The innovation of wearable devices is advancing rapidly. Activity monitors can be used to improve the total hip replacement (THR) patients’ recovery process and reduce costs. This systematic review assessed the body-worn accelerometers used in studies to enhance the rehabilitation process and monitor THR patients. Electronic databases such as Cochrane Database of Systematic Reviews library, CINAHL CompleteVR, Science Citation Index, and MedlineVR from January 2000 to January 2022 were searched. Due to inclusion criteria, fourteen eligible studies that utilised commercial wearable technology to monitor physical activity both before and after THR were identified. Their evidence quality was assessed with RoB 2.0 and ROBINS-I. This study demonstrates that wearable device technology might be feasible to predict, monitor, and detect physical activity following THR. They could be used as a motivational tool to increase patients’ mobility and enhance the recovery process. Also, wearable activity monitors could provide a better insight into the individual’s activity level in contrast to subjective self-reported questionnaires. However, they have some limitations, and further evidence is needed to establish this technology as the primary device in THR rehabilitation.
Purpose: The aim of this study was to critically examine the content of smartphone apps produced for patients undergoing total hip replacement and total knee replacement surgery. Materials and methods: A systematic search was conducted across the five most popular smartphone app stores: iTunes; Google Play; Windows Mobile; Blackberry App World; and Nokia Ovi. Apps were identified for screening if they: targeted total hip replacement or total knee replacement patients; were free of charge; and were in English. App quality assessment was conducted independently by three reviewers using the Mobile App Rating Scale. Results: 15 apps met the inclusion criteria. On the 5-point Mobile App Rating Scale, the mean overall app quality score was 3.1. Within the Mobile App Rating Scale, the “Aesthetics” subscale had the most inconsistency across all apps, generating the highest and lowest mean scores (4.7 and 1, respectively). The “functionality” subscale had the highest mean score (3.8) among the four subscales, and the “information” subscale had the lowest mean score (2.7). Conclusion: This study highlights that despite a wide range of apps currently available to total hip replacement and total knee replacement patients, there is significant variability in their quality. Future efforts should be made to develop apps in partnership with patients, to improve the content, interactivity and relevance of apps.
1 January 2018 in Journal of Rehabilitation and Assistive Technologies Engineering
Clinical teams are under increasing pressure to facilitate early hospital discharge for total hip replacement and total knee replacement patients following surgery. A wide variety of wearable devices are being marketed to assist with rehabilitation following surgery. A review of wearable devices was undertaken to assess the evidence supporting their efficacy in assisting rehabilitation following total hip replacement and total knee replacement. A search was conducted using the electronic databases including Medline, CINAHL, Cochrane, PsycARTICLES, and PubMed of studies from January 2000 to October 2017. Five studies met the eligibility criteria, and all used an accelerometer and a gyroscope for their technology. A review of the studies found very little evidence to support the efficacy of the technology, although they show that the use of the technology is feasible. Future work should establish which wearable technology is most valuable to patients, which ones improve patient outcomes, and the most economical model for deploying the technology.
Individuals have increasingly high expectations of return to activity following total hip replacement (THR) surgery. The current literature demonstrates marked improvements in pain following THR. However, there is limited evidence showing objective improvement in daily activity. This randomized pilot trial aimed to determine the effect of an intervention where outdoor walking distance is used as a goal to increase daily activity of older adults using a commercial activity monitor at 3 to 6 months post THR. Findings suggested that the participants in the intervention group had higher activity levels after THR, compared to those in the control group. The Cohen’s effect sizes were larger for the changes in the gait, Hip Disability and Osteoarthritis Outcome Score, and Psychosocial Impact of Assistive Devices Scale data in the intervention group in contrast to the control group. However, further research with a larger sample size is required to provide tangible evidence on the significance of the effect of the purposeful walk compared to step count.
The rapid advancement of artificial intelligence (AI)–driven diagnostics and wearable health technologies is transforming health care delivery by enabling real-time health monitoring and early disease detection. These innovations are catalyzing a shift toward personalized medicine, with interventions tailored to individual patient profiles with unprecedented precision. This paper examines the current National Institute for Health and Care Excellence (NICE) evidence standards framework (ESF) for digital health technologies (DHTs) and evaluates the challenges associated with integrating DHTs into existing health and care systems. A comprehensive review of the NICE ESF guidelines was conducted, alongside an evaluation of their applicability to emerging AI and wearable technologies. Key limitations and barriers were identified, with particular focus on the framework’s responsiveness to technologies that evolve through machine learning and real-world data integration. Our findings indicate that while the NICE ESF provides a structured approach for evaluating DHTs, it lacks the adaptability required for rapidly evolving innovations. The framework does not sufficiently incorporate real-world evidence or support continuous learning models, which are critical for the safe and effective deployment of AI-based diagnostics and wearables. To remain effective and relevant, the NICE ESF should transition to a dynamic, adaptive model co-designed with industry stakeholders. By embedding real-world evidence-based strategies and promoting transparency, efficiency, and collaborative innovation, the updated framework would better facilitate the integration of AI-driven diagnostics and wearables into health care systems, ultimately enhancing patient outcomes and optimizing health care delivery.