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Biofeedback-Based Mental Health Software and Its Statistical Analysis
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Author(s): Rohit Rastogi (Dayalbagh Educational Institute, India & ABES Engineering College, Ghaziabad, India), Devendra Kumar Chaturvedi (Dayalbagh Educational Institute, India)and Sathiyamoorthi V. (Sona College of Technology, Salem, India)
Copyright: 2021
Pages: 20
Source title:
Challenges and Applications of Data Analytics in Social Perspectives
Source Author(s)/Editor(s): V. Sathiyamoorthi (Sona College of Technology, India)and Atilla Elci (Hasan Kalyoncu University, Turkey)
DOI: 10.4018/978-1-7998-2566-1.ch008
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Abstract
Many apps and analyzers based on machine learning have been designed already to help and cure the stress issue, which is increasing. The project is based on an experimental research work that the authors have performed at Research Labs and Scientific Spirituality Centers of Dev Sanskriti VishwaVidyalaya, Haridwar and Patanjali Research Foundations, Uttarakhand. In the research work, the correctness and accuracy have been studied and compared for two biofeedback devices named as electromyography (EMG) and galvanic skin response (GSR), which can operate in three modes, audio, visual and audio-visual, with the help of data set of tension type headache (TTH) patients. The authors have realized by their research work that these days people have lot of stress in their life so they planned to make an effort for reducing the stress level of people by their technical knowledge of computer science. In the project they have a website that contains a closed set of questionnaires from SF-36, which have some weight associated with each question.
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