Analysis of Different Hand and Finger Grip Patterns using Surface Electromyography and Hand Dynamometry

Recording an Electromyogram (EMG) signal is essential for diagnostic procedures like muscle health assessment and motor neurons control. The EMG signals have been used as a source of control for powered prosthetics to support people to accomplish their activities of daily living (ADLs). This work d...

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Autores principales:	A. Buniya, Ali H. Al-Timemy, A. Aldoori, Rami N. Khushaba
Formato:	article
Lenguaje:	EN
Publicado:	Al-Khwarizmi College of Engineering – University of Baghdad 2020
Materias:	Chemical engineering TP155-156 Engineering (General). Civil engineering (General) TA1-2040
Acceso en línea:	https://doaj.org/article/adac7a05598a4bdba99494ee532f3418
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spelling	oai:doaj.org-article:adac7a05598a4bdba99494ee532f34182021-12-02T10:12:41ZAnalysis of Different Hand and Finger Grip Patterns using Surface Electromyography and Hand Dynamometry10.22153/kej.2020.05.0011818-11712312-0789https://doaj.org/article/adac7a05598a4bdba99494ee532f34182020-06-01T00:00:00Zhttp://alkej.uobaghdad.edu.iq/index.php/alkej/article/view/679https://doaj.org/toc/1818-1171https://doaj.org/toc/2312-0789 Recording an Electromyogram (EMG) signal is essential for diagnostic procedures like muscle health assessment and motor neurons control. The EMG signals have been used as a source of control for powered prosthetics to support people to accomplish their activities of daily living (ADLs). This work deals with studying different types of hand grips and finding their relationship with EMG activity. Five subjects carried out four functional movements (fine pinch, tripod grip and grip with the middle and thumb finger, as well as the power grip). Hand dynamometer has been used to record the EMG activity from three muscles namely; Flexor Carpi Radialis (FCR), Flexor Digitorum Superficialis (FDS), and Abductor Pollicis Brevis (ABP) with different levels of Maximum Voluntary Contraction (MVC) (10-100%). In order to analyze the collected EMG and force data, the mean absolute value of each trial is calculated followed by a calculation of the average of the 3 trials for each grip for each subject across the different MVC levels utilized in the study. Then, the mean and the standard deviation (SD) across all participants (3 males and 2 females) are calculated for FCR, FDS and APB muscles with multiple % MVC, i.e 10, 30, 50, 70 % MVC for each gesture. The results showed that APB muscle has the highest mean EMG activity across all grips, followed by FCR muscle. Furthermore, the grip with the thumb and middle fingers is the grip with the highest EMG activity for 10-70% MVC than the power grip. As for the 100% MVC, thumb and middle fingers grip achieved the highest EMG activity for APB muscle, while the power grip has the highest EMG activity for both FCR and FDS muscles. A. BuniyaAli H. Al-TimemyA. AldooriRami N. KhushabaAl-Khwarizmi College of Engineering – University of BaghdadarticleChemical engineeringTP155-156Engineering (General). Civil engineering (General)TA1-2040ENAl-Khawarizmi Engineering Journal, Vol 16, Iss 2 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Chemical engineering TP155-156 Engineering (General). Civil engineering (General) TA1-2040
spellingShingle	Chemical engineering TP155-156 Engineering (General). Civil engineering (General) TA1-2040 A. Buniya Ali H. Al-Timemy A. Aldoori Rami N. Khushaba Analysis of Different Hand and Finger Grip Patterns using Surface Electromyography and Hand Dynamometry
description	Recording an Electromyogram (EMG) signal is essential for diagnostic procedures like muscle health assessment and motor neurons control. The EMG signals have been used as a source of control for powered prosthetics to support people to accomplish their activities of daily living (ADLs). This work deals with studying different types of hand grips and finding their relationship with EMG activity. Five subjects carried out four functional movements (fine pinch, tripod grip and grip with the middle and thumb finger, as well as the power grip). Hand dynamometer has been used to record the EMG activity from three muscles namely; Flexor Carpi Radialis (FCR), Flexor Digitorum Superficialis (FDS), and Abductor Pollicis Brevis (ABP) with different levels of Maximum Voluntary Contraction (MVC) (10-100%). In order to analyze the collected EMG and force data, the mean absolute value of each trial is calculated followed by a calculation of the average of the 3 trials for each grip for each subject across the different MVC levels utilized in the study. Then, the mean and the standard deviation (SD) across all participants (3 males and 2 females) are calculated for FCR, FDS and APB muscles with multiple % MVC, i.e 10, 30, 50, 70 % MVC for each gesture. The results showed that APB muscle has the highest mean EMG activity across all grips, followed by FCR muscle. Furthermore, the grip with the thumb and middle fingers is the grip with the highest EMG activity for 10-70% MVC than the power grip. As for the 100% MVC, thumb and middle fingers grip achieved the highest EMG activity for APB muscle, while the power grip has the highest EMG activity for both FCR and FDS muscles.
format	article
author	A. Buniya Ali H. Al-Timemy A. Aldoori Rami N. Khushaba
author_facet	A. Buniya Ali H. Al-Timemy A. Aldoori Rami N. Khushaba
author_sort	A. Buniya
title	Analysis of Different Hand and Finger Grip Patterns using Surface Electromyography and Hand Dynamometry
title_short	Analysis of Different Hand and Finger Grip Patterns using Surface Electromyography and Hand Dynamometry
title_full	Analysis of Different Hand and Finger Grip Patterns using Surface Electromyography and Hand Dynamometry
title_fullStr	Analysis of Different Hand and Finger Grip Patterns using Surface Electromyography and Hand Dynamometry
title_full_unstemmed	Analysis of Different Hand and Finger Grip Patterns using Surface Electromyography and Hand Dynamometry
title_sort	analysis of different hand and finger grip patterns using surface electromyography and hand dynamometry
publisher	Al-Khwarizmi College of Engineering – University of Baghdad
publishDate	2020
url	https://doaj.org/article/adac7a05598a4bdba99494ee532f3418
work_keys_str_mv	AT abuniya analysisofdifferenthandandfingergrippatternsusingsurfaceelectromyographyandhanddynamometry AT alihaltimemy analysisofdifferenthandandfingergrippatternsusingsurfaceelectromyographyandhanddynamometry AT aaldoori analysisofdifferenthandandfingergrippatternsusingsurfaceelectromyographyandhanddynamometry AT raminkhushaba analysisofdifferenthandandfingergrippatternsusingsurfaceelectromyographyandhanddynamometry
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Analysis of Different Hand and Finger Grip Patterns using Surface Electromyography and Hand Dynamometry

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