IoT-Enabled Wearable Prototype: Detecting Signs of Depression

Abstract

The emergence of the Internet of Things (IoT) offers new possibilities for mental health care, including remote monitoring and early detection of depressive symptoms. This paper presents the design and development of a smart monitoring system called "MindTrack"aimed at addressing the long-term treatment and monitoring challenges of depression. MindTrack is composed of smart wearable devices integrated with a real-time monitoring desktop application. It passively monitors patients' behavioral and physiological data, enabling an objective assessment of depressive symptoms. The proposed architecture combines Analog-to-Digital Converters (ADCs) and WiFi-HaLoW (IEEE 802.11ah) protocols for efficient data transmission, edge computing and cloud connectivity incorporation for storage and analysis, various sensor utilization in the perception layer to track the patient's well-being and includes a patient-oriented smart wearable device operating system (OS) and a desktop application for psychologists to monitor and aid in treatment planning. None of the existing studies utilized a comprehensive combination of sensors specifically tailored for monitoring patients with Major Depressive Disorder (MDD). Moreover, there's limited focus on efficient power resources and security risk management. Hence, this paper proposes Mindtrack as a reliable and usable solution for improving specialized mental health care and addressing the challenges associated with MDD treatment and monitoring.