Remote Patient Monitoring with Wearable Sensors Following Knee Arthroplasty

Scott M Bolam, Bruno Batinica, Ted C Yeung, Sebastian Weaver, Astrid Cantamessa, Teresa C Vanderboor, Shasha Yeung, Jacob T Munro, Justin W Fernandez, Thor F Besier, Andrew Paul Monk, Scott M Bolam, Bruno Batinica, Ted C Yeung, Sebastian Weaver, Astrid Cantamessa, Teresa C Vanderboor, Shasha Yeung, Jacob T Munro, Justin W Fernandez, Thor F Besier, Andrew Paul Monk

Abstract

(Background) Inertial Measurement Units (IMUs) provide a low-cost, portable solution to obtain functional measures similar to those captured with three-dimensional gait analysis, including spatiotemporal gait characteristics. The primary aim of this study was to determine the feasibility of a remote patient monitoring (RPM) workflow using ankle-worn IMUs measuring impact load, limb impact load asymmetry and knee range of motion in combination with patient-reported outcome measures. (Methods) A pilot cohort of 14 patients undergoing primary knee arthroplasty for osteoarthritis was prospectively enrolled. RPM in the community was performed weekly from 2 up to 6 weeks post-operatively using wearable IMUs. The following data were collected using IMUs: mobility (Bone Stimulus and cumulative impact load), impact load asymmetry and maximum knee flexion angle. In addition, scores from the Oxford Knee Score (OKS), EuroQol Five-dimension (EQ-5D) with EuroQol visual analogue scale (EQ-VAS) and 6 Minute Walk Test were collected. (Results) On average, the Bone Stimulus and cumulative impact load improved 52% (p = 0.002) and 371% (p = 0.035), compared to Post-Op Week 2. The impact load asymmetry value trended (p = 0.372) towards equal impact loading between the operative and non-operative limb. The mean maximum flexion angle achieved was 99.25° at Post-Operative Week 6, but this was not significantly different from pre-operative measurements (p = 0.1563). There were significant improvements in the mean EQ-5D (0.20; p = 0.047) and OKS (10.86; p < 0.001) scores both by 6 weeks after surgery, compared to pre-operative scores. (Conclusions) This pilot study demonstrates the feasibility of a reliable and low-maintenance workflow system to remotely monitor post-operative progress in knee arthroplasty patients. Preliminary data indicate IMU outputs relating to mobility, impact load asymmetry and range of motion can be obtained using commercially available IMU sensors. Further studies are required to directly correlate the IMU sensor outputs with patient outcomes to establish clinical significance.

Keywords: PROMs; inertial measurement unit (IMU); knee arthroplasty; remote monitoring; telemedicine; wearable sensor.

Conflict of interest statement

Thor Besier was a co-founder of IMeasureU and remains a consultant to VICON-IMeasureU (Vicon, Oxford, UK). The other authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Schematic representing our workflow for post-operative remote patient monitoring of patients following total knee arthroplasty using inertial measurement units (IMUs). Mobility and knee flexion range of motion (ROM) were taken at baseline and 6 weeks post-op. Patient-reported outcome measures (PROMs) were taken at each time point as well as at 12-weeks post-op.
Figure 2
Figure 2
Inertial measurement unit (Vicon Blue Trident sensor) strapped to the ankle of the patient (A), as worn during weekly remote home monitoring after outpatient rehabilitation clinics. An additional thigh-worn sensor (B) was taped to the distal thigh pre-operatively and at Post-Op Week 6 to determine maximum knee flexion ankle.
Figure 3
Figure 3
PROMs (OKS, EQ-5D Index Score and EQ-VAS) were recorded pre-operatively until Post-Op Week 12 presented as [left] mean (solid line) ± S.D (dotted line) and [right] all individual patient data represented by a different colour line. Data were analysed by one-way ANOVA with Tukey’s post-hoc analysis (p  <  0.05, comparison vs. Pre-Op Score [solid bar above] and p < 0.05, comparison vs. Post-op Week 2 Score [dashed bar above]).
Figure 4
Figure 4
IMU Outputs (Bone Stimulus, Impact Load and Impact Load Asymmetry) presented as [left] mean (solid line) ± S.D (dotted line) and [right] all individual patient data represented by a different colour line. Data were analysed by one-way ANOVA with Tukey’s post-hoc analysis (p < 0.05, comparison vs. Post-op Week 2 Score [dashed bar above]).
Figure 5
Figure 5
Individual data for Patient 1 and 2 with PROMs scores (OKS, dashed line) and IMU Outputs (Impact Load, solid line) over the post-operative period.
Figure 6
Figure 6
The distance walked over the 6 Minute Walk Test and Maximum Knee Flexion Angle (measured with IMU sensors) pre-operatively and at Post-Op Week 6. The mean (solid line) ± S.D. (dotted line) all individual patient data are presented.

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