Advances in algorithms developed with sensor data from smart phones demonstrates the capacity to passively collect qualitative gait metrics. The purpose of this feasibility study was to assess the recovery of these metrics following joint reconstruction. A secondary data analysis of an ethics approved global, multicenter, prospective longitudinal study evaluating gait quality data before and after primary total knee arthroplasty (TKA, n=476), partial knee arthroplasty (PKA, n=139), and total hip arthroplasty (THA, n=395). A minimum 24 week follow-up was required (mean 45±12, range 24 - 78). Gait bouts and gait quality metrics (walking speed, step length, timing asymmetry, and double support percentage) were collected from a standardized smartphone operating system. Pre- and post-operative values were compared using paired-samples t-tests (p<0.05). A total of 595 females and 415 males with a mean age of 61.9±9.3 years and mean BMI of 30.2±6.1 kg/m2 were reviewed. Walking speeds were lowest at post-operative week two (all, p<.001). Speeds exceeded pre-operative means consistently by week 21 (p=0.015) for PKA, and week 13 (p=0.007) for THA. The average weekly step length was lowest in post-operative week two (all, p<0.001). PKA and THA cases achieved pre-operative step lengths by week seven (p=0.064) and week 9 (p=0.081), respectively. The average weekly gait asymmetry peaked at week two post-operatively (all, p <0.001). Return to pre-operative baseline asymmetry was achieved by week 11 (p=0.371) for TKA, week six (p=0.541) for PKA, and week eight (p=.886) for THA. Double limb support percentages peaked at week two (all, p<0.001) and returned to pre-operative levels by week 24 (p=0.089) for TKA, week 12 (p=0.156) for PKA, and week 10 (p=0.143) for THA. Monitoring gait quality in real-world settings following joint reconstruction using smartphones is feasible, and may provide the advantage of removing the Hawthorne effect related to typical gait assessments and in-clinic observations.
The purpose of this study was to demonstrate the feasibility of passively collecting objective data from a commercially available smartphone-based care management platform (sbCMP) and robotic assisted total knee arthroplasty (raTKA). Secondary data analysis was performed using de-identified data from a commercial database that collected metrics from a sbCMP combined with intraoperative data collection from raTKA. Patients were included in this analysis if they underwent unilateral raTKA between July 2020 and February 2021, and were prescribed the sbCMP (n=131). The population consisted of 76 females and 55 males, with a mean age of 64 years (range, 43 – 81). Pre-operative through six-week post-operative data included step counts from the sbCMP, as well as administration of the KOOS JR. Intraoperative data included surgical times, the hip-knee-ankle angle (HKA), and medial and lateral laxity assessments from the robotic assessment. Data are presented using descriptive statistics. Comparisons were performed using a paired samples t-test, or Wilcoxon Signed-rank test, with significance assessed at p<0.05. A minimal detectable change (MDC) in the KOOS JR score was considered ½ standard deviation of the preoperative values.Introduction
Methods
The purpose of this study was to characterize the recovery of physical activity following knee arthroplasty by means of step counts and flight counts (flights of stairs) measured using a smartphone-based care platform. This is a secondary data analysis on the treatment cohort of a multicenter prospective trial evaluating the use of a smartphone-based care platform for primary total and unicondylar joint arthroplasty. Participants in the treatment arm that underwent primary total or unicondylar knee arthroplasty and had at least 3 months of follow-up were included (n=367). Participants were provided the app with an associated smart watch for measuring several different health measures including daily step and flight counts. These measures were monitored preoperatively, and the following postoperative intervals were selected for review: 2–4 days, 1 month, 1.5 month, 3 months and 6 months. The data are presented as mean, standard deviation, median, and interquartile range (IQR). Signed rank tests were used to assess the difference in average of daily step counts over time. As not all patients reported having multiple stairs at home, a separate analysis was also performed on average flights of stairs (n=214). A sub-study was performed to evaluate patients who returned to preoperative levels at 1.5 months (step count) and 3 months (flight count) using an independent samples T test or Fisher's Exact test was to compare demographics between patients that returned to preoperative levels and those that did not.Introduction
Methods
Recent advances in algorithms developed with passively collected sensor data from smart phones and watches demonstrate new, objective, metrics with the capacity to show qualitative gait characteristics. The purpose of this feasibility study was to assess the recovery of gait quality following primary total hip and knee arthroplasty collected using a smartphone-based care platform. A secondary data analysis of an IRB approved multicenter prospective trial evaluating the use of a smartphone-based care platform for primary total knee arthroplasty (TKA, n=88), unicondylar knee arthroplasty (UKA, n=28), and total hip arthroplasty (THA, n=82). Subjects were followed from 6 weeks preoperative to 24 weeks postoperative. The group was comprised of 117 females and 81 males with a mean age of 61.4 and BMI of 30.7. Signals were collected from the participants' smartphones. These signals were used to estimate gait quality according to walking speed, step length, and timing asymmetry. Post-operative measures were compared to preoperative baseline levels using a Signed-Rank test (p<0.05).Introduction
Methods
