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Wearable Monitoring Shows Sustained Increases in Daily Activity After Total Knee Arthroplasty, with a 6‑Month Recovery Window

MedXY Editorial Team•Nov 5, 2025•AI
Physical Activitypostoperative recoverytotal knee arthroplastywearable technology

Highlight

– Objective, continuous Apple Watch monitoring in 152 unilateral TKA patients detected significant increases in daily steps, standing hours and gait speed at 6 and 12 months postoperatively.

– Average daily step count rose from baseline to 5,293 ± 236 steps at 6 months (p < 0.001) and 5,180 ± 260 steps at 12 months (p < 0.001); gait speed improved from 0.88 ± 0.01 m/s pre-op to 1.01 ± 0.01 m/s at 12 months (p = 0.006).

– The data point to a clinically relevant recovery window around 6 months and illustrate the promise—and current limitations—of consumer wearables for longitudinal postoperative monitoring.

Background

Total knee arthroplasty (TKA) is a highly effective surgical intervention for end-stage knee osteoarthritis, with goals that include pain relief, restored function and improved participation in daily activities. Traditional assessment of recovery after TKA relies heavily on clinic-based performance measures (e.g., timed up-and-go, 6-minute walk test) and patient-reported outcome measures (PROMs). These approaches have important roles but are limited by episodic sampling, recall bias, clinic attendance barriers and the inability to characterize real-world activity patterns continuously.

Wearable consumer devices (smartwatches, fitness trackers) offer an opportunity to collect longitudinal, objective measures of mobility (e.g., step counts, standing time, gait speed estimates) in patients’ everyday environments. If reliable and interpretable, these data could provide earlier signals of recovery, identify patients who are off trajectory, and enable tailored rehabilitation. The study by Wu et al. provides one of the first prospective, longitudinal analyses using Apple Watch-derived metrics across preoperative, 6-week, 6-month and 12-month time points following unilateral TKA.

Study design

Population and setting

This was a prospective cohort study of 152 patients undergoing unilateral TKA. Participants were equipped with an Apple Watch and enrolled in a digital care management application that captured wearable-derived metrics via Apple HealthKit.

Data collection and endpoints

Primary objective metrics extracted from Apple HealthKit included daily step count, standing duration (hours standing per day), a steadiness metric, estimated gait speed, and an estimated 6-minute walk test (6MWT) value derived from the device. Data were collected at predefined time points: preoperative baseline, 6 weeks, 6 months and 12 months postoperatively.

Analysis

Descriptive statistics characterized cohort metrics over time. Paired t tests compared postoperative values to baseline. Analyses were performed in R. The study is presented as Level II evidence.

Key findings

The main outcomes reflect consistent improvements in objective mobility measures after TKA, with a notable inflection at 6 months.

Step count

Average daily step count increased substantially from preoperative baseline to postoperative follow-ups. The highest mean step count was observed at 6 months: 5,293 ± 236 steps/day (p < 0.001 versus baseline). At 12 months the mean remained elevated at 5,180 ± 260 steps/day (p < 0.001 versus baseline). The size of the step-count increase suggests a meaningful shift in ambulatory behavior for many participants, although absolute step counts remained below recommended thresholds for highly active adults.

Gait speed

Estimated gait speed rose from 0.88 ± 0.01 m/s preoperatively to 1.01 ± 0.01 m/s at 12 months (p = 0.006). This change crosses clinically relevant boundaries: gait speeds below ~1.0 m/s are associated with reduced community ambulation and poorer outcomes in older adults, so reaching ~1.0 m/s represents functional improvement for the cohort as a whole.

Standing time and steadiness

Standing hours increased from 9.99 ± 0.30 hours/day pre-op to 11.47 ± 0.31 hours/day at 6 months, with persistence at 12 months. Steadiness and the device-estimated 6MWT displayed recovery trends but with wider variability at 12 months, indicating heterogeneity in recovery trajectories across patients.

Temporal pattern — a critical 6‑month window

Metrics tended to show the greatest gains by 6 months, with maintenance rather than further large increases between 6 and 12 months. This suggests that the 6-month postoperative interval is a critical window for recovery and might represent an optimal time for targeted interventions to consolidate gains and address persistent deficits.

Safety and adverse events

The primary publication reports functional metrics only; it does not indicate device-related adverse events. Wearable monitoring itself is generally low-risk, but clinical decision-making based on such data warrants caution until device-derived metrics are validated against gold-standard measures and integrated with clinical context.

Expert commentary and interpretation

The study by Wu et al. advances the field by demonstrating feasibility and clinically interpretable signals from consumer wearables in a sizable, prospectively followed TKA cohort. Important strengths include the longitudinal design, objective continuous data capture, and clinically relevant endpoints (steps, gait speed, standing time). The clear trend to improved activity by 6 months aligns with conventional rehabilitation milestones and PROM improvements commonly reported after TKA.

Clinical significance versus statistical significance

Statistically significant increases in steps and gait speed are encouraging, but clinical interpretation requires context. For example, the mean 12-month gait speed of ~1.01 m/s is an important threshold improvement for community ambulation; however, mean step counts around 5,000/day reflect modest activity relative to public health targets (e.g., 7,000–10,000 steps/day often cited for general health). Individual-level variability is also considerable: some patients likely achieved step counts and gait speeds associated with high function, while others lagged.

Wearable data validity and limitations

Consumer devices like the Apple Watch use proprietary algorithms to estimate steps, gait speed and other metrics. While several validation studies have shown acceptable accuracy for step counting in healthy adults and in controlled conditions, performance can vary by walking speed, assistive device use, gait pattern and device placement. Device-derived estimates of gait speed and 6MWT are indirect and should be interpreted cautiously until validated in post-TKA populations. Missing data due to nonwear, device syncing issues, or limited battery life can bias results if nonwear correlates with poorer function.

Selection and generalizability

Participants willing to enroll in a digital care pathway and wear a smartwatch may differ from the broader TKA population (younger, more tech-literate, higher socioeconomic status). The cohort’s demographics and comorbidity profile (not detailed here) influence generalizability. Additionally, unilateral TKA patients were included; results may not apply to bilateral procedures or revision surgery.

Data stewardship and privacy

Widespread deployment of consumer wearables for clinical monitoring raises practical questions about data ownership, privacy, integration into electronic health records, and provider workflows. Systems for alerting clinicians about off-trajectory recovery must minimize false positives and not increase clinician burden unduly.

Clinical implications and recommended next steps

For clinicians and health systems considering wearable-based monitoring after TKA, this study suggests several actionable insights:

  • Wearable data can complement clinic-based assessments and PROMs by providing continuous, ecological measures of mobility.
  • Six months postoperatively appears to be a key milestone—patients not showing expected gains by this time may benefit from targeted interventions (physical therapy intensification, gait retraining, pain management review, fall-risk assessment).
  • Interpret device-derived metrics within clinical context; establish baseline preoperative measures and consider patient-specific goals.
  • Before scaling wearable monitoring, validate device estimates against gold-standard measures in representative TKA populations and develop protocols for data handling, clinician alerts and patient feedback.

Limitations of the study

Key limitations include reliance on a single consumer device platform (Apple Watch), potential selection bias, limited reporting of patient demographics and comorbidities in the summary, and lack of direct validation of device-derived gait speed and 6MWT against lab-based measures in this cohort. The study reports cohort averages; granular trajectory analyses stratified by age, BMI, baseline function, comorbidity, and rehabilitation adherence would strengthen interpretability.

Conclusion

Wu et al. provide compelling prospective evidence that consumer wearable monitoring captures meaningful improvements in daily physical activity after unilateral TKA, with gains peaking around 6 months and persisting at 12 months. These findings support the role of wearables as adjunctive tools for postoperative surveillance and rehabilitation planning. However, clinical deployment requires further validation of device algorithms in surgical populations, attention to equity and generalizability, and workflows that meaningfully integrate device data into patient care.

Funding and clinicaltrials.gov

The primary article should be consulted for details on funding sources and clinical trial registration. Readers are encouraged to reference the published manuscript for full disclosures.

References

Wu KA, Kugelman DN, Goel RK, Dilbone ES, Shenoy D, Ryan SP, Wellman SS, Bolognesi MP, Seyler TM. Wearable health technology finds improvements in daily physical activity levels following total knee arthroplasty: A prospective study. Knee Surg Sports Traumatol Arthrosc. 2025 Sep;33(9):3218-3227. doi: 10.1002/ksa.12675. Epub 2025 Apr 13. PMID: 40221914.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.

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