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Gamified 3D orthopaedic rehabilitation using low cost and portable inertial sensors

Kontadakis Grigorios

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Summary

This work introduces an innovative gamified rehabilitation platform comprising of a mobile game and a custom sensor placed on the knee, intended for patients that have undergone Total Knee Replacement surgery, in collaboration with the General Hospital in Chania. The application uses a single custom-made, light, portable and low-cost sensor node consisting of an Inertial Measurement Unit (IMU) attached on a lower limb in order to capture its orientation in space in real-time, while the patient is completing a physiotherapy protocol.An IMU measures and reports a body's specific force (accelerometer), angular rate (gyroscope), and sometimes the magnetic field surrounding the body (magnetometer). IMUs provide the leading technology used in wearable devices and are employed in this thesis as they meet the main design constraints of this framework, maximizing portability and minimizing cost. Previous work indicates that when multiple IMUs are employed, satisfactory rehabilitation exercise classification accuracy results are achieved based on three, two and one IMUs. Such results drive the further investigation of the challenging classification problem using just a single IMU in this thesis, enhancing maximum portability compared to multiple IMU systems, in conjunction with sufficiently high success rates of movement detection.Our goal is to reduce the need for the physical presence of a physiotherapist by aiding the efficient performance of exercise sessions at any location and increase patient engagement during physiotherapy by motivating the user to participate in a game using the current ultra-portable framework of just a single IMU sensor and an Android device. The proposed sensor node attached on the lower limb provides input to the gamified experience displayed on an Android mobile device, offering feedback to the patient in relation to whether the performed exercises were accurately conducted. A classification algorithm is proposed that automatically classifies an exercise in real-time as correct or incorrect, according to physiotherapists’ set criteria. Initial testing of the system is conducted in the Chania’s General Hospital Orthopaedic Clinic, Greece, in collaboration with Orthopaedic Surgeons and Physiotherapists. This testing indicates that patient engagement is enhanced in most cases.

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