Lower-limb kinematic reconstruction during pedaling tasks from EEG signals using Unscented Kalman filter.
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.
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