Decoding Taste Information in Human Brain: A Temporal and Spatial Reconstruction Data Augmentation Method Coupled with Taste EEG

TL;DR

This paper presents a novel approach combining data augmentation and neural network techniques to accurately decode human taste perceptions from EEG signals, advancing objective taste evaluation methods.

Contribution

The study introduces TSRDA, a new data augmentation method, and a multi-view attention CNN for taste EEG analysis, improving decoding accuracy and objectivity.

Findings

Achieved 99.56% accuracy in taste EEG classification

Proved effectiveness of TSRDA in enhancing model training

Demonstrated potential for objective food taste evaluation

Abstract

For humans, taste is essential for perceiving food's nutrient content or harmful components. The current sensory evaluation of taste mainly relies on artificial sensory evaluation and electronic tongue, but the former has strong subjectivity and poor repeatability, and the latter is not flexible enough. This work proposed a strategy for acquiring and recognizing taste electroencephalogram (EEG), aiming to decode people's objective perception of taste through taste EEG. Firstly, according to the proposed experimental paradigm, the taste EEG of subjects under different taste stimulation was collected. Secondly, to avoid insufficient training of the model due to the small number of taste EEG samples, a Temporal and Spatial Reconstruction Data Augmentation (TSRDA) method was proposed, which effectively augmented the taste EEG by reconstructing the taste EEG's important features in temporal and spatial dimensions. Thirdly, a multi-view channel attention module was introduced into a designed convolutional neural network to extract the important features of the augmented taste EEG. The proposed method has accuracy of 99.56%, F1-score of 99.48%, and kappa of 99.38%, proving the method's ability to distinguish the taste EEG evoked by different taste stimuli successfully. In summary, combining TSRDA with taste EEG technology provides an objective and effective method for sensory evaluation of food taste.