Worker Motion Evaluation Apparatus Using Expert Reference Comparison
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Solution Overview
Problem
Current information processing systems lack an effective method to evaluate and quantify the development of workers based on their motion patterns over time, particularly in comparison to expert standards, which is crucial for skill assessment and development monitoring.
Innovation Solution
An information processing apparatus that acquires time-series evaluation values of worker motions and reference evaluation values from experts, calculates motion levels indicating similarity, and outputs a development degree, utilizing cameras and microphones to detect various motion parameters, including facial expressions, voice analysis, and biometric data, to determine development stages and work skills.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If motion evaluation systems are introduced to assess worker skills, then skill assessment capability is improved, but system complexity increases
Solution Approach 1:
The evaluation system is segmented into distinct functional modules: an acquisition section for collecting motion data, a calculation section for processing evaluation values, and an output section for presenting results. This modular segmentation allows each component to perform a specific function, improving measurement precision while managing system complexity through organized functional divisions.
Solution Approach 2:
The information processing apparatus is designed with multi-functionality, serving as a universal evaluation system that can assess various worker skills across different tasks. The system collects diverse motion data (position, orientation, acceleration) and processes it through unified calculation algorithms, enabling broad skill assessment capability without requiring separate specialized systems for each skill type.
2Measurement precision
If multiple motion parameters are collected to improve evaluation accuracy, then measurement precision is improved, but information processing load increases
Solution Approach 1:
The system extracts only the essential motion parameters needed for skill assessment from the raw sensor data. The acquisition section collects position, orientation, and acceleration information, while the calculation section extracts key evaluation values from these parameters. This extraction process maintains measurement precision by focusing on relevant data while reducing processing load by eliminating unnecessary information.
Solution Approach 2:
Motion data is collected and pre-processed in advance through the acquisition section before being passed to the calculation section. The system preliminarily organizes raw sensor data into structured motion parameters (position, orientation, acceleration), preparing the information for efficient subsequent analysis. This preliminary action reduces the processing burden on the calculation section while preserving all necessary evaluation information.
Data Source
AI summary
An information processing apparatus includes an acquisition section that acquires at least two first evaluation values obtained by evaluating a motion of a worker in time series and a reference evaluation value obtained by evaluating a motion of an expert as an exemplar of the worker, a calculation section that calculates at least two motion levels indicating similarity between the at least two first evaluation values and the reference evaluation value, and an output section that outputs a development degree indicating a degree of development of the worker based on the at least two motion levels.