Electromyography (EMG) analysis for pre-clinical trials of hand rehabilitation tasks

With the prevailing demand for medical care due to the graying population, there is a greater need for healthcare professionals like therapists, both physical and occupational. This project aims to integrate bio-signals, that is, electromyography (EMG) signals, with a hand rehabilitation device whic...

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Main Author: Ang, Kok Yong
Other Authors: Low Kin Huat
Format: Final Year Project
Language:English
Published: 2009
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Online Access:http://hdl.handle.net/10356/16197
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-161972023-03-04T19:15:46Z Electromyography (EMG) analysis for pre-clinical trials of hand rehabilitation tasks Ang, Kok Yong Low Kin Huat School of Mechanical and Aerospace Engineering Robotics Research Centre DRNTU::Engineering::Mechanical engineering::Assistive technology With the prevailing demand for medical care due to the graying population, there is a greater need for healthcare professionals like therapists, both physical and occupational. This project aims to integrate bio-signals, that is, electromyography (EMG) signals, with a hand rehabilitation device which serves as a tool in the therapists’ work of planning, assessing and intervention with patients. The three-tier approach implemented includes an in-depth assessment on hand motions, development of pre-clinical grading system and a comprehensive study on correlation of force and EMG signals. Primarily, the present study focuses on capturing the EMG signals for five activities for daily living (ADL) tasks – five-pulp pinch, lateral pinch, pulp-to-pulp pinch, tripod grip and cylindrical grip. The testing conducted on twenty-five subjects ranged from seventeen to seventy-eight years old. Prior to the subject testing, experimental results of specific hand motions had provided a platform for the understanding of extrinsic and intrinsic muscles and the selection muscle groups. Furthermore, the usage of fractional and factorial design of experiments, ANOVA and the least significant difference level test (t-test) has shown that age is a predominant factor attributing to the difference in EMG signals and force. Also, the age group between 45 to 59 years old is found to have little difference with the age group 60 years old or greater, but the age group, less than 45 years old, is different from the two senior age groups. Therefore, this leads to the derivation of the pre-clinical grading system for hand rehabilitation for post-stroke and spinal cord injury (SCI) patients. Lastly, to incorporate the above findings with the design domain of the hand rehabilitation device research, the relationship between force and EMG signals is further explored. The study of passive and active forces has reflected that the latter has significantly higher EMG signals comparatively. The flexion angle of fingers, position of actuator (at tip end of PIP joint) and materials of contact have shown to have an effect on the amount of force exerted too. Bachelor of Engineering (Mechanical Engineering) 2009-05-22T05:01:06Z 2009-05-22T05:01:06Z 2009 2009 Final Year Project (FYP) http://hdl.handle.net/10356/16197 en Nanyang Technological University 174 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Mechanical engineering::Assistive technology
spellingShingle DRNTU::Engineering::Mechanical engineering::Assistive technology
Ang, Kok Yong
Electromyography (EMG) analysis for pre-clinical trials of hand rehabilitation tasks
description With the prevailing demand for medical care due to the graying population, there is a greater need for healthcare professionals like therapists, both physical and occupational. This project aims to integrate bio-signals, that is, electromyography (EMG) signals, with a hand rehabilitation device which serves as a tool in the therapists’ work of planning, assessing and intervention with patients. The three-tier approach implemented includes an in-depth assessment on hand motions, development of pre-clinical grading system and a comprehensive study on correlation of force and EMG signals. Primarily, the present study focuses on capturing the EMG signals for five activities for daily living (ADL) tasks – five-pulp pinch, lateral pinch, pulp-to-pulp pinch, tripod grip and cylindrical grip. The testing conducted on twenty-five subjects ranged from seventeen to seventy-eight years old. Prior to the subject testing, experimental results of specific hand motions had provided a platform for the understanding of extrinsic and intrinsic muscles and the selection muscle groups. Furthermore, the usage of fractional and factorial design of experiments, ANOVA and the least significant difference level test (t-test) has shown that age is a predominant factor attributing to the difference in EMG signals and force. Also, the age group between 45 to 59 years old is found to have little difference with the age group 60 years old or greater, but the age group, less than 45 years old, is different from the two senior age groups. Therefore, this leads to the derivation of the pre-clinical grading system for hand rehabilitation for post-stroke and spinal cord injury (SCI) patients. Lastly, to incorporate the above findings with the design domain of the hand rehabilitation device research, the relationship between force and EMG signals is further explored. The study of passive and active forces has reflected that the latter has significantly higher EMG signals comparatively. The flexion angle of fingers, position of actuator (at tip end of PIP joint) and materials of contact have shown to have an effect on the amount of force exerted too.
author2 Low Kin Huat
author_facet Low Kin Huat
Ang, Kok Yong
format Final Year Project
author Ang, Kok Yong
author_sort Ang, Kok Yong
title Electromyography (EMG) analysis for pre-clinical trials of hand rehabilitation tasks
title_short Electromyography (EMG) analysis for pre-clinical trials of hand rehabilitation tasks
title_full Electromyography (EMG) analysis for pre-clinical trials of hand rehabilitation tasks
title_fullStr Electromyography (EMG) analysis for pre-clinical trials of hand rehabilitation tasks
title_full_unstemmed Electromyography (EMG) analysis for pre-clinical trials of hand rehabilitation tasks
title_sort electromyography (emg) analysis for pre-clinical trials of hand rehabilitation tasks
publishDate 2009
url http://hdl.handle.net/10356/16197
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