Quantitatively Recognizing Stimuli Intensity of Primary Taste Based on Surface Electromyography

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...

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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
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https://doaj.org/article/321c7c9cab164464bec1a6f9f1f1b057

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