Development of NLP-Integrated Intelligent Web System for E-Mental Health

Area of Science:

• Digital Health
• Mental Healthcare Technology
• Computer Science Applications

Background:

• The COVID-19 pandemic has amplified the need for accessible healthcare, particularly mental health services.
• Existing mental health support facilities are often inadequate, especially in remote areas.
• Societal stigma surrounding mental health treatment hinders individuals from seeking necessary care.

Purpose of the Study:

• To design and implement a comprehensive web-based mental health support system.
• To leverage technology, including AI and computer vision, to enhance remote mental healthcare accessibility.
• To provide a secure and user-friendly platform for mental health assessment and support.

Main Methods:

• Developed a web platform using React.js (frontend), Express.js (backend), and MongoDB (database).
• Integrated a Natural Language Processing (NLP)-based chatbot using a deep neural network (Python, NLTK, TensorFlow, Keras) for personality assessment.
• Implemented a video conferencing feature with emotion detection (computer vision, Haar Cascade, TensorFlow) and secure payment gateway.

Main Results:

• The developed web platform successfully integrates NLP chatbots and computer vision-powered video conferencing with emotion detection.
• Functionalities include user registration, peer-to-peer chat, professional video consultations, downloadable prescriptions, and secure payments.
• All implemented features were tested and confirmed to be functional.

Conclusions:

• The developed system offers a scalable solution to bridge the gap in mental health service accessibility.
• Remote mental health support systems can effectively mitigate challenges posed by geographical limitations and social stigma.
• The platform provides a vital resource for teenagers, youth, and the middle-aged population seeking mental health assistance.