Sability Assessment of Technologies for Remote Monitoring of Knee Osteoarthritis

Knee osteoarthritis (OA) is a prevalent degenerative joint disorder that significantly affects the elderly population, leading to chronic pain, joint stiffness, and limited mobility. Early diagnosis and continuous monitoring are essential for effective management and to delay disease progression. This project introduces an innovative, wearable system for the detection and management of knee osteoarthritis using a combination of Micro-Electro-Mechanical Systems (MEMS) sensors, force sensors, and a vibration motor. The MEMS sensor continuously tracks knee joint angles and motion to identify abnormal movement patterns typically associated with osteoarthritic degradation. Complementing this, the force sensor evaluates the pressure applied to the knee during movement, providing insights into load distribution and joint strain. A vibration motor is employed to deliver localized therapeutic stimulation to the surrounding muscles, aiding in pain relief and enhancing joint flexibility. The system is built on a microcontroller-based architecture that processes sensor data in real time. It is also designed with future scalability in mind, allowing integration with Internet of Things (IoT) modules for remote health monitoring and tele-rehabilitation. This solution offers a non-invasive, cost-effective, and user- friendly method to support both clinical assessments and home-based management strategies for individuals at risk of or suffering from knee osteoarthritis. By leveraging sensor fusion and intelligent feedback mechanisms, this approach promotes early intervention, encourages patient engagement, and improves overall quality of life.