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Gamified platform for rehabilitation after total knee replacement surgery employing low cost and portable inertial measurement sensor node

Kontadakis Grigorios, Chasiouras Dimitrios, Proimaki Despoina, Halkiadakis Manolis, Fyntikaki Maria, Mania Aikaterini

Πλήρης Εγγραφή


URI: http://purl.tuc.gr/dl/dias/77F5BEE8-AEBC-4606-B778-76F104A825A9
Έτος 2020
Τύπος Δημοσίευση σε Περιοδικό με Κριτές
Άδεια Χρήσης
Λεπτομέρειες
Βιβλιογραφική Αναφορά G. Kontadakis, D. Chasiouras, D. Proimaki, M. Halkiadakis, M. Fyntikaki and K. Mania, "Gamified platform for rehabilitation after total knee replacement surgery employing low cost and portable inertial measurement sensor node," Multimed. Tools Appl., vol. 79, no. 5-6, pp. 3161-3188, Feb. 2020. doi: 10.1007/s11042-018-6572-6 https://doi.org/10.1007/s11042-018-6572-6
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Περίληψη

This paper 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. Initial testing of the system is conducted in the Hospital Orthopaedic Clinic, in collaboration with Orthopeadic Surgeons and Physiotherapists. 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. The aim is to increase patient engagement during physiotherapy by motivating the user to participate in a game. 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. The game projects a graphical image of the patient’s limb motion as part of a 3D computer graphics scene. It then classifies the exercise performed during physiotherapy as accurately performed or not and increases patient compliance via a reward system. 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, e.g. at home, indoors and outdoors by just utilizing a light sensor and an Android device. Initial testing of the application in the Chania’s General Hospital Orthopaedic Clinic, Greece, indicates that patient engagement is enhanced in most cases, even when elderly patients are concerned.

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