A hybrid FPGA-based system for EEG-and EMG-based online movement prediction

H Wöhrle, M Tabie, SK Kim, F Kirchner, EA Kirchner - Sensors, 2017 - mdpi.com
A current trend in the development of assistive devices for rehabilitation, for example
exoskeletons or active orthoses, is to utilize physiological data to enhance their functionality …

Enhanced performance for multi-forearm movement decoding using hybrid IMU–SEMG interface

W Shahzad, Y Ayaz, MJ Khan, N Naseer… - Frontiers in …, 2019 - frontiersin.org
Control of active prosthetic hands using surface electromyography (sEMG) signals is an
active research area; despite the advances in sEMG pattern recognition and classification …

Hand movement recognition based on singular value decomposition of surface EMG signal

O Iqbal, SA Fattah, S Zahin - 2017 IEEE Region 10 …, 2017 - ieeexplore.ieee.org
Surface electromyography (sEMG) signals represent electrical activity of muscle cells and
are extensively used for prosthetics development. In this paper, an effective technique is put …

Machine learning techniques for gesture recognition

CA Caceres - 2014 - vtechworks.lib.vt.edu
Classification of human movement is a large field of interest to Human-Machine Interface
researchers. The reason for this lies in the large emphasis humans place on gestures while …

Cost-effective system for the classification of muscular intent using surface electromyography and artificial neural networks

A Khanna… - … International conference of …, 2017 - ieeexplore.ieee.org
This paper presents the implementation of a system to classify muscular intent. A neural
network is used for this purpose. After skin preparation, feature extraction, network training …