IoT framework of telerehabilitation system with wearable sensors for diabetes mellitus patients

Abstract

Physical activity is commonly used as a treatment for diabetes patients, although its effectiveness in improving cognitive functions such as learning, thinking, remembering, and decision making is not clear. Regular exercise can gradually improve metabolic abnormalities associated with pre-diabetes and assist patients with type-2 diabetes (T2D) in managing their pharmacological treatment. The usage of mobile health (mHealth) as a tool to help diabetes patients with their diabetes self-management have been demonstrated in previous studies and it can lead to reductions in glycosylated hemoglobin (HbA1c) levels. Heart rate readings during physical activity is beneficial for healthcare professionals (HCP) to ensure appropriate intensity levels for their patients is achieved. Additionally, the list of the tailored physical activities is long, and it is quite challenging for the T2D patients to remember. Therefore, Tele-DM is proposed, consisting of a smartwatch and mobile application that enable remote physiotherapy sessions for T2D patients. The smartwatch transfers the heart rate data to Tele-DM through Google Fit database. The system provides tailored exercise programs to help patients reduce their weight and HbA1c levels. With the ability to facilitate two-way communication between HCP and T2D patients, the Tele-DM system is designed to enable an effective remote rehabilitation process.

A new framework to enhance healthcare monitoring using patient-centric predictive analysis

“…The open software foundation (OSF) produced two different kinds of identifiers: universally unique identifiers (UUIDs) and globally developed identifiers (GUIDs). Distributed computing environment (DCE) employs a technique called universally unique identifier (UUID), which does not rely on a single administrator [13].…”