Abstract
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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 374-383 |
| Number of pages | 10 |
| Journal | Simulation Series |
| Volume | 54 |
| Issue number | 1 |
| State | Published - 2022 |
| Event | 2022 Annual Modeling and Simulation Conference, ANNSIM 2022 - San Diego, United States Duration: Jul 18 2022 → Jul 20 2022 |
Keywords
- artificial neural networks
- electromyography
- functional electrical stimulation
- rehabilitation
- system identification
ASJC Scopus subject areas
- Computer Networks and Communications