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Lower-limb kinematic reconstruction during pedaling tasks from EEG signals using Unscented Kalman filter.
Blanco-Díaz, Cristian Felipe; Guerrero-Mendez, Cristian David; Delisle-Rodriguez, Denis; de Souza, Alberto Ferreira; Badue, Claudine; Bastos-Filho, Teodiano Freire.
Afiliação
  • Blanco-Díaz CF; Postgraduate Program in Electrical Engineering, Federal University of Espírito Santo (UFES), Vitória, Brazil.
  • Guerrero-Mendez CD; Postgraduate Program in Electrical Engineering, Federal University of Espírito Santo (UFES), Vitória, Brazil.
  • Delisle-Rodriguez D; Edmond and Lily Safra International Institute of Neurosciences, Macaíba, Brazil.
  • de Souza AF; Department of Informatics, Federal University of Espírito Santo (UFES), Vitória, Brazil.
  • Badue C; Department of Informatics, Federal University of Espírito Santo (UFES), Vitória, Brazil.
  • Bastos-Filho TF; Postgraduate Program in Electrical Engineering, Federal University of Espírito Santo (UFES), Vitória, Brazil.
Comput Methods Biomech Biomed Engin ; : 1-11, 2023 May 02.
Article em En | MEDLINE | ID: mdl-37129900
Kinematic reconstruction of lower-limb movements using electroencephalography (EEG) has been used in several rehabilitation systems. However, the nonlinear relationship between neural activity and limb movement may challenge decoders in real-time Brain-Computer Interface (BCI) applications. This paper proposes a nonlinear neural decoder using an Unscented Kalman Filter (UKF) to infer lower-limb kinematics from EEG signals during pedaling. The results demonstrated maximum decoding accuracy using slow cortical potentials in the delta band (0.1-4 Hz) of 0.33 for Pearson's r-value and 8 for the signal-to-noise ratio (SNR). This leaves an open door to the development of closed-loop EEG-based BCI systems for kinematic monitoring during pedaling rehabilitation tasks.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Comput Methods Biomech Biomed Engin Assunto da revista: ENGENHARIA BIOMEDICA / FISIOLOGIA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Brasil País de publicação: Reino Unido
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Comput Methods Biomech Biomed Engin Assunto da revista: ENGENHARIA BIOMEDICA / FISIOLOGIA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Brasil País de publicação: Reino Unido