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Open Access

Towards Rehabilitation at Home After Total Knee Replacement

Department of Electrical Engineering and Computer Science, Cleveland State University, Cleveland, OH 44115, USA
School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China
School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China
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Abstract

In this paper, we present the design and implementation of an avatar-based interactive system that facilitates rehabilitation for people who have received total knee replacement surgeries. The system empowers patients to carry out exercises prescribed by a clinician at the home settings more effectively. Our system helps improve accountability for both patients and clinicians. The primary sensing modality is the Microsoft Kinect sensor, which is a depth camera that comes with a Software Development Kit (SDK). The SDK provides access to 3-dimensional skeleton joint positions to software developers, which significantly reduces the challenges in developing accurate motion tracking systems, especially for use at home. However, the Kinect sensor is not well-equipped to track foot orientation and its subtle movements. To overcome this issue, we augment the system with a commercial off-the-shelf Inertial Measurement Unit (IMU). The two sensing modalities are integrated where the Kinect serves as the primary sensing modality and the IMU is used for exercises where Kinect fails to produce accurate measurement. In this pilot study, we experiment with four rehabilitation exercises, namely, quad set, side-lying hip abduction, straight raise leg, and ankle pump. The Kinect is used to assess the first three exercises, and the IMU is used to assess the ankle pump exercise.

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Tsinghua Science and Technology
Pages 791-799

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Cite this article:
Zhao W, Yang S, Luo X. Towards Rehabilitation at Home After Total Knee Replacement. Tsinghua Science and Technology, 2021, 26(6): 791-799. https://doi.org/10.26599/TST.2020.9010034

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Received: 08 August 2020
Accepted: 08 September 2020
Published: 09 June 2021
© The author(s) 2021.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).