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Deep learning-based classification using Cumulants and Bispectrum of EMG signals
(Institute of Electrical and Electronics Engineers, 2019-12)
Surface electromyographic signals (EMG) historically have been used to classify tasks in basis of a feature extraction scheme and low complexity classifiers. Deep networks, as Multilayer Perceptron and Convolutional Neural ...
Metodologia para classificação de sinais EMG para controle de próteses com baixo esforço computacionalLow computational power methodology for EMG classification for use in prosthesis control
(Universidade Federal de UberlândiaBRPrograma de Pós-graduação em Engenharia ElétricaEngenhariasUFU, 2016)
Recognition of Movements Through Dynamic Electromyographic Signals
(ESRSA Publications, 2016-02)
The recognition of movements through electromyographic (EMG) signals is critical for myoelectric control systems. Performance of these systems depend on processing methods and protocols used to extract the EMG signals. The ...
Análise de técnicas de classificação de sinais de eletromiografia para controle de prótese de membro superior
(Universidade Estadual Paulista (Unesp), 2020-07-31)
A classificação de sinais eletromiográficos é uma tarefa importante para o controle de próteses ativas de membros superiores. Este trabalho propõe analisar e avaliar técnicas e ferramentas para classificação de sinais ...
Lower limbs motion intention detection by using pattern recognition
(Institute of Electrical and Electronics Engineers Inc., 2018)
Electromyographic (EMG) signals processing allows to perform the detection of the intention of movement of the limbs of the human body in order to further use this decision to control wearable devices. For instance, robotic ...
Emotion stimuli-based surface electromyography signal classification employing Markov transition field and deep neural networks
Surface electromyography (sEMG) has been widely used in clinical medicine, rehabilitation medicine, and intelligent robots. Currently, sEMG signal classification methods promoted the development and industrialization of ...
Detección de patrones para trabajo en conjunto de EMG y EEG para prótesis de mano
(Universidad de los AndesMaestría en Ingeniería BiomédicaFacultad de IngenieríaDepartamento de Ingeniería Biomédica, 2017)
"This work shows proofs of concept for the development of upper limb prostheses control systems, working in conjunction with electromyography (EMG) and electroencephalography (EEG) signals, or also called hybridBCI (hBCI). ...
Bispectrum-based features classification for myoelectric control
(Elsevier, 2013-03)
Surface electromyographic signals provide useful information about motion intentionality. Therefore, they are a suitable reference signal for control purposes. A continuous classification scheme of five upper limb movements ...
sEMG feature evaluation for identification of elbow angle resolution in graded arm movement
(2014)
© 2014 Castro et al.Automatic and accurate identification of elbow angle from surface electromyogram (sEMG) is essential for myoelectric controlled upper limb exoskeleton systems. This requires appropriate selection of ...
Optimization of Features to Classify Upper-Limb Movements Through sEMG Signal Processing
(Universidade Tecnológica Federal do Paraná (UTFPR), 2016)