Abstract
Tremor is a neurological condition present in half of all multiple sclerosis and Parkinson cases, resulting in involuntary, debilitating movement oscillations. Functional electrical stimulation (FES) can be used to suppress tremor, but current approaches using classical control methods have shown significant limitations. This paper establishes the feasibility of using repetitive control (RC), giving rise to the first FES control structure that embeds learning from experience for the purpose of suppressing tremor. The paradigm is applied to suppress tremor at the wrist via FES regulated co-contraction of wrist extensors/flexors. Experimental evaluation is performed using a validated wrist-rig and results are compared against classical feedback control design to establish the efficacy of the approach.
Original language | English |
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Pages | 6023 - 6028 |
DOIs | |
Publication status | Published - 11 Feb 2016 |
Event | IEEE Conference on Decision and Control - Osaka, Japan Duration: 15 Dec 2015 → 18 Dec 2015 |
Conference
Conference | IEEE Conference on Decision and Control |
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Country/Territory | Japan |
City | Osaka |
Period | 15/12/15 → 18/12/15 |
Bibliographical note
The full text is currently unavailable on the repository.Keywords
- Muscles
- Wrist
- Torque
- Electrical stimulation
- Steady-state
- Contracts
- Heuristic algorithms
- neuromuscular stimulation
- diseases
- medical control systems
- medical disorders
- feedback control design
- FES based tremor suppression
- repetitive control
- neurological condition
- sclerosis
- Parkinson
- involuntary debilitating movement oscillations
- functional electrical stimulation
- FES control
- FES regulated cocontraction
- wrist extensors
- wrist-rig
- Modelling
- Tremor suppression
- Functional electrical stimulation
- Repetitive control
- Induced tremor