Search Results (351)

This study investigates the link between changes in physical activity (PA) measured by wearable accelerometers and the worsening of knee osteoarthritis (KOA) symptoms over two years. Using data from 782 participants in the Osteoarthritis Initiative accelerometer sub-study, PA was tracked with hip-worn ActiGraphs. Participants were classified as “worsening” if their Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) total score increased by >10 points and as “stable” otherwise. PA was categorized into daily counts and minutes spent in various intensity levels, and analyzed in 3 h intervals across the day. Of the participants, 123 (15.7%) experienced worsening symptoms. At baseline, both groups had similar characteristics aside from slower sit-to-stand times in the worsening group. Over two years, the worsening group had a greater decline in total daily activity counts (−18% vs. −10%) and more significant reductions during late afternoon and evening (15:00–21:00; −21% vs. −6%). This group also showed a notable decrease in gait speed, longer sit-to-stand times, and a trend towards greater medial joint space narrowing. These findings suggest that larger declines in PA, especially in activities in the late afternoon and evening, are associated with worsening KOA symptoms, although causality cannot be established. Full article

Background/Objectives: Physical activity benefits women with metastatic breast cancer. Past trials are typically well-resourced and supervised, but home-based interventions may be preferable and more accessible. This pilot trial evaluated the feasibility and preliminary efficacy of a remotely delivered behaviour change intervention aiming to increase physical activity for women with metastatic breast cancer. Methods: A 12-week, two-arm trial involved 20 women with metastatic breast cancer randomised 1:1 to a generic recommendation group or behaviour change group. Both groups received a physical activity recommendation, Fitbit^® watch, diary, and nine phone/video call sessions. The behaviour change group received individualised advice around physical activity benefits, motivation, barriers, and social support; the generic recommendation group completed a recurring symptom questionnaire. Feasibility outcomes were recruitment, retention and adherence rates. Acceptability was evaluated with a structured interview at trial completion. Preliminary efficacy outcomes included 5-day Actigraph wear, 6 min walk distance, 30 s sit-to-stands, and questionnaires for self-reported physical activity, quality-of-life, fatigue, behavioural factors, and patient-specific function. Results: Recruitment, retention, and adherence rates were 63% (n = 20/32), 80% (n = 16/20), and 76% (137/180 sessions), respectively. Participants across both groups reported that participation was acceptable, and their behaviour change was perceived as sustainable. Preliminary change scores for efficacy measures favoured the behaviour change group, except some quality-of-life and behavioural factor subscales. Conclusions: Participants were receptive to the trial, and feasibility and efficacy measures were positive. This indicates that a behaviour change intervention for unsupervised physical activity is acceptable and can be beneficial to women with metastatic breast cancer, warranting further exploration. Full article

Actigraphy quantifies human locomotor activity by measuring wrist acceleration via wearable devices at relatively high rates and converting it into lower-temporal-resolution activity values; however, the computational implementations of this data compression differ substantially across manufacturers. Building on our previous work comparing activity determination methods, we have investigated how they (e.g., digital filtering and data compression) influence nonparametric circadian rhythm analysis and sleep–wake scoring. In addition to our generalized actigraphic framework, we have also emulated the use of specific devices commonly employed in such sleep-related studies by applying their methods to raw actigraphic acceleration data we collected to demonstrate, through concrete real-life examples, how methodological choices may shape analytical outcomes. Additionally, we assessed whether nonparametric indicators could be derived directly from acceleration data without compressing them into activity values. Overall, our analysis revealed that all these analytical approaches to the sleep–wake cycle can be substantially affected by the manufacturer-dependent actigraphic methodology employed, with the observed effects traceable to distinct steps of the signal-processing pipeline, underscoring the necessity of cross-manufacturer harmonization from a clinically oriented perspective. Full article

Consumer wearables are increasingly used in physical activity (PA) interventions, but their validity as a measurement tool among low PA groups, like adolescent girls, is unclear. We assessed the minute- and day-level agreement between PA measures among adolescent Latinas from an intervention. Participants wore a Fitbit Inspire HR and an ActiGraph GT3X+ for overlapping epochs. ActiGraph data were classified using two different cut points and aligned with Fitbit data to produce 1,149,169 matched minutes of wear across 137 adolescent girls (M = 15.73 yrs). Confusion matrices were calculated for pairwise comparisons to determine minute-level Moderate-Vigorous PA (MVPA) classification. Data were aggregated to 1007 days for Bland–Altman analyses. ActiGraph cut points showed moderate agreement for minute-level MVPA classification (Balanced Accuracy = 0.71, AC1 = 0.98), while Fitbit showed fair agreement (Balanced Accuracy = 0.50, AC1 = 0.95–0.97) largely driven by non-MVPA observations. The Freedson cut point overestimated daily MVPA relative to Treuth by 14.7 min/day and Fitbit by 14.2 min/day in Bland–Altman space. The daily Treuth and Fitbit comparison did not significantly differ. Findings suggest systematic differences between cut points that warrant further consideration. Fitbit showed moderate agreement with ActiGraph, but heteroscedasticity and the epoch of aggregation significantly impacted agreement. Understanding device differences has implications for promoting/researching public health among adolescents. Full article

Sleep is a fundamental biological process essential for health and homeostasis. Traditionally investigated through laboratory-based polysomnography (PSG), sleep research has undergone a paradigm shift with the advent of wearable technologies that enable non-invasive, long-term, and real-world monitoring. This review traces the evolution from early analog and actigraphic methods to current multi-sensor and AI-driven wearable systems. We summarize major technological milestones, including the transition from movement-based to physiological and biochemical sensing, and the growing role of edge computing and deep learning in automated sleep staging. Comparative studies with PSG are discussed, alongside the strengths and limitations of emerging devices such as wristbands, rings, headbands, and camera-based systems. The clinical applications of wearable sleep monitors are examined in relation to remote patient management, personalized medicine, and large-scale population research. Finally, we outline future directions toward integrating multimodal biosensing, transparent algorithms, and standardized validation frameworks. By bridging laboratory precision with ecological validity, wearable technologies promise to redefine the gold standard for sleep monitoring, advancing both individualized care and population-level health assessment. Full article

Background/Objectives: This study examined the efficacy of a physical activity (PA) intervention augmented by a non-immersive Virtual Reality (VR) gaming system (i.e., Virtual Reality-infused Movement and Activity Program; V-MAP) on physical activity (i.e., sedentary behavior, moderate-to-vigorous PA [MVPA], vigorous PA [VPA]) and cognitive skills (i.e., response error, movement latency and reaction time) in Head Start preschoolers. Methods: Using a repeated-measure with 1-month follow-up design, a sample of 13 Head Start preschoolers (Mage = 67.08 ± 4.32 months; 36.2% boys) engaged in a 6-week V-MAP intervention (30-min session; 8 sessions) that focused on non-immersive VR based movement integration. The Cambridge Neuropsychological Test Automated Battery (CANTAB) was used to measure cognition; school-based PA and sedentary behavior were assessed by ActiGraph accelerometer. Pedometers were used to monitor real time engagement and implementation over eight intervention sessions. Results: On average, children obtained 1105 steps during the 30-min intervention (36.85 steps/min). There was a significant increase in VPA after the V-MAP intervention, whereas no significant changes in MVPA or sedentary behavior were observed (ps > 0.05). Although we did not observe significant improvement in studied cognitive function variables (ps > 0.05) after the V-MAP intervention, some delayed effects were observed in the follow-up test (Cohen’s d ranges from −0.41 to −0.73). Conclusions: This efficacy trial provides preliminary support that implementing V-MAP in recess may help Head Start preschoolers achieve or accumulate the recommended daily 60-min MVPA guideline during preschool years. The findings also provide insights that VR-based PA for as little as 30 min per day may benefit cognitive capability. Full article

Objective: This study investigated associations between physical activity (PA) during late adolescence and emerging adulthood and bone strength in emerging adulthood by utilizing advanced finite element analysis of computed tomography (CT/FEA) technology beyond the traditional dual-energy X-ray absorptiometry (DXA) method. Methods: This study included 266 participants (152 females) from the Iowa Bone Development Study. PA volume (average acceleration) and intensity (intensity gradient) metrics were calculated from ActiGraph accelerometer data collected at ages 17, 19, 21, and 23 years. Compressive modulus and compressive stiffness of the tibia were estimated at age 23 via CT/FEA of the tibia. Sex-specific linear regression models were used to evaluate associations between PA metrics and bone outcomes, adjusting for age, height, weight, musculoskeletal fitness, and calcium intake. Results: Intensity gradient averaged over 17–23 years of age was positively associated with compressive stiffness at age 23 years in both females and males (p < 0.01). Intensity gradient was positively associated with compressive modulus in females (p < 0.01), but not in males. No significant associations were found between average acceleration and either compressive stiffness or modulus in either sex (p > 0.05). Conclusions: Using a state-of-the-art CT/FEA method, this study suggests that high-intensity PA during late adolescence and emerging adulthood improves bone strength. Full article

Background: Self-report physical activity (PA) scales, accelerometry, and heart rate (HR) monitoring are reliable tools for PA measurement for children with cerebral palsy (CP); however, there are limitations for those who are primary wheelchair users. The purpose of our study was to evaluate face and construct validity of the PROMIS^® Pediatric PA parent proxy short form 8a in measuring PA amount and intensity in children with CP who are non-ambulatory. Methods: Face validity: Semi-structured interviews with parents and pediatric physical therapists (PTs) were conducted about the appropriateness of each item on the PROMIS^® Pediatric PA short form. Construct validity: Children with CP who were non-ambulatory participated in a one-week observational study. PA amount and intensity were examined using PA monitors (Actigraph GT9X) and HR monitors (Fitbit Charge 4). Activity counts and time in sedentary and non-sedentary intensity zones were derived and compared to the PROMIS^® T-scaled score. Results: Twenty-two physical therapists (PTs) and fifteen parents participated in the interviews, and ten children completed 1-week PA observation. Eight and seven participants completed sufficient time of uninterrupted PA and HR monitor wear, respectively. Parents and PTs agreed that several questions were not appropriate for children with CP who were non-ambulatory. PA intensity via activity counts derived from wrist worn monitors showed a strong positive correlation with the PROMIS^® PA measure. Conclusions: Construct validity in our small sample was established between PROMIS^® scores and accelerometry activity counts when documenting PA amount and intensity; however, there were some differences on PROMIS^® face validity per parent and PT respondents. Despite some concerns regarding face validity, the PROMIS^® Pediatric PA parent proxy short form 8a shows promise as a valid measure of physical activity amount and intensity in non-ambulatory children with CP, warranting further investigation and refinement. Full article

Background/Objectives: Although public health organizations encourage family walking, no studies have examined children’s physical activity and enjoyment during outdoor parent–child walks. This study addresses those gaps by examining children’s moderate-to-vigorous physical activity (MVPA) and enjoyment during outdoor walks with their parents, along with parental barriers and their relationship with parent’s self-efficacy and co-activity minutes. Methods: Fifty parent–child dyads (children aged 6–12 years) completed 10 min, self-paced outdoor walks while wearing waist-worn ActiGraph monitors. Parents reported perceived barriers to walking outdoors with their child and self-efficacy for supporting their child’s daily physical activity. Results: Children reported high enjoyment (mean = 5.1 on a six-point scale) and attained high physical activity intensity (71.3% of time in MVPA, 22.0% in vigorous activity, mean step count = 1200). Parents reported an average of 2.6 barriers (SD = 1.0) to walking outdoors with their child, with poor weather (70%) and lack of time (70%) reported most frequently. Each additional barrier was associated with a 1.3-point reduction in parents’ self-efficacy (p = 0.007). Two barriers (‘diverse interests between parent and child’ and ‘other parent-suggested barriers’) were significantly associated with fewer co-activity minutes per week (p < 0.001). Conclusions: Our study highlights the benefits of parent–child outdoor walking for promoting MVPA and enjoyment in children. Because perceived barriers may lower parents’ self-efficacy in supporting their child’s physical activity, addressing these barriers may be essential for the success of family-based interventions that encourage walking together outdoors. Full article

Background/Objectives: Imposed sleep restriction leads to increased feelings of appetite and hedonic eating behaviors (or food rewards). No study to date has assessed home-based measures of sleep with appetite and food rewards exclusively in Black emerging adults (ages 18–28 years), despite higher risks of short sleep and obesity in this population. We examined associations between 6-month changes in sleep with changes in appetite and food reward in Black emerging adults. Methods: Fifteen Black emerging adults (12 females; age, 21 ± 2.5 years; body mass index, 25.7 ± 4.5 kg/m²; body fat, 25.8 ± 11.9%) completed two identical 7-day measurement bursts at baseline and 6 months. Sleep (duration, efficiency, and architecture) was captured via 7 days of actigraphy and 2 nights of in-home polysomnography. During a laboratory visit, participants completed appetite measures (desire to eat, hunger, fullness, and prospective food consumption) via visual analog scales before and for 3 h following standard breakfast intake. The food reward for the fat and sweet categories of food was measured before lunch with the Leeds Food Preference Questionnaire. Results: Fasting fullness scores decreased from baseline to 6 months (−8.9 mm, p < 0.01) despite increases in body weight (2.6 kg, p < 0.01) and waist circumference (2.4 cm, p = 0.03). Increases in actigraph-measured sleep duration were associated with decreases in fasting desire to eat (r = −0.58, p = 0.04). Increases in actigraph-measured sleep efficiency were also associated with decreases in explicit liking for sweet foods (r = −0.60, p = 0.03). Conclusions: Our findings suggest that improvements in sleep duration and sleep efficiency may lead to decreased feelings of appetite and food reward in Black emerging adults. Full article

Background: Motor competence (MC) plays a critical role in shaping children’s physical activity, health-related fitness, and weight status. However, few studies have explored these interrelationships during middle childhood. Objectives: The current study aimed to examine the relationships between MC and physical activity (PA), health-related fitness (HRF), and weight status (WS) in children during middle childhood (9–10 years). Simultaneously, the study aimed to find possible differences in PA, HRF, and WS between children with different levels of MC. Methods: In this cross-sectional study, the TGMD-2 (MC), UNIFITTEST 6–60 (HRF), ActiGraph GT3X (PA), and anthropometry (WS) were administered to 86 children (59 boys, age range of 9–10 years and mean age of 10.1 ± 0.6 years). Results: A significant strong association was observed between MC and HRF (p < 0.01, Cramer‘s V = 0.42). Significant moderate associations were observed between MC and WS (p < 0.05, Cramer’s V = 0.34) and between MC and PA (p < 0.05, Cramer‘s V = 0.25). Children with high MC proficiency demonstrated significantly higher levels of HRF (p < 0.01; large ES) and PA (p < 0.05; moderate ES) and a healthier WS (p < 0.01; moderate ES) than those with low MC proficiency. Similarly, children with moderate MC proficiency outperformed children with low MC in terms of HRF and WS. Conclusions: The strong associations between MC and key health indicators such as PA, HRF, and WS suggest that movement proficiency in middle childhood should be viewed as a cornerstone of health promotion. Although no causal claims can be made, the results emphasize the practical importance of integrating targeted motor skill development—especially FMSs—into school-based physical education and extracurricular programs. Supporting MC at this age may be a decisive step toward fostering long-term engagement in physical activity and improving children’s overall health trajectories. Full article

Health-related quality of life (HRQoL) is a multidimensional construct that encompasses physical, emotional, psychological, and social domains, according to an individual’s perception. Studies have indicated that lifestyle-related factors, such as engaging in physical activity (PA), reducing screen time (ST), and maintaining adequate sleep duration, may contribute to improved HRQoL in adolescents. The present study aimed to examine the associations of the 24 h movement behaviors (PA, ST, and sleep duration) with physical and psychological well-being, and HRQoL in adolescents. This study included 746 adolescents of both sexes, aged 11 to 15 years, enrolled in public schools. Sleep duration was assessed through a specific question related to habitual bedtime and wake-up time. ST was evaluated using a question regarding the daily time spent using recreational electronic devices. PA was measured using accelerometers (ActiGraph GT3X-BT). The KIDSCREEN questionnaire was used to assess physical and psychological well-being and HRQoL. Generalized linear models were used for statistical analysis. Significant associations were observed between meeting sleep duration recommendations and higher HRQoL scores (β = 1.05, 95% CI: 1.01–1.08), as well as psychological well-being (β = 1.07, 95% CI: 1.03–1.11). Additionally, adherence to ST recommendations was significantly associated with higher physical well-being scores (β = 1.07, 95% CI: 1.01–1.14). Concerning the combination of adherence to guidelines, meeting both sleep duration and ST recommendations was significantly associated with higher HRQoL scores (β = 1.08, 95% CI: 1.02–1.15), physical well-being (β = 1.11, 95% CI: 1.03–1.21), and psychological well-being (β = 1.09, 95% CI: 1.01–1.18). The findings of this study highlight the importance of adhering to the 24 h movement guidelines, which may contribute to improved adolescent well-being. Full article

This case series investigates whether traditional machine learning (ML) and convolutional neural network (CNN) models trained on wrist-worn accelerometry data collected in a laboratory setting can accurately predict real-world functional hand use in individuals with chronic stroke. Participants (N = 4) with neuroimaging-confirmed chronic stroke completed matched activity scripts—comprising instrumental and basic activities of daily living—in-lab and at-home. Participants wore ActiGraph CenterPoint Insight watches on the impaired and unimpaired wrists; concurrent video recordings were collected in both environments. Frame-by-frame annotations of the video, guided by the FAABOS scale (functional, non-functional, unknown), served as the ground truth. The results revealed a consistent capacity–performance gap: participants used their impaired hand more in-lab than at-home, with the largest discrepancies in patients with moderate to severe impairment. Random forest ML models trained on in-lab accelerometry accurately classified at-home hand use, with the highest performance in mildly and severely impaired limbs (accuracy = 0.80–0.90) and relatively lower performance (accuracy = 0.62) in moderately impaired limbs. CNN models showed comparable accuracy to random forest classifiers. These pilot findings demonstrate the feasibility of using lab-trained ML models to monitor real-world hand use and identify emerging patterns of learned non-use—enabling timely, targeted interventions to promote recovery in outpatient stroke rehabilitation. Full article

Environmental enrichment is crucial to improve welfare, reduce stress, and encourage natural behaviours in dogs housed in confined environments. This study aimed to use accelerometery and machine learning to evaluate the effect of different enrichment types on dog behaviour. Three enrichments (food, olfactory, and tactile) were provided to dogs for five consecutive days, with four days between each treatment. Acceleration data were collected using a collar mounted ActiGraph^®. Nine behaviours were classified using a validated machine learning model. Behaviour and activity differed significantly among the dogs. Dogs interacted most with the food enrichment, followed by the olfactory and then tactile enrichments. The dogs were least active during the olfactory enrichment, whereas activity was relatively consistent during the food and tactile enrichments. For all enrichments, dogs exhibited the most exploratory/locomotive behaviour during the first hour of each enrichment period, but this declined over the treatment period indicating habituation. For exploratory and locomotive behaviour, food enrichment was the most stimulating for the dogs with longer daily engagement than for both olfactory and tactile enrichments. These results illustrate that accelerometery and machine learning can be used to evaluate enrichment strategies in dogs, but it is important to consider variation among dogs and habituation. Full article

This systematic review evaluated machine learning applications for analysing physical activity and behaviour in preschool children using accelerometer data. Following the PRISMA guidelines, we systematically searched PubMed, FECYT, and ProQuest Central databases. Fourteen studies implementing machine learning approaches for preschool accelerometry data were identified and assessed using the MINORS scale. Studies focused on two primary domains: physical activity analysis (n = 10) and sleep monitoring (n = 4). The ActiGraph GT3X+ was predominantly used, with placement varying between the hip and wrist. Random Forest algorithms proved most effective, achieving accuracy rates up to 86.4% in activity classification and 96.2% in sleep prediction. Sampling frequencies (0.25–100 Hz) and epoch lengths (1–60 s) varied considerably across studies. Machine learning applications show promising results for preschool physical activity assessment. However, small sample sizes and methodological inconsistencies limit generalizability. Future research should prioritise larger cohorts, explore multiple sensor integrations, and develop standardised protocols to enhance practical applications. Full article