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Background: Individuals with end‐stage knee osteoarthritis (OA) walk at a lower intensity (ie, slower step cadence) contributing to worse physical function. Previous literature reports daily step counts and sedentary time, with little information regarding stepping bouts or cadence. Determining relationships between daily higher stepping cadence duration and clinical outcomes can move the field toward optimal daily stepping prescription. Objective: To quantify daily physical activity patterns of individuals with end‐stage knee OA and determine the contribution of high stepping cadence to explain functional capacity variability. Design: Cross‐sectional analysis. Setting: Veterans Administration medical center. Participants: U.S. military veterans (n = 104; age: 67.1 years [7.2]; mean [SD]; male [89.3%]) with end‐stage knee OA were enrolled. Intervention: Not applicable. Main outcome measure: Functional capacity (6‐Minute Walk Test [6MWT]). Physical activity (activPAL wearable sensor; cadence and time sitting, standing, and stepping), pain (Western Ontario and McMaster Universities Osteoarthritis Index‐pain subscale) sociodemographic variables, and comorbidities (body mass index and Functional Comorbidity Index) are the main explanatory variables. Results: Participants' wake time was mainly sitting (11.0 h/day) in ≥60‐minute bouts (29.7% ± 12.7 of sitting time). Standing (3.4 hours/day) and stepping (1.4 h/day) primarily occurred in 0–5 minute bouts (standing: 87.7% ± 14.4 of standing time, stepping: 98.7% ± 12.7 of stepping time) and stepping cadence was predominantly incidental (1–19 spm; 52.9% ± 9.6 of total stepping time). Backward elimination model results indicated shorter medium‐to‐brisk cadence bout duration, older age, and higher pain significantly explained shorter 6MWT distance (AdjR2=0.24, p <.01). Conclusions: Individuals with knee OA spend most of their waking hours sitting, while standing and stepping occurs in short bouts at very low stepping cadence. Decreased time in high stepping cadence is associated with lower functional capacity. Future studies should explore if increasing the daily time spent in higher step cadence can improve functional capacity in this population. [ABSTRACT FROM AUTHOR]

People with lower-limb loss participate in less physical activity than able-bodied individuals, which increases the mortality risk and incidence of metabolic syndromes. This study evaluated the effect of lower-limb prosthesis osseointegration on physical activity, including daily steps and stepping cadence. Free-living walking activity was assessed from 14 patients scheduled to undergo prosthesis osseointegration at two time points (within 2 weeks prior to osseointegration surgery and 12-months following). Daily step count, stepping time, number of walking bouts, average step cadence per bout, maximum step cadence per bout, and time spent in bands of step cadence were compared before and after osseointegration. Twelve months after prosthesis osseointegration, participants increased daily steps, daily stepping time, average step cadence, and maximum cadence per walking bout compared to pre-osseointegration. Participants engaged in more daily steps, higher stepping cadence, and longer bouts at higher cadence one year following osseointegration compared to when using a socket prosthesis. As a novel intervention that is becoming more common, it is important to understand walking activity outcomes as these are critical for long-term health. People with lower-limb loss participate in less physical activity than able-bodied individuals, which increases the mortality risk and incidence of metabolic syndromes. Daily step count, walking bouts, and step cadence during free-living walking activity are promising measures to capture physical functional performance in patients with lower-limb amputation. This study shows that patients with osseointegrated prostheses increase their stepping activity, including daily steps, number of bouts, and stepping cadence compared to when using a socket prosthesis, which has positive implications on overall patient health. As a novel intervention that is becoming more common, it is important for clinicians, patients, and researchers to understand expectations for walking activity outcomes as a critical factor in long-term patient health after prosthesis osseointegration. [ABSTRACT FROM AUTHOR]

Purpose: Less physical activity has been associated with systemic biomarkers of cartilage breakdown after anterior cruciate ligament reconstruction (ACLR). However, previous research lacks analysis of deleterious cartilage compositional changes and objective physical activity after ACLR. The purpose of this study was to determine the association between physical activity quantified via accelerometer-based measures of daily steps and time in moderate-to-vigorous physical activity (MVPA), and T1rho magnetic resonance imaging (MRI) of the femoral articular cartilage, a marker of proteoglycan density in individuals with ACLR. Methods: Daily steps and MVPA were assessed over 7 d using an accelerometer worn on the hip in 26 individuals between 6 and 12 months after primary unilateral ACLR. Resting T1rho MRI was collected bilaterally, and T1rho MRI interlimb ratios (ILR: ACLR limb/contralateral limb) were calculated for lateral and medial femoral condyle regions of interest. We conducted univariate linear regression analyses to determine associations between T1rho MRI ILRs and daily steps and MVPA with and without controlling for sex. Results: Greater T1rho MRI ILR of the central lateral femoral condyle, indicative of less proteoglycan density in the ACLR limb, was associated with greater time in MVPA (R 2 = 0.178, P = 0.032). Sex-adjusted models showed significant interaction terms between daily steps and sex in the anterior (P = 0.025), central (P = 0.002), and posterior (P = 0.002) medial femoral condyle. Conclusions: Lesser physical activity may be a risk factor for maintaining cartilage health after ACLR; additionally, the relationship between physical activity and cartilage health may be different between males and females. [ABSTRACT FROM AUTHOR]

Background: Wearable physiological monitoring devices are promising tools for remote monitoring and early detection of potential health changes of interest. The widespread adoption of such an approach across communities and over long periods of time will require an automated data platform for collecting, processing, and analyzing relevant health information., Objective: In this study, we explore prospective monitoring of individual health through an automated data collection, metrics extraction, and health anomaly analysis pipeline in free-living conditions over a continuous monitoring period of several months with a focus on viral respiratory infections, such as influenza or COVID-19., Methods: A total of 59 participants provided smartwatch data and health symptom and illness reports daily over an 8-month window. Physiological and activity data from photoplethysmography sensors, including high-resolution interbeat interval (IBI) and step counts, were uploaded directly from Garmin Fenix 6 smartwatches and processed automatically in the cloud using a stand-alone, open-source analytical engine. Health risk scores were computed based on a deviation in heart rate and heart rate variability metrics from each individual's activity-matched baseline values, and scores exceeding a predefined threshold were checked for corresponding symptoms or illness reports. Conversely, reports of viral respiratory illnesses in health survey responses were also checked for corresponding changes in health risk scores to qualitatively assess the risk score as an indicator of acute respiratory health anomalies., Results: The median average percentage of sensor data provided per day indicating smartwatch wear compliance was 70%, and survey responses indicating health reporting compliance was 46%. A total of 29 elevated health risk scores were detected, of which 12 (41%) had concurrent survey data and indicated a health symptom or illness. A total of 21 influenza or COVID-19 illnesses were reported by study participants; 9 (43%) of these reports had concurrent smartwatch data, of which 6 (67%) had an increase in health risk score., Conclusions: We demonstrate a protocol for data collection, extraction of heart rate and heart rate variability metrics, and prospective analysis that is compatible with near real-time health assessment using wearable sensors for continuous monitoring. The modular platform for data collection and analysis allows for a choice of different wearable sensors and algorithms. Here, we demonstrate its implementation in the collection of high-fidelity IBI data from Garmin Fenix 6 smartwatches worn by individuals in free-living conditions, and the prospective, near real-time analysis of the data, culminating in the calculation of health risk scores. To our knowledge, this study demonstrates for the first time the feasibility of measuring high-resolution heart IBI and step count using smartwatches in near real time for respiratory illness detection over a long-term monitoring period in free-living conditions., (©Pooja Gaur, Dorota S Temple, Meghan Hegarty-Craver, Matthew D Boyce, Jonathan R Holt, Michael F Wenger, Edward A Preble, Randall P Eckhoff, Michelle S McCombs, Hope C Davis-Wilson, Howard J Walls, David E Dausch. Originally published in JMIR Formative Research (https://formative.jmir.org), 07.08.2024.)

Background: Individuals with end-stage knee osteoarthritis (OA) walk at a lower intensity (ie, slower step cadence) contributing to worse physical function. Previous literature reports daily step counts and sedentary time, with little information regarding stepping bouts or cadence. Determining relationships between daily higher stepping cadence duration and clinical outcomes can move the field toward optimal daily stepping prescription., Objective: To quantify daily physical activity patterns of individuals with end-stage knee OA and determine the contribution of high stepping cadence to explain functional capacity variability., Design: Cross-sectional analysis., Setting: Veterans Administration medical center., Participants: U.S. military veterans (n = 104; age: 67.1 years [7.2]; mean [SD]; male [89.3%]) with end-stage knee OA were enrolled., Intervention: Not applicable., Main Outcome Measure: Functional capacity (6-Minute Walk Test [6MWT]). Physical activity (activPAL wearable sensor; cadence and time sitting, standing, and stepping), pain (Western Ontario and McMaster Universities Osteoarthritis Index-pain subscale) sociodemographic variables, and comorbidities (body mass index and Functional Comorbidity Index) are the main explanatory variables., Results: Participants' wake time was mainly sitting (11.0 h/day) in ≥60-minute bouts (29.7% ± 12.7 of sitting time). Standing (3.4 hours/day) and stepping (1.4 h/day) primarily occurred in 0-5 minute bouts (standing: 87.7% ± 14.4 of standing time, stepping: 98.7% ± 12.7 of stepping time) and stepping cadence was predominantly incidental (1-19 spm; 52.9% ± 9.6 of total stepping time). Backward elimination model results indicated shorter medium-to-brisk cadence bout duration, older age, and higher pain significantly explained shorter 6MWT distance ( Adj R 2 =0.24, p < .01)., Conclusions: Individuals with knee OA spend most of their waking hours sitting, while standing and stepping occurs in short bouts at very low stepping cadence. Decreased time in high stepping cadence is associated with lower functional capacity. Future studies should explore if increasing the daily time spent in higher step cadence can improve functional capacity in this population., (© 2023 American Academy of Physical Medicine and Rehabilitation.)