes them with the video timeline. This intermediary component manages the complexity of multi-data collection by providing a unified interface and centralized processing, allowing precise emotional response detection without proportionally increasing system complexity.
Data Source
AI summary
An information processing system including an acquisition unit that acquires time-series data representing vital sign information of a plurality of persons who share a location in a predetermined time, and a control unit that specifies persons who have a same or similar emotional response as persons having a good affinity with each other in accordance with the time-series data acquired by the acquisition unit.