Daniel Nixon , Viswanatha Vanjre Mallappa , Vishwanath Petli , Sangamesh HosgurMath , Shashi Kiran K
{"title":"A novel AI therapy for depression counseling using face emotion techniques","authors":"Daniel Nixon , Viswanatha Vanjre Mallappa , Vishwanath Petli , Sangamesh HosgurMath , Shashi Kiran K","doi":"10.1016/j.gltp.2022.03.008","DOIUrl":null,"url":null,"abstract":"<div><p>Depression or stress is faced by most of the population throughout the world for multiple reasons and at different stages of life. Due to present busy life cycle, humans get into stress in their daily life, which leads to depression on long term. Stress is faced in education activity, competitive / challenging tasks, work pressure, family consequences, different types of human relation management, health disorders, old age etc. In this paper, a novel Artificial Intelligence therapy for depression analysis is proposed. This research is helpful for Psychologist to conduct counselling for their patients. Machine learning based Face Emotion techniques are used to detect depression level in any patient. This model can be tested for any age / category of patient, who faces depression due to any kind of problem or different sequences of life. To train machine learning algorithm, fer2013 open-source dataset is used. The algorithm was well trained and experiment were conducted on different age people. The results of this proposed algorithm were able to analyze depression more effectively.</p></div>","PeriodicalId":100588,"journal":{"name":"Global Transitions Proceedings","volume":"3 1","pages":"Pages 190-194"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666285X22000139/pdfft?md5=13892ae04cab36618d8ccf6033f56890&pid=1-s2.0-S2666285X22000139-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Global Transitions Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666285X22000139","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Depression or stress is faced by most of the population throughout the world for multiple reasons and at different stages of life. Due to present busy life cycle, humans get into stress in their daily life, which leads to depression on long term. Stress is faced in education activity, competitive / challenging tasks, work pressure, family consequences, different types of human relation management, health disorders, old age etc. In this paper, a novel Artificial Intelligence therapy for depression analysis is proposed. This research is helpful for Psychologist to conduct counselling for their patients. Machine learning based Face Emotion techniques are used to detect depression level in any patient. This model can be tested for any age / category of patient, who faces depression due to any kind of problem or different sequences of life. To train machine learning algorithm, fer2013 open-source dataset is used. The algorithm was well trained and experiment were conducted on different age people. The results of this proposed algorithm were able to analyze depression more effectively.