A Smart Biomedical Healthcare System to Detect Stress using Internet of Medical Things, Machine Learning and Artificial Intelligence
Keywords:
Stress, AI, mental health, IoMT, biomedical, MLAbstract
Stress is a widespread issue in today's fast-paced world, affecting millions of individuals globally. Although stress can have adverse impacts on physical and mental health, identifying and managing it in real-time can be challenging. Advanced technologies such as Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Medical Things (IoMT) have the potential to revolutionize the way we live and work and address this challenge. A recent study, "A Smart Biomedical Healthcare System to Detect Stress using IoT, Machine Learning and Artificial Intelligence," proposes a machine learning-based approach coupled with IoMT to detect stress in individuals using physiological sensors such as heart rate, temperature, and moisture (sweat) sensors, as well as facial expressions. The proposed method can monitor and classify individuals into "stressful" or "non-stressful" situations. Our classification findings show that our method is a better one for identifying stress in real time. The prototype's primary aim is to introduce an innovative approach to detecting initial stress in workplace, educational, and organizational settings to promote the well-being of staff members, students, and others, ultimately enhancing productivity.
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