Page 526 - Emerging Trends and Innovations in Web-Based Applications and Technologies

International Journal of Trend in Scientific Research and Development (IJTSRD)
Special Issue on Emerging Trends and Innovations in Web-Based Applications and Technologies
Available Online: www.ijtsrd.com e-ISSN: 2456 – 6470

MentalWell: An Innovative Smart System for Early
Detection and Management of Psychological Disorders

Mr. Lokesh Gakhre , Mr. Harshal Raut , Prof. Usha Kosarkar
1
2
3
1,2,3 Department of Science and Technology,
1,2,3 G H Raisoni College of Engineering and Management, Nagpur, Maharashtra, India

ABSTRACT Artificial Intelligence (AI) has emerged as a transformative
This research introduces MentalWell, an AI-driven system tool in mental healthcare, revolutionizing how psychological
designed to revolutionize early detection and management conditions are detected, monitored, and managed. AI
of psychological disorders during a global mental health techniques, including machine learning, natural language
crisis. It highlights AI's transformative potential in processing, and deep learning, enable the analysis of diverse,
addressing challenges such as timely diagnosis, high-dimensional datasets, uncovering patterns and offering
personalized treatment, and accessible care. Utilizing predictive insights for mental health interventions. These
advanced machine learning and natural language advancements extend to applications such as diagnosing
processing (NLP), MentalWell analyzes diverse data sources mood disorders, supporting emotional regulation, and
to identify mental health issues early and deliver tailored improving outcomes for conditions like schizophrenia,
interventions. autism, and neurodegenerative diseases.
The study critiques traditional mental health assessments, The integration of AI-powered systems, such as Autonomous
showcasing AI's ability to overcome barriers with real-time, Psychological Health Monitoring (APHM), offers unparalleled
scalable solutions. Ethical and privacy considerations are potential for real-time data analysis through multimodal
integral, ensuring algorithms remain culturally sensitive, sensing technologies, including smartphones, wearables, and
unbiased, and secure. Key features include sentiment chatbots. These systems facilitate early detection,
analysis and multimodal data integration for accurate personalized care, and continuous monitoring, ensuring
assessments and actionable insights. tailored support and improving therapeutic outcomes.
However, this transformative approach necessitates
A systematic methodology underpins the research, addressing challenges like ethical considerations, privacy
involving literature reviews, comparisons of existing AI concerns, and algorithmic fairness, ensuring culturally aware
models, and algorithm development. Applications include and unbiased implementations.
managing schizophrenia, autism, mood disorders, and
neurodegenerative conditions, as well as supporting This synthesis underscores the growing importance of
emotional regulation, online therapy, and treatment leveraging AI in mental healthcare to improve diagnostic
monitoring. Challenges like limited datasets, algorithmic accuracy, streamline clinical workflows, and provide
fairness, and clinical integration are addressed using accessible, cost-effective solutions for a global population. By
implementation science. uniting technological innovation with clinical expertise, AI is
poised to redefine mental health care, offering hope and
The study concludes by envisioning advancements in early
improved outcomes for individuals worldwide.
detection, multimodal technologies, and global clinical
adoption. MentalWell establishes itself as a pioneering AI II. RELATED WORK
solution, setting a transformative trajectory for mental The intersection of artificial intelligence (AI) and mental
health care. health has gained considerable attention in recent years,
with research focusing on utilizing advanced computational

KEYWORDS: MentalWell, artificial intelligence (AI), machine techniques to address critical challenges in psychological
learning and natural language processing (NLP), early care. Mental health issues, particularly mood disorders such
as depression and anxiety, present a significant challenge
detection, personalized treatment, sentiment analysis,
worldwide, especially among youth. Depression,
multimodal data, ethical considerations, privacy concerns,
characterized by emotional, cognitive, somatic, and
algorithmic fairness, online therapy platforms, emotional
behavioral symptoms, can lead to severe outcomes, including
regulation, neurodegenerative disorders, schizophrenia,
suicide, one of the leading causes of death among young
autism spectrum disorders, mood disorders
adults in World. The COVID-19 pandemic further
exacerbated these mental health challenges, with increased
I. INTRODUCTION
rates of depression and anxiety among young individuals.
Mental health conditions are a pervasive global challenge,
However, advancements in technology, such as wearable
impacting over 1 billion individuals annually and
devices, mobile applications, and artificial intelligence (AI)-
significantly contributing to the global disease burden. With
enabled solutions, offer new opportunities for early
an estimated 32.4% of years lived with disability attributed diagnosis, treatment, and monitoring of mental health
to mental illnesses, the gap in care is further exacerbated by
disorders.
a severe shortage of mental health professionals, worsened
by the COVID-19 pandemic. This crisis calls for innovative Technological Innovations in Mental Health Monitoring
solutions to bridge the care gap and improve accessibility. Ecological Momentary Assessment (EMA), facilitated by
smartphones, allows real-time tracking of an individual's
IJTSRD | Special Issue on Emerging Trends and Innovations in Web-Based Applications and Technologies Page 516