e-Prime: Advances in Electrical Engineering, Electronics and Energy (Dec 2023)
BCI-AMSH: A MATLAB based open-source brain computer interface assistive application for mental stress healing
Abstract
Numerous Brain computer interface (BCI) assistive software applications or toolboxes help to monitor the status of brain through Electroencephalogram (EEG); however, currently there is no application available to alleviate mental stress along with EEG analysis. In this paper, a new MATLAB-based assistive application called BCI-AMSH (Brain-Computer Interface-Assistive Mental Stress Healing) is developed. This application includes EEG signal offline analysis and stress healing techniques, such as guided meditation and singing bowl sound therapy, combined with real-time EEG analysis using the Enobio-8 device. The EEG offline analysis and stress healing modules are designed to be platform-independent.EEG offline analysis module offers signal preprocessing methods, diverse EEG signal analysis techniques, feature extraction methods, such as time and frequency domain analysis, and a range of machine learning and deep learning models for classification, various performance evaluation metrics. Additionally, it generates comprehensive EEG report about the user's mental states such as focus, relax and stress both in real-time and offline analysis. Furthermore, the stress healing module provides a variety of guided breathing practices and singing bowl sound therapy practices to effectively reduce stress levels. This new application is designed to be very simple and user-friendly, making it accessible to users without prior experience. Its potential applications are significant, particularly in the clinical industry for mental health purposes, as well as for novice researchers seeking to explore new possibilities in BCI.
