Prediction of Fingertip Force Based on the Muscle Characteristics Using Element Description Method

Daiki Sodenaga, Issei Takeuchi, Daswin De Silva, Seiichiro Katsura

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Human motion prediction based on the biological signal has been improved because of the improvement of an artificial intelligent (AI) technology. Conventional methods to predict a human motion have been based on a machine learning such as a neural network, a regression model and so on. From the above, the model by them cannot generate the model whose calculation process is not clear. Then, it is impossible to interpret the relationship between input and output information. In this paper, the element description method (EDM) was applied to generate the model and the prediction of human motion and the analysis about muscle characteristics had been done. An EDM is one of the system identification methods and it is possible to interpret the relationship between input and output because it can generate a block diagram of the model. Especially, the fingertip force and the surface-electromyography (sEMG) of the muscles which move the joint were focused in this paper Moreover, the fingertip force was estimated from the SEMG and it was also done to analyze the muscle characteristics based on the model by an EDM.

Original languageEnglish
Title of host publication2024 33rd International Symposium on Industrial Electronics, ISIE 2024 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350394085
DOIs
Publication statusPublished - 2024
Event33rd International Symposium on Industrial Electronics, ISIE 2024 - Ulsan, Korea, Republic of
Duration: 2024 Jun 182024 Jun 21

Publication series

NameIEEE International Symposium on Industrial Electronics
ISSN (Print)2163-5137
ISSN (Electronic)2163-5145

Conference

Conference33rd International Symposium on Industrial Electronics, ISIE 2024
Country/TerritoryKorea, Republic of
CityUlsan
Period24/6/1824/6/21

Keywords

  • Biological Signal
  • Force Prediction
  • Muscle Characteristics
  • Surface-Electromyography

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering

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