AI can bring a paradigm shift in mental healthcare In India
By Dr. Puneet Agarwal – Vice Chairman and Professor of Department of Neurology, MAX Super Speciality Hospital and Founder and Chairman, NeuroDX
India is facing a growing mental health crisis, which affects individuals, workplace and families and economy as a whole. The country has a mental health need for 150-200 million people who are yet to be treated, and there is only 1 neurologist for 5 lakh patients on an average. The gap is more evident for people in rural India, where more than 65% of the population resides.
Depressions, different forms of anxiety, phobias, obsessive-compulsive disorder (OCD), substance use disorders, bipolar and mood disorders, autism spectrum disorder, post-traumatic stress disorder, and other mental health issues have been affecting our citizens for years. Added with urban stress, academic pressure, job insecurity, and social expectations contribute significantly to rising anxiety levels in today’s world. With rising life expectancy, cognitive disorders are increasing, especially in urban areas.
This crisis deepens when individuals resort to extreme measures such as suicide and self-harm. In 2023, around 1.72 suicide cases have been reported in India. Alarmingly, millennials and younger generations are increasingly vulnerable, as mounting academic and workplace stress, financial instability, substance abuse, social isolation, and relationship challenges compound their emotional distress. The convergence of these pressures, often amplified by digital exposure and reduced social support systems, is pushing many young people toward severe mental health struggles.
Thus, there is an ardent need to find a solution to reduce the mental health crisis gap and promote mental well-being amongst Indians. What is more important is that the solutions, should not be concentrated only in the urban centres, but need decentralization, specially to the rural pockets.
While technology and AI are being implemented across industries for faster business turnarounds, there is a need for the use of artificial intelligence in neurotechnology. And there is a beginning. Artificial Intelligence (AI) is transforming how Electroencephalography (EEG) data is analyzed, interpreted, and applied in clinical and research settings. Since EEG produces large volumes of complex brain-wave data, AI is helping detect more and more patterns, in a faster and more accurately than traditional manual interpretation.
EEG analysis is increasingly emerging as a powerful tool because it offers objective physiological data. Correlations have been found between, alpha wave anomalies and anxiety disorders, and theta wave anomalies and depression, often related to disrupted emotional regulation and cognitive processing. Preliminary research indicates that AI-assisted EEG analysis can offer diagnostic accuracy of over 85-90% in a controlled environment, in contrast to less reliable symptom-based diagnosis.
One of the most important potential advantages of these technologies is the improvement of accessibility. Advances in portable EEG technology are now available at significantly lower costs which means that screenings can be done outside of tertiary care centres, community health centres, schools, and even rural health clinics. With the development of telemedicine infrastructure and mobile networks, the neurological information can also be centrally analysed while the patient. Pilot is in the comfort of their homes. This opens the possibility for primary care physicians and MBBS practitioners in rural settings to conduct preliminary screenings, initiate first-line management, and refer patients to neurologists or psychiatrists when necessary. Such a model could significantly reduce delays in diagnosis and treatment, which are currently a major barrier in mental healthcare delivery.
In addition to diagnosis, neuro-AI applications can help in early detection and prevention of many mental healthcare issues. By pointing out minute neural indicators linked to stress, burnout, and mood disorders, these applications can help in early intervention for high-risk groups like students, frontline workers, and industrial employees. And early intervention is mission critical for better medical care and quicker recovery.
The mental health crisis in India is a complex issue that has been deeply embedded in the country’s social and economic fabric. Neuro-AI signals a fundamental shift in how India can approach mental healthcare: from reactive to preventive, from subjective to data-driven, and from urban-centric to truly inclusive. With the rise of mental health issues in India, a better diagnostic care can democratize brain health screening, reduce delays in treatment, intervene before the issues get worse and lead to more accurate treatment. We still live in a country, where mental health is yet not openly talked out, it is often related to social stigma and millions continue to suffer in silence. An objective, scalable, and accessible neurotechnology can become a powerful equalizer.
If supported by robust policy frameworks, ethical safeguards, and public-private collaboration, Neuro-AI could help transform mental healthcare from a privilege of access into a basic right, which in essence is the right of every citizen.