PULSE - PERSONALIZED UNDERSTANDING, LEARNING AND WORKING STRESS EVALUATION
Received: 07 November 2025, Revised: 20 May 2026, Accepted: 22 May 2026, Date of Publication: 11 June 2026
DOI:
https://doi.org/10.20319/lijhls.2026.12.1028Keywords:
Affective Computing, E-Learning, Occupational Health, Work-Related Stress, Wearable SensorsAbstract
Work-related stress has become a pervasive challenge with significant social and economic implications. This paper presents PULSE, a holistic digital system designed for Personalized Understanding, Learning, and Working Stress Evaluation in modern workplaces. The proposed system integrates non-invasive wearable sensors, IoT devices, and affective computing techniques to continuously monitor physiological, behavioral, and environmental indicators of stress. Advanced machine learning algorithms analyze these multimodal data in real time to detect stress levels, while a personalized e-learning platform delivers adaptive interventions (such as mindfulness exercises and cognitive-behavioral strategies) to help individuals manage stress proactively. A gamified mobile application interfaces with users, providing feedback and motivation to engage in stress-reduction activities. The paper also outlines a pilot study plan in a real workplace environment to evaluate the system’s effectiveness. By combining accurate stress detection with tailored just-in-time support, PULSE aims to promote mental well-being and enhance productivity in the workplace.
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