Abstract
Arthroplasty surgery is a common and successful end-stage intervention for advanced osteoarthritis. Yet, postoperative outcomes vary significantly among patients, leading to a plethora of measures and associated measurement approaches to monitor patient outcomes. Traditional approaches rely heavily on patient-reported outcome measures (PROMs), which are widely used, but often lack sensitivity to detect function changes (e.g. gait limitations) that may persist after surgery. Accessible measurement systems for objectively capturing functional outcomes have steadily emerged recently. Notably, wearable motion sensing and sensor-embedded prostheses offer high-resolution, real-time data on patient mobility, revealing discrepancies between PROMs and functional recovery trajectories. Coupled with advancements in mobile health platforms, opportunities for remote monitoring and remotely engaging arthroplasty patients is burgeoning. Smartphone applications have improved adherence to rehabilitation protocols, pain management, and patient satisfaction while enabling remote care and reducing healthcare utilization. However, barriers such as inconsistent protocols, the need for clinical validation, reliance on patient compliance with sensor use, small sample sizes, privacy concerns, cost and reimbursement challenges, and limited long-term data remain. Other emerging technologies are further enabling uptake, including but not limited to smart implants, in-home monitoring systems, and artificial intelligence (AI)/machine learning (ML)-enhanced analyses. Together, these technologies hold promise for more personalized, cost-effective strategies for comprehensive and patient-centered assessments that can inform tailored rehabilitation approaches, allow for near real-time assessment of patient outcomes, improve function, and promote earlier mobilization. Further research should focus on standardization and clinical validation, economic and environmental impact, and long-term efficacy to optimize their integration into routine clinical practice.