Surface Electromyographic signal based finger prosthesis control using ANN

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dc.contributor.authorIslam, Jahedul
dc.contributor.authorSarker, Dhiman Kumar
dc.contributor.authorDas, Piyas
dc.date.accessioned2026-07-06T21:29:18Z
dc.date.available2026-07-06T21:29:18Z
dc.date.issued26-Sep-2019
dc.description.abstractThis paper represents the development of surface Electromyographic (sEMG) signal-based finger prosthesis control. A filter & amplifier circuit captures the EMG signal from the surface of the human hand that can be recorded using ATmega-2560 micro-controller. The analysis of the output signal is done to study time domain features. In this paper, standard deviation, mean, a variance is taken as time domain feature. The signal is then trained using simple Artificial Neural Network to classify accurately two finger motion i.e. grip motion and thumb index finger motion.
dc.identifier.otherhttp://103.99.128.19:8080/jspui/handle/123456789/390
dc.identifier.urihttp://103.99.128.19:8080/xmlui/handle/123456789/390
dc.publisherDepartment of Electrical and Electronics Engineering, IUB
dc.sourceCUET Digital Repository
dc.subjectATmega-2560
dc.subjectsEMG Signal
dc.subjectElectrode
dc.subjectServo
dc.subjectInstrumentation Amplifier
dc.subjectMoving Average
dc.subjectANN
dc.titleSurface Electromyographic signal based finger prosthesis control using ANN
dc.title.alternative5th International Conference on Advances in Electrical Engineering (ICAEE) 2019
dc.title.alternativeICAEE 2019

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