Analysis of Electromyography Signals for Control Models of Power-Assisted Stroke Rehabilitation Devices of Upper Limb System - 12th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2021 Access content directly
Conference Papers Year : 2021

Analysis of Electromyography Signals for Control Models of Power-Assisted Stroke Rehabilitation Devices of Upper Limb System

Abstract

Stroke is a significant affliction that can affect people with varying degrees of severity. One of the most common consequences of stroke is the impairment of the muscular motor function to some degree with two-thirds of the patients being affected by upper-limb paralysis. For those cases, the most effective forms of regaining muscular motor function are through rehabilitation therapy, traditionally this must be done in a clinical environment. Developments in robotics, batteries and electronics have made accessible the prototyping, production, and utilization of exoskeleton type devices technically adapted for personal and residential rehabilitation. This paper presents and discusses the results of EMG signals from upper limb of brachial biceps muscle, obtained from a cohort of healthy volunteers. The methodology for testing is presented and explained, additionally, a preliminary discussion is made on the obtained data. Some control considerations, variables and methods are also presented and discussed.
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hal-03685922 , version 1 (02-06-2022)

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Paulo Bonifácio, Valentina Vassilenko, Guilherme Marques, Diogo Casal. Analysis of Electromyography Signals for Control Models of Power-Assisted Stroke Rehabilitation Devices of Upper Limb System. 12th Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), Jul 2021, Costa de Caparica, Portugal. pp.307-315, ⟨10.1007/978-3-030-78288-7_29⟩. ⟨hal-03685922⟩
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