Convolutional neural network proposal for wrist position classification from electromyography signals

Alvaro D. Orjuela-Canon, Oscar J. Perdomo-Charry, Cesar H. Valencia-Nino, Leonardo Forero

Producción científica: Capítulo en Libro/ReporteCapítulo

Resumen

Commonly, electromyography (EMG) signals have been employed for movements or pattern classification. For this, different digital signals processing methods are applied to extract features, before a classification stage. The present work deals with a proposal based on the use of image classification employing deep learning techniques. The images were obtained from a spectrogram analysis as a previous process of the convolutional neural network employment. Then, a classification of five positions from wrist movements is carried out the model. Results showed that the accuracy is comparable to similar techniques employed with a shallow neural network and a deep neural network applied to the same dataset.

Idioma originalInglés estadounidense
Título de la publicación alojada2020 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2020 - Proceedings
EditoresAlvaro David Orjuela-Canon
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781728194066
DOI
EstadoPublicada - ago. 7 2020
Evento2020 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2020 - Virtual, Cali, Colombia
Duración: ago. 7 2020ago. 9 2020

Serie de la publicación

Nombre2020 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2020 - Proceedings

Conferencia

Conferencia2020 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2020
País/TerritorioColombia
CiudadVirtual, Cali
Período8/7/208/9/20

Áreas temáticas de ASJC Scopus

  • Inteligencia artificial
  • Informática aplicada
  • Visión artificial y reconocimiento de patrones
  • Teoría de la decisión (miscelánea)
  • Gestión y sistemas de información
  • Control y optimización

Huella

Profundice en los temas de investigación de 'Convolutional neural network proposal for wrist position classification from electromyography signals'. En conjunto forman una huella única.

Citar esto