Mental Health Assistant Using Machine-Learning

Many people suffer from psychological wellness issues like tension and stress. Obtaining proficient help is often hindered by shame and accessibility issues. This paper presents a unique solution: a mobile application based on machine learning for stress and anxiety management. The application uses a simple sign-in and a comprehensive questionnaire developed by experts to assess stress and anxiety levels. It includes ten questions with multiple responses to each question. The AI framework computes a score from 1 to 10, with higher scores indicating more trouble. The app provides personalized solutions based on evidence-based practices, including journaling, reflection, exercises, yoga, positive affirmations, sleep tracking, self-improvement guides, to-do lists, music, and podcast playlists. The frequency and intensity of activities adjust based on the user’s levels. The user-friendly interface includes tools for progress monitoring, activity logging, reminders, and content access. The paper discusses the development, assessment, and implementation of the app, emphasizing user perspectives and ethical values. It aims to enhance mental well-being and promote proactive mental healthcare, improving lives and advancing mental health intervention.