• Janhavi V. Deshmukh
• Dr. V. B Kute sir
• Dr. Z. I Khan sir

Mental health challenges such as stress, emotional imbalance, and lifestyle irregularities are increasingly prevalent among students and working professionals worldwide. Recent advancements in artificial intelligence (AI) have enabled automated stress detection; however, most existing systems focus only on prediction without providing explainability or actionable behavioral guidance. This survey examines contemporary research in AI-driven mental health monitoring, covering physiological-signal analysis, text-based sentiment assessment, multimodal learning, and Human-centric AI frameworks. The review highlights significant limitations in current approaches, including limited interpretability, narrow data modalities, absence of personalized routine recommendations, and minimal long-term behavioral insights. Based on these gaps, the survey emphasizes the need for integrated, explainable, and user-centric mental-health systems capable of offering both stress detection and preventive lifestyle guidance. The findings aim to support future development of holistic mental-health assistants that combine Human-centric AI, routine optimization, and proactive intervention strategies. Keywords - Mental health monitoring, Stress detection, Human-centric AI, SHAP, Machine learning, Behavioral analytics, Routine optimization, Personalized recommendations.

Mental health monitoring, Stress detection, Human-centric AI

"A SURVEY ON AI-DRIVEN MENTAL HEALTH PREDICTION AND PERSONALIZED ROUTINE MANAGEMENT SYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.13, Issue 1, page no.f350-f356, January-2026, Available :http://www.jetir.org/papers/JETIR2601553.pdf

"A SURVEY ON AI-DRIVEN MENTAL HEALTH PREDICTION AND PERSONALIZED ROUTINE MANAGEMENT SYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.13, Issue 1, page no. ppf350-f356, January-2026, Available at : http://www.jetir.org/papers/JETIR2601553.pdf