The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Intelligent Mental Health Analyzer by Biofeedback: App and Analysis
|
|
Author(s): Rohit Rastogi (ABES Engineering College, Ghaziabad, India), Devendra Kumar Chaturvedi (Dayalbagh Educational Institute, Agra, India), Mayank Gupta (Tata Consultancy Services, Noida, India)and Parul Singhal (ABES Engineering College, Ghaziabad, India)
Copyright: 2020
Pages: 27
Source title:
Handbook of Research on Optimizing Healthcare Management Techniques
Source Author(s)/Editor(s): Nilmini Wickramasinghe (Swinburne University of Technology, Australia & Epworth HealthCare, Australia)
DOI: 10.4018/978-1-7998-1371-2.ch009
Purchase
|
Abstract
Many apps and analyzers based on machine learning have been designed to help and cure the stress issue. The chapter is based on an experimental research work that the authors 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 lives, so they planned to make an effort for reducing the stress level of people by their technical knowledge of computer science. In the chapter, they have a website that contains a closed set of questionnaires from SF-36, which have some weight associated with each question.
Related Content
|
.
© 2024.
27 pages.
|
|
.
© 2024.
10 pages.
|
|
.
© 2024.
13 pages.
|
|
.
© 2024.
6 pages.
|
|
.
© 2024.
23 pages.
|
|
.
© 2024.
14 pages.
|
|
.
© 2024.
7 pages.
|
|
|