An IoT-Based Automated Music Therapy System for Stress Management: Design and Implementation

Modern lifestyles often lead to considerable mental stress, adversely impacting daily human life. These stresses cause physiological changes, such as increased heart rate and blood pressure, leading to potential health issues. Commonly recommended stress-relief strategies, like medication, can yield harmful side effects and further health disorders. To address this, we propose an innovative solution: music therapy. It has been proven to decrease stress by calming the individual and regulating brainwave activity. While some hospitals manually apply this therapy, our model automates the process using Internet of Things (IoT) technology. This model employs IoT to seamlessly deliver data to the cloud, utilizing Raspberry
$\text{Pi}$
. We measure stress parameters using a pulse sensor and an electroencephalogram (EEG). Artificial neural networks (ANN) in the cloud then compare these measured values with pre-established threshold values. When a patient's pulse rate drops below the threshold, an emergency message is automatically dispatched to the physician. Furthermore, based on the patient's heart rate, the ANN categorizes the patient's health condition and stress level. A playlist, specifically curated to the patient's mood, is then played to alleviate stress levels. By leveraging cloud storage, the individual's status can be accessed conveniently through the internet or a dedicated mobile app on the patient's smartphone. Therefore, our model offers an innovative, nonpharmaceutical solution to manage and alleviate stress in modern life.