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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Bibliographic Details
Main Authors:	Hengyang Wang, Dongcheng Lu, Li Liu, Han Gao, Rumeng Wu, Yueling Zhou, Qing Ai, You Wang, Guang Li
Format:	article
Language:	EN
Published:	MDPI AG 2021
Subjects:	primary taste taste stimuli intensity pattern recognition Support Vector Machine (SVM) brain-computer interface (BCI) surface electromyography (sEMG) Chemical technology TP1-1185
Online Access:	https://doaj.org/article/321c7c9cab164464bec1a6f9f1f1b057
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Quantitatively Recognizing Stimuli Intensity of Primary Taste Based on Surface Electromyography

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