Abstract
The human brain is one of the most advanced, complex, and incredible machines which has continued to fascinate scientists, researchers, and scholars for hundreds of years. Many experiments and studies have been done on the human brain to understand its mechanism and how it works, yet we are not close to understanding its full potential. One way of studying the brain is to study the brain wave frequencies which are emitted by it. The brain emits five different types of waves namely, delta, theta, alpha, beta, and gamma. Studying these different waves can help in solving various psychological issues, and problems like anxiety, stress, and depression which every human faces at least once in their life, according to WHO depression will be the main cause of mental illness by 2030. This work aims to find the influence of different brain waves and their involvement in the case of depression. For this, we have used deep learning techniques and developed a supervised learning model called convolutional neural network (CNN) for the classification of signals from Major Depression Disorder (MDD) from the healthy control. The developed CNN is run in five brain waves, and we calculated the accuracy for performance evaluation of the developed model for each brain wave frequency. The best accuracy we get is 98.4% for the delta wave followed by 97.6% for the alpha wave and the beta wave giving the least accuracy of 72.83%.
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Acknowledgement
1. We acknowledge the National Supercomputing Mission (NSM) for providing computing resources of “PARAM Siddhi-AI” under the National PARAM Supercomputing Facility (NPSF), C-DAC, Pune, and supported by the Ministry of Electronics and Information Technology (MeitY) and Department of Science and Technology (DST), Government of India.
2. The author is extremely grateful to University Grants Committee (UGC) for providing the Junior Research Fellowship (JRF) under Maulana Azad National Fellowship for Minorities (MANFJRF), with the award reference number: NO.F.82-27/2019 (SA III).
3. We also acknowledge the Institute of Eminence (IoE) scheme at BHU for supporting us.
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Gosala, B., Gosala, E.R., Gupta, M. (2023). A Deep Learning Based Model to Study the Influence of Different Brain Wave Frequencies for the Disorder of Depression. In: Morusupalli, R., Dandibhotla, T.S., Atluri, V.V., Windridge, D., Lingras, P., Komati, V.R. (eds) Multi-disciplinary Trends in Artificial Intelligence. MIWAI 2023. Lecture Notes in Computer Science(), vol 14078. Springer, Cham. https://doi.org/10.1007/978-3-031-36402-0_42
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