Human stress classification using EEG signals in response to music tracks

• Published in: Computers in biology and medicine Vol. 107; pp. 182 - 196
• Main Authors: Asif, Anum, Majid, Muhammad, Anwar, Syed Muhammad
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 01.04.2019; Elsevier Limited
• Subjects: Accuracy; Algorithms; Anxiety; Brain; Cardiovascular disease; Classification; Classifiers; EEG; Electroencephalography; Electroencephalography (EEG); Emotions; Feature extraction; Females; Genre; Heart rate; Human stress; Irritable bowel syndrome; Language; Listening; Males; Multilayer perceptrons; Music; Nervous system; Optimization; Phase lag; Physiology; Psychological stress; Questionnaires; Rap music; Regression analysis; Researchers; Respiration; Signal classification; State trait anxiety inventory (STAI); Variance analysis; Feature extraction; Human stress; State trait anxiety inventory (STAI); Electroencephalography (EEG); Music; Classification

Stress is inevitably experienced by almost every person at some stage of their life. A reliable and accurate measurement of stress can give an estimate of an individual's stress burden. It is necessary to take essential steps to relieve the burden and regain control for better health. Listening...