講演・口頭発表等

2019年1月1日

Workload Estimation System of Sequential Manual Tasks by Using Muscle Fatigue Model

Advances in Intelligent Systems and Computing
  • Akihiko Seo
  • ,
  • Maki Sakaguchi
  • ,
  • Kazuki Hiranai
  • ,
  • Atsushi Sugama
  • ,
  • Takanori Chihara

© 2019, Springer Nature Switzerland AG. In this study, we sought to develop a system to evaluate the workload of multiple sequential tasks using a digital human and muscle fatigue model, as well as test its validity using a sequential task experiment. The muscle fatigue model is the three-component model introduced by Xia et al. The model assumes that the muscle motor unit consists of resting, activated, and fatigued components. We used a temporal smoothed value of the active component ratio to the non-fatigued component to estimate workload. A system was developed using this model to evaluate workload of any combination of sequential tasks of the single manual handling task. A sequential task consisting of three kinds of material handling task performed by a digital human and real environment was prepared as a validity test. We found that the estimated workload using the simulation and the subjective scores showed a similar pattern with the load of the sequential tasks and repetitions.

リンク情報
URL
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85052093289&origin=inward
DOI
https://doi.org/10.1007/978-3-319-96068-5_9