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A novel spatial feature for the identification of motor tasks using high-density electromyography

Autor
Jordanic, M.; Rojas, M.; Mañanas, M.A.; Alonso, J.F.; Marateb, H.R.
Tipus d'activitat
Article en revista
Revista
Sensors
Data de publicació
2017-07-08
Volum
17(7)
Número
1597
Pàgina inicial
1
Pàgina final
24
DOI
https://doi.org/10.3390/s17071597 Obrir en finestra nova
Projecte finançador
Diseño de métodos para la evaluación de procesos de deterioro neurológico y neuromuscular asociados al envejecimiento
Repositori
http://hdl.handle.net/2117/111932 Obrir en finestra nova
URL
http://www.mdpi.com/1424-8220/17/7/1597 Obrir en finestra nova
Resum
Estimation of neuromuscular intention using electromyography (EMG) and pattern recognition is still an open problem. One of the reasons is that the pattern-recognition approach is greatly influenced by temporal changes in electromyograms caused by the variations in the conductivity of the skin and/or electrodes, or physiological changes such as muscle fatigue. This paper proposes novel features for task identification extracted from the high-density electromyographic signal (HD-EMG) by applying ...
Citació
Jordanic, M., Rojas, M., Mañanas, M.A., Alonso, J.F., Marateb, H.R. A novel spatial feature for the identification of motor tasks using high-density electromyography. "Sensors", 8 Juliol 2017, vol. 17(7), núm. 1597, p. 1-24.
Paraules clau
high-density electromyography, mean shift, myoelectric control, pattern recognition, prosthetics
Grup de recerca
BIOART - BIOsignal Analysis for Rehabilitation and Therapy
CREB - Centre de Recerca en Enginyeria Biomedica

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