Electromyography-Based Detection of Human Hand Movement Gestures

Autor:	C. H. Shameem Sharmina, Rajesh Reghunadhan
Rok vydání:	2020
Předmět:	medicine.diagnostic_test business.industry Computer science Feature extraction medicine Pattern recognition Electromyography Artificial intelligence Movement detection business Hand movements Gesture
Zdroj:	Algorithms for Intelligent Systems ISBN: 9789811552427
DOI:	10.1007/978-981-15-5243-4_69
Popis:	Electromyography (EMG) signal is considered to be one of the most significant signals for the classification of the movements of muscle and has very good applications in artificial limb control. It is very important to find out a set of minimal features from the signal which quickly classifies the movements. This paper proposes EMG-based hand movement detection using entropy features. The experimental results show that entropy has discriminant ability to classify the movements. Combination of entropy features with other features gave much promising results compared to the results of Christos Sapsanis et al.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::cb96637c262b09110dde2da3e55be73d https://doi.org/10.1007/978-981-15-5243-4_69 Zobrazit plný text záznamu