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Updated: Jul 9, 2025

A Single-Channel and Non-Invasive Wearable Brain-Computer Interface for Industry and Healthcare
Published on: July 7, 2023
A novel wearable ERP-based BCI approach to explicate hunger necessity
Egehan Çetin1, Süleyman Bilgin2, Gürkan Bilgin3
1Distance Education Application and Research Center, Burdur Mehmet Akif Ersoy University, Burdur, Turkey.
Abstract:
This study aimed to design a Brain-Computer Interface system to detect people's hunger status. EEG signals were recorded in various scenarios to create a database. We extracted the time-domain and frequency-domain features from these signals and applied them to the inputs of various Machine Learning algorithms. We compared the classification performances and reached the best-performing algorithm. The highest success score of 97.62% was achieved using the Multilayer Perceptron Neural Network algorithm in Event-Related Potential analysis.
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