Medicine in Novel Technology and Devices (Sep 2021)

Is clinically measured knee range of motion after total knee arthroplasty ‘good enough?’: A feasibility study using wearable inertial measurement units to compare knee range of motion captured during physical therapy versus at home

  • Ryan M. Chapman,
  • Wayne E. Moschetti,
  • Douglas W. Van Citters

Journal volume & issue
Vol. 11
p. 100085

Abstract

Read online

Total knee arthroplasty is highly successful, in part due to range of motion (RoM) recovery. This is typically estimated goniometrically/visually by physical therapists (PTs) in the clinic, which is imprecise. Accordingly, a validated inertial measurement unit (IMU) method for capturing knee RoM was deployed assessing postoperative RoM both in and outside of the clinical setting. The study's objectives were to evaluate the feasibility of continuously capturing knee RoM pre-/post-op via IMUs, dividing data into PT/non-PT portions of each day, and comparing PT/non-PT metrics. We hypothesized IMU-based clinical knee RoM would differ from IMU-based knee RoM captured outside clinical settings. 10 patients (3 ​M, 69 ​± ​13 years) completed informed consent documents following ethics board approval. A validated IMU method captured long duration (8–12 ​h/day, ~50 days) knee RoM pre-/post-op. Post-op metrics were subdivided (PT versus non-PT). Clinical RoM and patient reported outcome measures were also captured. Compliance and clinical disruption were evaluated. ANOVA compared post-op PT and non-PT means and change scores. Maximum flexion during PT was less than outside PT. PT stance/swing RoM and activity level were greater than outside PT. No temporal variable differences were found PT versus non-PT. IMU RoM measurements capture richer information than clinical measures. Maximum PT flexion was likely less than non-PT due to the exercises completed (i.e. high passive RoM vs. low RoM gait). PT gait flexion likely exceed non-PT because of ‘white coat effects’ wherein patients are closely monitored clinically. This implies data captured clinically represents optimum performance whereas data captured non-clinically represents realistic performance.

Keywords