Machine learning techniques for detecting motor imagery in upper limbs

Juan Sebastian Ramirez Archila, Alvaro David Orjuela-Canon

Resultado de la investigación: Capítulo en Libro/Reporte/ConferenciaContribución a la conferencia

Resumen

Nowadays, the human machine interfaces have increased the applications for improving the quality of life in injured people. In spite of the progress in the field, new strategies are important to contribute to solve new problems. This proposal shows the employing of feature extraction in time and frequency domains. Three machine learning techniques as KNN, SVM and Random Forest were used to detect motor imagery from EEG signals. Comparison for feature extraction and the employed detection models were analyzed to find the best election in an application for close-open fist in hands. The results achieved more than 90% in accuracy for both approaches, showing as the frequency domain is preferable for feature extraction and the employment of the KNN classifier as best strategy for the present demand.

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.
Páginas1-5
Número de páginas5
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

All Science Journal Classification (ASJC) codes

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

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