Real-Time Mental Stress Monitoring Using Machine Learning On User Interaction Patterns

Rajalakshmi S; Mohana Priya N; Kalaiyarasi E; Varnikha Varshini S; Kalavathi S; Buvana J

doi:10.36948/ijfmr.2026.v08i03.77259

Real-Time Mental Stress Monitoring Using Machine Learning On User Interaction Patterns

Author(s)	Dr. Rajalakshmi S, Ms. Mohana Priya N, Ms. Kalaiyarasi E, Ms. Varnikha Varshini S, Dr. Kalavathi S, Ms. Buvana J
Country	India
Abstract	The detection of mental stress is becoming an essential function of modern Human Computer Interaction (HCI) systems due to its effects on user performance and mental well-being. This work introduces a novel real-time system to monitor mental stress by using machine learning techniques on non-invasive behavioral biometrics. The system collects data from user interaction through keyboard dynamics (typing speed and latency), mouse behavior (jitter and click frequency) and eye-tracking (using Eye Aspect Ratio, EAR, derived by using Media Pipe). We employ a Long Short-Term Memory (LSTM) model in order to capture the temporal patterns within the user's behaviour and the Isolation Forest algorithm for anomaly detection by identifying the discrepancies with the user's individual baseline pattern. A user-specific modelling approach with user-specific normalization is integrated into the system to adapt the model to the specific characteristics of each user. The proposed system employs an efficient SQLite lightweight database to store sessions and update the model accordingly. Our results show better performance based on F1-score and more resilience towards biased behavioral data than other approaches while keeping the low latency characteristics of the proposed system which make it a good candidate for real-time monitoring applications.
Keywords	Stress Monitoring, Behavioural Biometrics, Long Short-Term Memory (LSTM), Isolation Forest, Human-Computer Interaction, Real-Time Intervention.
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 8, Issue 3, May-June 2026
Published On	2026-05-23
DOI	https://doi.org/10.36948/ijfmr.2026.v08i03.77259

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Real-Time Mental Stress Monitoring Using Machine Learning On User Interaction Patterns

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