International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 09 Issue: 06 | June 2022
p-ISSN: 2395-0072
www.irjet.net
Mental Health Assistant using LSTM Ms. Aiciri C Hegde1, Ms. Madhiraju Kavyasri2, Ms. Somalaraju Soumya3,Ms. Srinidhi M Sharma4, Prof. Manohar R5 Students, Department of Information Science and Engineering, Sir M Visvesvaraya Institute of Technology, Bangalore, Karnataka, India1,2,3,4 Faculty , Department Of Information Science and Engineering, Sir M Visvesvaraya Institute of Technology, Bangalore, Karnataka, India5 ---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - Mental health is defined as a condition of
well-being in which a person recognises his or her own skills, can manage with everyday challenges, can work effectively and can contribute to his or her network. As the number of people suffering from mental illnesses rises, it’s difficult to slow or stop the rate of rise in the number. Our project will engage with the user, gather data, analyse emotion and provide a solution with the use of LSTM and NLP. We first begin conversation with the user then evaluate the voice or text provided by the user and study the emotion. Key Words: Learning
Mental health, Voice Assistant, Machine
1. INTRODUCTION One of the most important and difficult fitness challenges in the actual world is the automatic identification of psychological disorders. People’s behaviour, thinking and emotion are all influenced by their overall mental wellness,as they engage with the environment. Moreover mental illnesses are on the rise greatly contributing to the overall disease load in 2015, it is estimated that 44% of the people( more than 332 million people) have experienced symptoms of despair. The condition according to a WHO research is a prevalent mood disorder that affects a great amount of people of all ages. There are various barriers to depression diagnosis and therapy along with a paucity of specialists in the industry, societal shame and aside-fromthe-point mentality.
1.1 Motivation Acquiring psychiatric help has been proven to be useful in the treatment of a variety of health problems particularly inremote places where mental health facilities are already scarce. While technological advancements in the field of mental health received its share of challenges, there were many who supported online mental health treatments. Online therapy may not be everyones cup of tea but it has shown its effectiveness to the people who feel uncomfortable attending the traditional face-to-face support groups.
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Some people show hesitation in sharing their personal sorrows or problems with other people because of the risk of other people judging them or them getting mocked by other people. So, in such cases online webpages or dialogue systems can be used to get the normal informative needs of the user by acting as a friend or a well-wisher.
1.2 Problem Statement In the present world of AI and data science, everybody is searching for the kind of system which is interactive. Often within the health facility, there may be a loss of human assets to attend to the patients. So, by means of considering all these things we have decided our problem definition as follows: To create a friendly webpage and integrate it with a voice assistant. 2. RELATED WORK A. “A Proposal for Virtual Mental Health Assistant”[1]Psychological health has been one of the most overlooked and yet most crucial components of our entire well-being in recent years. Due to cost, time, and space restrictions, as well as a scarcity of resources connected to in-person counselling, this study presents a system for a virtual mental wellbeing assistant. Disturbed mental health is frequently the result of a snowball effect that develops over time and demands constant attention and purposeful attempts to improve. With the support of a virtual mental health assistant, this is achievable. A conversation function, psychological evaluation, an emotion recognition module, and a suggestion system for enhancing the user's mood will all be included in the proposed assistant. For sentiment analysis, we employed a Naive Bayes classifier and Neural Networks. B. “UpBeat – Your Mental Health Assistant using Rasa NLU”[2]In Recent years Textual conversational agent or chatbots have gained tremendous attention. In today’s world,
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