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Mapping of EMG signal to hand grip force at varying wrist angles

Sidek, Shahrul Na'im and Haja Mohideen, Ahmad Jazlan (2012) Mapping of EMG signal to hand grip force at varying wrist angles. In: IEEE EMBS International Conference on Biomedical Engineering and Sciences 2012, 17-19 Dec 2012, Langkawi, Malaysia.

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Abstract

Limb loss is a growing problem in Malaysia and the rest of the world due to the increasing number of industrial accidents, diseases and armed conflicts. After a tragic incident resulting in an amputation or paralysis, the disabled individual needs to be assisted with all possible technological means to improve his quality of life. A cybernetic prosthesis is a device which can greatly assist individuals with hand disabilities by enabling them to have some of the hand capabilities of an able bodied individual. The central nervous system which consists of the brain and spine governs hand grip force and hand movement in the human body by spatial and temporal motor unit recruitments. Electromyogram (EMG) is an electrical biological signal that can be measured from the skin surface and consists of the summation of Motor Unit Action Potentials (MUAP). Hand grip strength, wrist extension and wrist flexion are hand functions which result from the forearm muscle activity and are used in a wide range of daily tasks. Extracting hand grip force and wrist angle information from forearm EMG signals is useful to be used as inputs for the control of cybernetic prostheses. By establishing the relationship between forearm EMG and hand grip force/wrist angles, the prosthetic hand can be controlled in a manner that is customized to an amputee’s intent. In this research work, a myoelectric interface which consists of an electronic conditioning circuit to measure EMG signals and the software to record and process the EMG signals was developed. Experimental training and testing data sets from five subjects were collected to investigate the relationship between forearm EMG, hand grip force and wrist angle simultaneously.

Item Type: Conference or Workshop Item (Other)
Additional Information: 3023/69466
Uncontrolled Keywords: Electromyogram, wrist extension, wrist flexion, hand grip force, wrist angles, artificial neural networks
Subjects: T Technology > T Technology (General)
Kulliyyahs/Centres/Divisions/Institutes: Kulliyyah of Engineering > Department of Mechatronics Engineering
Depositing User: Dr. Shahrul Naim Sidek
Date Deposited: 08 Jan 2019 15:26
Last Modified: 08 Jan 2019 15:26
URI: http://irep.iium.edu.my/id/eprint/69466

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