Elicitation hybrid spatial features from HD-sEMG signals for robust classification of gestures in real-time

ABSTRACT

Recently, using high-density surface electromyography (HD-sEMG) electrodes in prosthetics have outdone the challenges of electrodes sites on the muscle, while the high accuracy of HD-sEMG signals classification will improve prosthetics performance. A new concept has emerged that the robust features extraction methods increase the efficiency of the classification regardless of the classifier. In addition, there are many factors affecting the quality of the signal, and thus the quality of classification such as stress, fatigue, disease, muscular dystrophy … etc. In this paper, these challenges will be reduced by the proposed approach for extraction hybrid features from the HD-EMG signal based on the histogram-oriented gradient (HOG) algorithm and signal intensity features, where the support vector machine (SVM) classifier is used for the classification process. The results showed high accuracy of the classification and successful in real-time tests. Also, the classification results of these experiments have overcome the challenge of long term classification.

KEYWORDS:

• gesture recognition; spatial features; SVM classifier; online classification

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Hanadi Abbas Jaber

Hanadi A. Jaber was born in Baghdad, Iraq in 1976. She received the B.S. and M.S. degrees in computer and Control Engineering from the University of Technology, Baghdad,  and Ph.D. degree in Electrical Engineering from University of Basrah, basra, Iraq.  Currently she is a lecturer at university of Basrah, Computer Engineering Department. Her research interests include Myoelectric pattern recognition, machine learning  techniques and control systems. 

Mofeed Turky Rashid

Mofeed T.Rashid  was born in Basrah, Iraq on 2/10/1976. He received the B.Eng. degree in electrical engineering from the University of Basrah, Basrah, Iraq, in 1998, the M.Sc. degree in electrical engineering from the University of Basrah, Basrah, Iraq, in 2001, and the Ph.D. degree in control and computer engineering from the University of Basrah, Basrah, Iraq, in 2011. He studied at DIEEI Lab., Catania University, Catania, Italy, by six-month fellowship program. He has held lecturing positions at The Omar al-Mukhtar University, Tobruk, Libya. He was a Lecturer at the Iraq University College, Basrah, Iraq, and The Shatt-Alarab University College, Basrah, Iraq, for several years. He is currently a Lecturer atthe University of Basrah, Basrah, Iraq. He is also a Professor with Basrah University, Basrah, Iraq. His research interests cover the design and analysis of various control systems, DCS, electrical machines and robotics systems.

Luigi Fortuna

Luigi Fortuna was born in Siracusa on 27/05/1953, engineer, is Full Professor of System Theory since November 1994 at the University of Catania where he is Head of the Department and co-ordinator of the Ph.D. Course in Electronic and Automatic Engineering. He is author of more than 400 scientific publications; among them seven are books published by international editors. He is author of 10 industrial patents. He is in charge for a series of contracts with public and private companies (exMURST,CNR, ENEA, EURATOM, ERG Petroli, ASI, STMicroelectronics, etc). At present he is local co-ordinator of two EC projects (ISAMCO and SPARK). He is national responsible of the FIRB project ”Cellular self organizing nets and chaotic nonlinear dynamics to model and control complex systems”. He is IEEE Fellow, Chairman of the IEEE Committee on CNNs.