Distinguishing between knee rehabilitation exercises using inertial measurement units

Jones, Phillip John; Woodgate, Samuel; Williams, David; Biggs, Paul; Nicholas, Kevin; Button, Kate; Corcoran, Padraig; Holt, Catherine Avril

doi:10.1016/j.joca.2018.02.745

Cited by 1 publication

(2 citation statements)

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“…According to a hospital's tracking report, some patients after TKR had knees that remained swollen or even deteriorated when the patients returned to the hospital for inpatient services [4]. Whether the surgical procedure was not performed properly and whether the patients lacked proper rehabilitation after returning home for recuperation are important clinical issues that concern orthopedists [6]. Therefore, in this paper, we propose an effective method that integrates a designed sensor device, an inertial measurement unit (IMU), and an Android smartphone for monitoring the progress of rehabilitation after TKR.…”

Section: Introductionmentioning

confidence: 99%

“…Kontadakis et al [11] introduced a gamified rehabilitation platform consisting of a mobile game and an IMU placed on a lower limb in order to capture its orientation in space in real-time for patients undergone TKR. Jones et al [6] attached IMUs on the lower limbs to objectively distinguish four rehabilitation exercises that were prescribed to osteoarthritis patients following TKR. Seel et al [12] used an IMU for joint axis and position identification, and for flexion/extension joint angle measurement.…”

Section: Introductionmentioning

confidence: 99%

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Monitoring and Assessment of Rehabilitation Progress on Range of Motion After Total Knee Replacement by Sensor-Based System

Huang

Liu

Hsu

et al. 2020

Sensors

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For total knee replacement (TKR) patients, rehabilitation after the surgery is key to regaining mobility. This study proposes a sensor-based system for effectively monitoring rehabilitation progress after TKR. The system comprises a hardware module consisting of the triaxial accelerometer and gyroscope, a microcontroller, and a Bluetooth module, and a software app for monitoring the motion of the knee joint. Three indices, namely the number of swings, the maximum knee flexion angle, and the duration of practice each time, were used as metrics to measure the knee rehabilitation progress. The proposed sensor device has advantages such as usability without spatiotemporal constraints and accuracy in monitoring the rehabilitation progress. The performance of the proposed system was compared with the measured range of motion of the Cybex isokinetic dynamometer (or Cybex) professional rehabilitation equipment, and the results revealed that the average absolute errors of the measured angles were between 1.65 • and 3.27 • for the TKR subjects, depending on the swing speed. Experimental results verified that the proposed system is effective and comparable with the professional equipment.

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Section: Introductionmentioning

confidence: 99%