TY - GEN
T1 - Simulation-Based Framework To Develop A Control System For Functional Electrical Stimulation
AU - Hong, Minsik
AU - Hasse, Brady A.
AU - Fuglevand, Andrew J.
AU - Rozenblit, Jerzy W.
N1 - Publisher Copyright:
© 2022 SCS.
PY - 2022
Y1 - 2022
N2 - Functional electrical stimulation (FES) has long been used to restore movements in paralyzed individuals. However, other than a small set of simple, preprogrammed movements, it has been challenging to accurately evoke natural movements with FES. This is due to the complexity of the system and moment-by-moment changes in the efficacy of stimulation and muscle fatigue. In this paper, a simulation-based design framework is proposed to develop and validate a FES control system that produces a wide range of complex upper limb movements. By using index finger motions with electromyographic signals as an example, we show the feasibility and effectiveness of the proposed framework to develop an advanced FES control system. Also, we show that error compensations could be used to command adjustments across a population of muscles to enhance movement accuracy.
AB - Functional electrical stimulation (FES) has long been used to restore movements in paralyzed individuals. However, other than a small set of simple, preprogrammed movements, it has been challenging to accurately evoke natural movements with FES. This is due to the complexity of the system and moment-by-moment changes in the efficacy of stimulation and muscle fatigue. In this paper, a simulation-based design framework is proposed to develop and validate a FES control system that produces a wide range of complex upper limb movements. By using index finger motions with electromyographic signals as an example, we show the feasibility and effectiveness of the proposed framework to develop an advanced FES control system. Also, we show that error compensations could be used to command adjustments across a population of muscles to enhance movement accuracy.
KW - artificial neural networks
KW - electromyography
KW - functional electrical stimulation
KW - rehabilitation
KW - system identification
UR - http://www.scopus.com/inward/record.url?scp=85138097350&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85138097350&partnerID=8YFLogxK
U2 - 10.23919/ANNSIM55834.2022.9859316
DO - 10.23919/ANNSIM55834.2022.9859316
M3 - Conference contribution
AN - SCOPUS:85138097350
T3 - Proceedings of the 2022 Annual Modeling and Simulation Conference, ANNSIM 2022
SP - 351
EP - 360
BT - Proceedings of the 2022 Annual Modeling and Simulation Conference, ANNSIM 2022
A2 - Martin, Cristina Ruiz
A2 - Emami, Niloufar
A2 - Blas, Maria Julia
A2 - Rezaee, Roya
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 Annual Modeling and Simulation Conference, ANNSIM 2022
Y2 - 18 July 2022 through 20 July 2022
ER -