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A novel method to calculate the anomaly score of movement variability of repetitive tasks
Author(s) -
Hiranai Kazuki,
Kuramoto Akisue,
Seo Akihiko
Publication year - 2020
Publication title -
human factors and ergonomics in manufacturing and service industries
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.408
H-Index - 39
eISSN - 1520-6564
pISSN - 1090-8471
DOI - 10.1002/hfm.20847
Subject(s) - elbow , anomaly (physics) , movement (music) , rotation (mathematics) , work (physics) , elbow flexion , physical medicine and rehabilitation , computer science , tracking (education) , motion (physics) , mathematics , artificial intelligence , psychology , medicine , engineering , acoustics , physics , anatomy , mechanical engineering , pedagogy , condensed matter physics
This study proposes a new calculation method for the anomaly score of repetitive tasks based on singular spectrum transformation (SST) that accounted for a long‐term history of human motion. To validate the efficacy of the proposed method, the calculated anomaly score was compared with movement variability computed by a traditional method and to its SST‐computed score. Eleven male participants performed repetitive lightweight material handling tasks under different work conditions and an electromagnetic tracking system measured their working posture. Movement variability and anomaly score on the shoulder and elbow joints were calculated based on measured working postures. The movement variability on the elbow flexion angle increased with time. In contrast, the anomaly score of the elbow flexion angle decreased with time, but shoulder flexion and inner rotation angles showed increased scores with the passage of time. These findings are similar to those of previous studies that stated that movement variability increased from redundant degrees of freedom available for performing multi‐joint movements; this occurred due to the development of muscle fatigue on the shoulder joint from performing repetitive tasks. On comparing this to the anomaly scores calculated by conventional SST, it was observed that the score computed by the proposed method reflected the whole trend of human motion in repetitive tasks and did not depend on local problems in working posture. Therefore, it was concluded that the new method of calculating the anomaly score is more suitable to detect changes in movement variability in repetitive tasks.