Four Gesture Recognization of a Robotic Hand using EMG

Maryam Arshad, Nimra Iftikhar, Noman Naseer

Abstract

Electromyography (EMG) measures muscle response when nerves are stimulated. The objective of this research paper is to present a work on control of a robotic hand using Electromyography. CAD model was selected using various open sources. The structure is printed with poly laic acid (PLA) material with the help of a 3D printer. EMG signals were acquired by wearing the eight channel Myo Armband, placed on the forearm muscles of 10 subjects. Then, these signals were filtered to remove noise. Different features are applied on noise free acquired signal and KNN is used for classification. From the KNN classifier, we achieved 98.9% accuracy. Gestures exhibited were Victory, Thumbs Up, Open Hand and Grasp. The classified signals are used to control the robotic hand.

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Paper Citation


in Harvard Style

Arshad M., Iftikhar N. and Naseer N. (2020). Four Gesture Recognization of a Robotic Hand using EMG.In Proceedings of the International Conference on Health Informatics, Medical, Biological Engineering, and Pharmaceutical - Volume 1: HIMBEP, ISBN 978-989-758-500-5, pages 80-87. DOI: 10.5220/0010289100800087


in Bibtex Style

@conference{himbep20,
author={Maryam Arshad and Nimra Iftikhar and Noman Naseer},
title={Four Gesture Recognization of a Robotic Hand using EMG},
booktitle={Proceedings of the International Conference on Health Informatics, Medical, Biological Engineering, and Pharmaceutical - Volume 1: HIMBEP,},
year={2020},
pages={80-87},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010289100800087},
isbn={978-989-758-500-5},
}


in EndNote Style

TY - CONF

JO - Proceedings of the International Conference on Health Informatics, Medical, Biological Engineering, and Pharmaceutical - Volume 1: HIMBEP,
TI - Four Gesture Recognization of a Robotic Hand using EMG
SN - 978-989-758-500-5
AU - Arshad M.
AU - Iftikhar N.
AU - Naseer N.
PY - 2020
SP - 80
EP - 87
DO - 10.5220/0010289100800087