A Wearable Knee Brace System For Real-Time Gait Monitoring And Abnormality Detection

Musculoskeletal disorders affecting the knee joint account for approximately 40 % of all musculoskeletal conditions worldwide, significantly impairing mobility and increasing the risk of long-term disability. In order to identify and treat these conditions early, accurate and real-time gait analysis is essential. The wearable gait monitoring system presented in this paper uses an Inertial Measurement Unit (IMU) sensor to extract important gait metrics and assess leg direction. The IMU sensor delivers gyroscope and accelerometer data, which are processed to calculate cadence, step time, step width, stride length, and step length. The use of a flex sensor to record knee joint flexion improves the system’s capacity to evaluate gait dynamics. The ESP32 microcontroller, which powers the system, interprets unprocessed sensor data and sends them over Bluetooth to a Flutter-developed mobile application. The smartphone application provides an easy-to-use interface for tracking locomotion characteristics and visualizes real-time gait metrics. The system’s capacity to provide reliable and precise gait parameter estimations with low latency and steady wireless transmission is demonstrated via experimental validation. The suggested wearable solution provides a scalable, portable, and affordable gait analysis method in contrast to traditional motion capture methods. The accuracy of gait assessment is improved by combining IMU based orientation tracking with flex sensor data, which makes it appropriate for use in sports biomechanics, clinical diagnostics, and rehabilitation. For increased accuracy and versatility, future developments will incorporate machine learning algorithms and sensor fusion approaches.