EMG and EEG signals integration in domotics
This article presents the integration of electromyographic (EMG) signals and a brain-computer interface (BCI) based on electroenecephalographic (EEG) signals in a domotic design for assistance. The EMG interface uses the myographic signal extracted from tibialis anterior in two sections: active musc...
| Autores: | , , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2022 |
| País: | México |
| Institución: | UNIVERSIDAD AUTÓNOMA DEL ESTADO DE HIDALGO |
| Repositorio: | PÄDI Boletín Científico de Ciencias Básicas e Ingeniería del ICBI |
| Idioma: | español |
| OAI Identifier: | oai:repository.uaeh.edu.mx:article/10140 |
| Acceso en línea: | https://repository.uaeh.edu.mx/revistas/index.php/icbi/article/view/10140 |
| Access Level: | acceso abierto |
| Palabra clave: | BCI EMG domotics steady state visul steady state visual evokated potential Interfaces BCI domótica potencial visual evocado en estado estable (SSVEP)) |
| Sumario: | This article presents the integration of electromyographic (EMG) signals and a brain-computer interface (BCI) based on electroenecephalographic (EEG) signals in a domotic design for assistance. The EMG interface uses the myographic signal extracted from tibialis anterior in two sections: active muscle and resting muscle. BCI uses the steady state visual evoked potential (SSVEP) generated as a response to blinking pictures in a display. A feature extraction method based on the Fast Fourier Transform (FFT) was used for off-line classification and the integration tests. |
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