TY - GEN
T1 - Prediction of Fingertip Force Based on the Muscle Characteristics Using Element Description Method
AU - Sodenaga, Daiki
AU - Takeuchi, Issei
AU - Silva, Daswin De
AU - Katsura, Seiichiro
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
KW - Biological Signal
KW - Force Prediction
KW - Muscle Characteristics
KW - Surface-Electromyography
UR - http://www.scopus.com/inward/record.url?scp=85199637204&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85199637204&partnerID=8YFLogxK
U2 - 10.1109/ISIE54533.2024.10595767
DO - 10.1109/ISIE54533.2024.10595767
M3 - Conference contribution
AN - SCOPUS:85199637204
T3 - IEEE International Symposium on Industrial Electronics
BT - 2024 33rd International Symposium on Industrial Electronics, ISIE 2024 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 33rd International Symposium on Industrial Electronics, ISIE 2024
Y2 - 18 June 2024 through 21 June 2024
ER -