Comparative Study of Mental Stress Detection through Machine Learning Techniques

With the rapid development of human civilization, the capability of the human brain is also increasing with the fast pace of development which is eventually leading to mental health issues varying from young stage students to working professionals. Mental health is the least concerning issue in the life of today's generation when compared to physical health. One of the main concerns about which very few are aware is that mental problems can lead directly to several other physical problems and several terminal diseases. Such cases can affect a person's normal life adversely in various ways from affecting day-to-day routine, the standard of living, and relationship trauma. Early-stage detection is significantly important for the cause but gets delayed due to irresponsible handling or ignorance of the situation, where artificial intelligence can play a vital role. In today's era, everything can be predicted using complex mathematical calculations which can be promptly paced up when integrated with computer science and programming concepts. Numerous pieces of research are being done in the dimension of AI and machine learning approach for early-stage detection of issues related to mental health with optimized accuracy. This study presented an effective review of the previous study and concluded the summary of the implementation of AI for the early detection of mental health issues focusing on the dimension of AI and its subfields such as machine learning for early-stage detection of issues related to mental health with optimized accuracy. A nation like India is a great way to become a developed nation and implementing AI -based technology will accelerate the developing phase for overall sustainable development.