Mental Health Through Biofeedback Is Important to Analyze: An App and Analysis

View Sample PDF

Author(s): Rohit Rastogi (ABES Engineering College, India), Devendra Kumar Chaturvedi (Dayalbagh Educational Institute, Agra, India)and Mayank Gupta (Tata Consultancy Services, India)
Copyright: 2021
Pages: 22
Source title: Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning
Source Author(s)/Editor(s): Geeta Rani (Manipal University Jaipur, India)and Pradeep Kumar Tiwari (Manipal University Jaipur, India)
DOI: 10.4018/978-1-7998-2742-9.ch020

Keywords: Knowledge Management and Library Science / Machine Learning / Medical Diagnosis and Practice / Medical Information Science Reference

Purchase

View Mental Health Through Biofeedback Is Important to Analyze: An App and Analysis on the publisher's website for pricing and purchasing information.

Abstract

Many apps and analyzers based on machine learning have been designed to help and cure the stress issue. This chapter is based on an experiment 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 used some data visualization techniques that EMG (electromyography) in audio mode is best among all other modes, and in this experiment, they have used a data set of SF-36 and successfully clustered them into three clusters (i.e., low, medium, and high) using K-means algorithm. After clustering, they used classification algorithm to classify a user (depending upon the sum of all the weights of questions he had answered) into one of these three class. They have also implemented various algorithms for classifications and compared their accuracy out of which decision tree algorithm has given the best accuracy.

The IRMA Community

Research IRM

Mental Health Through Biofeedback Is Important to Analyze: An App and Analysis

Purchase

Abstract

Related Content

IRMA Sponsors