Validity of wearable sensors for total knee arthroplasty (TKA) rehabilitation: a study in younger and older healthy participants

L. Forsyth*, A. Ligeti, M. Blyth, J.V. Clarke, P.E. Riches

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)
8 Downloads (Pure)

Abstract

Background
With 100,000 total knee arthroplasty (TKA) procedures taking place in the United Kingdom annually, the demand on rehabilitation services is high. Most regimes are home-based. Without clinician-patient interaction, detection of rehabilitation concerns can be delayed, reducing the chance of successful early intervention. Wearable technologies, such as MotionSenseTM (Stryker, US), may offer a solution to this problem by remotely supporting post-operative TKA rehabilitation through the provision of personalised rehabilitation and tracking of home exercises, enabling healthcare professionals to continuously monitor rehabilitation progress remotely. Validation of such devices against a known kinematic model in activities of daily living is important for confident interpretation of resulting clinical data. The aim of this study therefore was to validate the accuracy of MotionSenseTM against a clinical motion capture standard.
Methods
Twenty younger and 14 older healthy, able-bodied adults attended one testing session (Younger: 24 ± 4 years old; Older: 71 ± 5 years old). Movement was tracked using Vicon motion analysis and a Plug-In-Gait lower body model was applied to all participants. Three activities were performed – walking, stair ascent, stair descent. The knee flexion angle root mean square error (RMSE) between the technologies was determined.
Results
For both groups the knee flexion RMSE remained below 3° for all activities. The combined RMSE for all adults was 2.4° for walking, 2.7° for stair ascent, and 2.6° for stair descent. The signed error increased during the swing phase of gait.
Conclusion
MotionSenseTM was found to accurately estimate knee flexion angles during several common activities compared to Vicon motion capture.
Original languageEnglish
Pages (from-to)292-302
Number of pages11
JournalThe Knee
Volume51
Early online date24 Oct 2024
DOIs
Publication statusPublished - 1 Dec 2024

Funding

This work was funded by Stryker.

Keywords

  • rehabilitation
  • wearable sensor
  • IMU
  • total knee arthroplasty
  • motion analysis
  • gait analysis

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