Approximately 21% of the global population experiences hand and wrist problems due to various medical conditions, significantly impacting individuals’ quality of life and dexterity. One main cause of these issues is Distal Muscular Dystrophy, a genetic disorder that leads to the eventual weakening of hand muscles, reducing strength and control [1]. As the world’s demographic shifts towards an ageing population, the prevalence of Muscular Dystrophy and other geriatric diseases rises, requiring more effective physiotherapy solutions [2]. Current industry standard rehabilitation methods often rely on subjective assessments by physiotherapists, leading to a lack of objective medical products that can enhance patient recovery. In response to this gap, the proposed solution is an innovative rehabilitation glove equipped with integrated sensors and data-driven decision-making tools, aimed at improving the effectiveness of targeted rehabilitation and tracking disease progression [3]. The glove utilises Bluetooth for real-time data transmission and features Python-based software for data visualisation in graph form [4]. Key metrics such as grip strength, finger flexibility, and wrist range of motion are accurately measured using various sensors, including Force Sensitive Resistors (FSR), Flex Sensors, and an Inertial Measurement Unit (IMU). This comprehensive data collection provides valuable insights into hand and wrist functionality, empowering physiotherapists to create personalised treatment plans through an intuitive user interface. This glove has the potential to revolutionise rehabilitation, offering significant benefits for both physiotherapists and patients through enhanced monitoring capabilities.