Quantitatively Recognizing Stimuli Intensity of Primary Taste Based on Surface Electromyography

A novel approach to quantitatively recognize the intensity of primary taste stimuli was explored based on surface electromyography (sEMG). We captured sEMG samples under stimuli of primary taste with different intensities and quantitatively recognized preprocessed samples with Support Vector Machine...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Hengyang Wang, Dongcheng Lu, Li Liu, Han Gao, Rumeng Wu, Yueling Zhou, Qing Ai, You Wang, Guang Li
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	primary taste taste stimuli intensity pattern recognition Support Vector Machine (SVM) brain-computer interface (BCI) surface electromyography (sEMG) Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/321c7c9cab164464bec1a6f9f1f1b057
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Sea el primero en dejar un comentario!

Quantitatively Recognizing Stimuli Intensity of Primary Taste Based on Surface Electromyography

Ejemplares similares