Child State Image Extraction via Biological Data Synchronization
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Solution Overview
Problem
Conventional systems struggle to identify play behavior that attracts a child's interest and provide images indicating the child's state during such behavior, making it difficult for nursery-school teachers to create effective daily childcare records.
Innovation Solution
An information processing method that acquires biological information and images of a child in synchronization, identifies person identification information, and stores it with the images, allowing for the extraction and transmission of images associated with the child's state information selected by another person, such as a nursery-school teacher.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional play behavior recognition systems are used, then play behavior classification is achieved, but identification of behavior that attracts child's interest cannot be provided
Solution Approach 1:
The system segments behavior analysis into two distinct dimensions: play behavior classification (conventional) and interest level detection (new). By separating these functions and applying different measurement approaches - using biological information metrics like heart rate variability for interest detection while maintaining posture-based classification for play behavior - the system recovers the lost information about child's interest without compromising the precision of behavior classification.
Solution Approach 2:
The patent introduces biological information (heart rate, skin conductance, temperature) as an intermediary indicator to indirectly measure the child's interest level. Rather than directly observing interest which is subjective and difficult to measure, the system uses physiological responses as mediators that objectively reflect the child's engagement and interest state, thereby recovering the previously lost information.
2Loss of information
If detailed behavior monitoring is implemented, then behavior classification improves, but ability to provide images indicating child's state is insufficient
Solution Approach 1:
The system merges multiple data sources - camera images, biological information sensors, and behavior classification data - into a unified information processing framework. By combining these previously separate functions into one integrated system that processes all data together and produces comprehensive output including relevant images, the system recovers the lost visual information without proportionally increasing complexity, as the components work synergistically.
Solution Approach 2:
The information processing device is designed with multi-functionality, serving both conventional play behavior classification and the new function of interest-level-based image provision. The same system infrastructure processes both posture data for behavior classification and biological information for interest detection, then outputs both classification results and relevant images. This universal approach allows the system to provide comprehensive visual information without requiring separate dedicated systems for each function.
3Measurement precision
If comprehensive data collection is performed, then behavior recognition accuracy improves, but data storage and retrieval efficiency decreases
Solution Approach 1:
The system performs preliminary organization of collected data by automatically tagging and categorizing each data point (image, biological information, behavior classification) with metadata including time stamps, behavior type, and calculated interest levels. This preliminary structuring occurs at the time of data collection rather than during retrieval, enabling efficient subsequent access. When teachers need information, the pre-organized data can be quickly retrieved based on behavior type or interest level without reprocessing the entire dataset, thus maintaining high recognition accuracy while reducing retrieval time.
Solution Approach 2:
The system employs a selective data retention strategy where not all collected data is stored indefinitely. Instead, data is archived or discarded based on its relevance and the calculated interest level. High-interest behaviors are retained with full detail for later review, while low-interest routine behaviors may be summarized or discarded. This approach maintains the accuracy needed for important behaviors while reducing the overall data storage burden and improving retrieval efficiency by focusing on meaningful data.
Data Source
AI summary
An information processing method includes, by a computer: acquiring biological information on a first person; acquiring an image obtained by imaging the first person in synchronization with acquisition timing of the biological information; identifying person identification information for identifying the first person based on the image; storing, in a storage unit, the identified person identification information, the acquired biological information, and the acquired image in association with one another; acquiring the person identification information on the first person selected by a second person different from the first person, and state information indicating a state of the first person selected by the second person; and extracting, from the storage unit, the image associated with the acquired person identification information and the biological information corresponding to the acquired state information.