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Automated music therapy significantly reduces anxiety in elderly patients by monitoring health metrics, suggesting a new approach to mental health care.
The elderly are at a higher risk of developing depression, anxiety, and other mental illnesses due to their age, chronic diseases, financial dependencies and other factors. Access to mental health services is often limited due to high cost, a low number of psychologists/therapists, and social taboos. In this paper, we propose automating the emerging technique of 'music therapy' (MT) using the internet of things (IoT) to develop a novel solution 'IoT-MT'. IoT-MT has the potential to deal with psychological disorders in a convenient, quick, and cost-effective manner. The system is based on collecting body parameters (pulse rate, SPO2, and blood pressure) from the patient demonstrating anxiety levels and playing appropriate music on a handheld device if the received parameters are above a certain predefined threshold. An early version of the system prototype is developed along with the mobile app, and experiments were conducted at a general hospital in Karachi, Pakistan, with 500 patients and their corresponding cardiologists. It has been observed that the proposed MT system reduced the anxiety levels for the majority of the patients, as indicated by their pulse rate and blood pressure. Also, the anxiety detection of IoT-MT was found to be accurate when compared to the patients' self-assessment performed using the standard psychology tool, state-trait anxiety inventory (STAI).
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Siddiqui et al. (2025) studied this question.
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