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Surface Electromyography-Based Recognition of Electronic Taste Sensations

Authors :
Asif Ullah
Fengqi Zhang
Zhendong Song
You Wang
Shuo Zhao
Waqar Riaz
Guang Li
Source :
Biosensors, Vol 14, Iss 8, p 396 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

Taste sensation recognition is a core for taste-related queries. Most prior research has been devoted to recognizing the basic taste sensations using the Brain–Computer Interface (BCI), which includes EEG, MEG, EMG, and fMRI. This research aims to recognize electronic taste (E-Taste) sensations based on surface electromyography (sEMG). Silver electrodes with platinum plating of the E-Taste device were placed on the tongue’s tip to stimulate various tastes and flavors. In contrast, the electrodes of the sEMG were placed on facial muscles to collect the data. The dataset was organized and preprocessed, and a random forest classifier was applied, giving a five-fold accuracy of 70.43%. The random forest classifier was used on each participant dataset individually and in groups, providing the highest accuracy of 84.79% for a single participant. Moreover, various feature combinations were extracted and acquired 72.56% accuracy after extracting eight features. For a future perspective, this research offers guidance for electronic taste recognition based on sEMG.

Details

Language :
English
ISSN :
20796374
Volume :
14
Issue :
8
Database :
Directory of Open Access Journals
Journal :
Biosensors
Publication Type :
Academic Journal
Accession number :
edsdoj.8daa4faf3ed465c8b4905364a9bfd6b
Document Type :
article
Full Text :
https://doi.org/10.3390/bios14080396