An IoT-Based Emotion Analysis and Music Therapy

Music therapy is a mussic-engaged therapeutic approach that provides an alternative medicine treatment for patients affected by brain disorders, post-surgery trauma, cancer, and developmental disorders. The therapist plays music according to the change in physiological signals of the patient in the hospital. A method to play music in a patient's desired places would be more beneficial and convenient for such patients. The objective of this work is to propose a method to analyze the patient's emotions remotely by incorporating the Internet of Things solution via the information communication tool through which music therapy can be provided in a handheld device (mobile phone) maintained by the patient. This proposed method acquires the physiological signals of the patient, such as heart rate, electroencephalogram, and electrocardiogram, through asensor network. The acquired signals are transferred to the cloud server, where a machine learning algorithm is performed to analyze the patient's emotions. The outcome of a machine learning architecture from the cloud is transferred through the internet to the Android application on a patient's mobile phone. Accordingly, this internet-enabled mobile application searches music that is already predefined and saved for different emotions play the relevant music to enhance the patient's mood.