{"title":"UNWIND – A Mobile Application that Provides Emotional Support for Working Women","authors":"Priyanka Kugapriya, Mayuriya Manohara, Keerthiga Ranganathan, Dineshgaran Kanapathy, A. Gamage, Arshad Anzar","doi":"10.1109/ASIANCON55314.2022.9909084","DOIUrl":null,"url":null,"abstract":"Depression is a common phenomenon affecting more than 264 million people worldwide. It is one of the leading causes of disability and a major contributor to the overall global burden of disease. Around twice as many women are affected by mental illness compared to men. This situation has worsened during the pandemic. The need to balance both work life and personal life has put them under immense pressure. Even though the diagnosis of mental illness almost exclusively depends on doctor-patient communication, it has its own set of disadvantages such as patient denial, recall bias, subjective biases, time-consuming and inaccuracy and it is a long-term health problem that needs to be continuously monitored and managed. Considering this social problem, we have planned to develop an Emotional Support Mobile application UNWIND – using modern technological concepts of machine learning and artificial intelligence. Which focuses especially on working women and would include several functionalities: a Chabot to detect mental health status in real-time and to provide counseling, an internal activities tracker to find the correlation between changes in lifestyle and mental health, an improvement tracker of the user’s current mental state using facial recognition and also Recommendation system with the support group, which recommends the most suitable professional counselors to the user as per their preferences and enabling into the support group to provide with necessary treatments and consultation at greater accuracy.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"35 5","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASIANCON55314.2022.9909084","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 is a common phenomenon affecting more than 264 million people worldwide. It is one of the leading causes of disability and a major contributor to the overall global burden of disease. Around twice as many women are affected by mental illness compared to men. This situation has worsened during the pandemic. The need to balance both work life and personal life has put them under immense pressure. Even though the diagnosis of mental illness almost exclusively depends on doctor-patient communication, it has its own set of disadvantages such as patient denial, recall bias, subjective biases, time-consuming and inaccuracy and it is a long-term health problem that needs to be continuously monitored and managed. Considering this social problem, we have planned to develop an Emotional Support Mobile application UNWIND – using modern technological concepts of machine learning and artificial intelligence. Which focuses especially on working women and would include several functionalities: a Chabot to detect mental health status in real-time and to provide counseling, an internal activities tracker to find the correlation between changes in lifestyle and mental health, an improvement tracker of the user’s current mental state using facial recognition and also Recommendation system with the support group, which recommends the most suitable professional counselors to the user as per their preferences and enabling into the support group to provide with necessary treatments and consultation at greater accuracy.