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Accelerometers are commonly used to assess physical activity. Consumer activity trackers have become increasingly popular today, such as the Fitbit. This study aimed to compare the average number of steps per day using the wrist-worn Fitbit Flex and waist-worn ActiGraph (wGT3X-BT) in free-living conditions. 104 adult participants (n = 35 males; n = 69 females) were asked to wear a Fitbit Flex and an ActiGraph concurrently for 7 days. Daily step counts were used to classify inactive (<10,000 steps) and active (≥10,000 steps) days, which is one of the commonly used physical activity guidelines to maintain health. Proportion of agreement between physical activity categorizations from ActiGraph and Fitbit Flex was assessed. Statistical analyses included Spearman's rho, intraclass correlation (ICC), median absolute percentage error (MAPE), Kappa statistics, and Bland-Altman plots. Analyses were performed among all participants, by each step-defined daily physical activity category and gender. The median average steps/day recorded by Fitbit Flex and ActiGraph were 10193 and 8812, respectively. Strong positive correlations and agreement were found for all participants, both genders, as well as daily physical activity categories (Spearman's rho: 0.76-0.91; ICC: 0.73-0.87). The MAPE was: 15.5% (95% confidence interval [CI]: 5.8-28.1%) for overall steps, 16.9% (6.8-30.3%) vs. 15.1% (4.5-27.3%) in males and females, and 20.4% (8.7-35.9%) vs. 9.6% (1.0-18.4%) during inactive days and active days. Bland-Altman plot indicated a median overestimation of 1300 steps/day by the Fitbit Flex in all participants. Fitbit Flex and ActiGraph respectively classified 51.5% and 37.5% of the days as active (Kappa: 0.66). There were high correlations and agreement in steps between Fitbit Flex and ActiGraph. However, findings suggested discrepancies in steps between devices. This imposed a challenge that needs to be considered when using Fibit Flex in research and health promotion programs.

Wearable physical activity monitors are growing in popularity and provide the opportunity for large numbers of the public to self-monitor physical activity behaviours. The latest generation of these devices feature multiple sensors, ostensibly similar or even superior to advanced research instruments. However, little is known about the accuracy of their energy expenditure estimates. Here, we assessed their performance against criterion measurements in both controlled laboratory conditions (simulated activities of daily living and structured exercise) and over a 24 hour period in free-living conditions. Thirty men (n = 15) and women (n = 15) wore three multi-sensor consumer monitors (Microsoft Band, Apple Watch and Fitbit Charge HR), an accelerometry-only device as a comparison (Jawbone UP24) and validated research-grade multi-sensor devices (BodyMedia Core and individually calibrated Actiheart™). During discrete laboratory activities when compared against indirect calorimetry, the Apple Watch performed similarly to criterion measures. The Fitbit Charge HR was less consistent at measurement of discrete activities, but produced similar free-living estimates to the Apple Watch. Both these devices underestimated free-living energy expenditure (-394 kcal/d and -405 kcal/d, respectively; P<0.01). The multi-sensor Microsoft Band and accelerometry-only Jawbone UP24 devices underestimated most laboratory activities and substantially underestimated free-living expenditure (-1128 kcal/d and -998 kcal/d, respectively; P<0.01). None of the consumer devices were deemed equivalent to the reference method for daily energy expenditure. For all devices, there was a tendency for negative bias with greater daily energy expenditure. No consumer monitors performed as well as the research-grade devices although in some (but not all) cases, estimates were close to criterion measurements. Thus, whilst industry-led innovation has improved the accuracy of consumer monitors, these devices are not yet equivalent to the best research-grade devices or indeed equivalent to each other. We propose independent quality standards and/or accuracy ratings for consumer devices are required.

Limited knee range-of-motion (ROM) is common following total knee arthroplasty (TKA). It is associated with functional limitations and patient dissatisfaction. Regular knee ROM assessment is important but accurate testing traditionally requires timely access to trained healthcare professionals. Although accelerometer-based smartphone goniometry has shown to provide reliable and valid joint angles, current evidence of its use still positions healthcare providers as end users instead of patients themselves. Therefore, to maximize the impact of smartphone goniometry on post-TKA care, our study aimed to examine the feasibility, reliability, and validity of patients' self-measurement of knee ROM using an accelerometer-based smartphone goniometry application. Patients were given standard instructions with a practice trial before the actual measurements. Passive knee flexion and extension ROM was measured on 2 sessions in 30 patients with TKA using 4 block-randomized methods: (i) smartphone self-assessment, (ii) long-arm goniometry by physiotherapist, (iii) smartphone assessment by physiotherapist, and (iv) extendable-arm goniometry by physiotherapist with placement adjudication. Feasibility was assessed by the number of participants who could independently perform the self-measurement. To assess intra- and inter-session reliability, we computed intraclass correlation coefficients (ICCs) from random-effects models. To assess intra- and inter-session agreement, we computed mean absolute differences (MADs) and minimum detectable change (MDC). To assess concurrent validity, we designated extendable-arm goniometry as the \"gold standard\" and compared other methods against it using ICCs and MADs. All patients were able to comprehend and execute the assessment. 87% (n = 26) found the application easy to administer. Smartphone goniometry by patients showed excellent intra- and inter-session reliability (ICCs>0.97) and minimum variability (MAD = 0.9°-3.9°; MDC95 = 3.1°-9.0°). Smartphone or long-arm goniometry by physiotherapists did not outperform patients' self-assessment (ICC = 0.96-0.99, MAD = 0.7°-3.1°; MDC95 = 2.2°-8.0°). Compared against extendable-arm goniometry, smartphone goniometry by patients measured knee flexion and extension ROM with a MAD of 4.5° (ICC, 0.97) and 2.2° (ICC = 0.98), respectively. Our study demonstrates that smartphone goniometry is feasible, reliable and accurate, and can be used with confidence in the self-assessment of knee ROM post-TKA. Future studies should further explore its utility in telemonitored rehabilitation, and its possible integration into mobile health applications to enhance accessibility to care following TKA.

Background The development of validated “fit-for-purpose” rapid assessment tools to measure 24-hour movement behaviours in children aged 0–5 years is a research priority. This study evaluated the test-retest reliability and concurrent validity of the open-ended and closed-ended versions of the Movement Behaviour Questionnaire for baby (MBQ-B) and child (MBQ-C). Methods 300 parent-child dyads completed the 10-day study protocol (MBQ-B: N  = 85; MBQ-C: N  = 215). To assess validity, children wore an accelerometer on the non-dominant wrist (ActiGraph GT3X+) for 7 days and parents completed 2 × 24-hour time use diaries (TUDs) recording screen time and sleep on two separate days. For babies (i.e., not yet walking), parents completed 2 × 24-hour TUDs recording tummy time, active play, restrained time, screen time, and sleep on days 2 and 5 of the 7-day monitoring period. To assess test-retest reliability, parents were randomised to complete either the open- or closed-ended versions of the MBQ on day 7 and on day 10. Test-retest intraclass correlation coefficients (ICC’s) were calculated using generalized linear mixed models and validity was assessed via Spearman correlations. Results Test-retest reliability for the MBQ-B was good to excellent with ICC’s ranging from 0.80 to 0.94 and 0.71–0.93 for the open- and closed-ended versions, respectively. For both versions, significant positive correlations were observed between 24-hour diary and MBQ-B reported tummy time, active play, restrained time, screen time, and sleep (rho = 0.39–0.87). Test-retest reliability for the MBQ-C was moderate to excellent with ICC’s ranging from 0.68 to 0.98 and 0.44–0.97 for the open- and closed-ended versions, respectively. For both the open- and closed-ended versions, significant positive correlations were observed between 24-hour diary and MBQ-C reported screen time and sleep (rho = 0.44–0.86); and between MBQ-C reported and device-measured time in total activity and energetic play (rho = 0.27–0.42). Conclusions The MBQ-B and MBQ-C are valid and reliable rapid assessment tools for assessing 24-hour movement behaviours in infants, toddlers, and pre-schoolers. Both the open- and closed-ended versions of the MBQ are suitable for research conducted for policy and practice purposes, including the evaluation of scaled-up early obesity prevention programs.

ObjectiveTo determine the accuracy of wrist and arm-worn activity monitors’ estimates of energy expenditure (EE).Data sourcesSportDISCUS (EBSCOHost), PubMed, MEDLINE (Ovid), PsycINFO (EBSCOHost), Embase (Ovid) and CINAHL (EBSCOHost).DesignA random effects meta-analysis was performed to evaluate the difference in EE estimates between activity monitors and criterion measurements. Moderator analyses were conducted to determine the benefit of additional sensors and to compare the accuracy of devices used for research purposes with commercially available devices.Eligibility criteriaWe included studies validating EE estimates from wrist-worn or arm-worn activity monitors against criterion measures (indirect calorimetry, room calorimeters and doubly labelled water) in healthy adult populations.Results60 studies (104 effect sizes) were included in the meta-analysis. Devices showed variable accuracy depending on activity type. Large and significant heterogeneity was observed for many devices (I2 >75%). Combining heart rate or heat sensing technology with accelerometry decreased the error in most activity types. Research-grade devices were statistically more accurate for comparisons of total EE but less accurate than commercial devices during ambulatory activity and sedentary tasks.ConclusionsEE estimates from wrist and arm-worn devices differ in accuracy depending on activity type. Addition of physiological sensors improves estimates of EE, and research-grade devices are superior for total EE. These data highlight the need to improve estimates of EE from wearable devices, and one way this can be achieved is with the addition of heart rate to accelerometry.PROSPEROregistration numberCRD42018085016.

Background Over 1.3 million people live with colorectal cancer in the United States. Physical activity is associated with lower risk of colorectal cancer recurrence and mortality. Interventions are needed to increase physical activity in colorectal cancer survivors. Methods We conducted a 2-arm non-blinded pilot randomized controlled trial at the University of California, San Francisco among 42 individuals who had completed curative-intent treatment for colorectal cancer to determine the feasibility and acceptability of a 12-week (84 days) physical activity intervention using a Fitbit Flex™ and daily text messages. Participants were randomized 1:1 to receive the intervention with print educational materials or print educational materials alone. We explored the impact of the intervention versus usual care on physical activity using ActiGraph GT3X+ accelerometers pre−/post-intervention. Results We screened 406 individuals and randomized 42 to intervention ( n  = 21) or control ( n  = 21) groups. During the 12-week study, the intervention arm wore their Fitbits a median of 74 days [88% of days in study period, interquartile range: 23–83 days] and responded to a median of 34 (out of 46) text messages that asked for a reply (interquartile range: 13–38 text messages). Among the 16 intervention participants who completed the feedback survey, the majority (88%) reported that the intervention motivated them to exercise and that they were satisfied with their experience. No statistically significant difference in change in moderate-to-vigorous physical activity was found from baseline to 12 weeks between arms. Conclusion A 12-week physical activity intervention with a Fitbit and text messages was feasible and acceptable among colorectal cancer patients after curative treatment. Larger studies are needed to determine whether the intervention increases physical activity. Trial registration Clinicaltrials.gov Identifier NCT02966054 . Registered 17 November 2016, retrospectively registered.

To our knowledge, no studies have examined light physical activity (PA) measured by accelerometry and heart disease in older women. To investigate whether higher levels of light PA were associated with reduced risks of coronary heart disease (CHD) or cardiovascular disease (CVD) in older women. Prospective cohort study of older women from baseline (March 2012 to April 2014) through February 28, 2017, for up to 4.91 years. The setting was community-dwelling participants from the Women's Health Initiative. Participants were ambulatory women with no history of myocardial infarction or stroke. Data from accelerometers worn for a requested 7 days were used to measure light PA. Cox proportional hazards regression models estimated hazard ratios (HRs) and 95% CIs for physician-adjudicated CHD and CVD events across light PA quartiles adjusting for possible confounders. Light PA was also analyzed as a continuous variable with and without adjustment for moderate to vigorous PA (MVPA). Among 5861 women (mean [SD] age, 78.5 [6.7] years), 143 CHD events and 570 CVD events were observed. The HRs for CHD in the highest vs lowest quartiles of light PA were 0.42 (95% CI, 0.25-0.70; P for trend <.001) adjusted for age and race/ethnicity and 0.58 (95% CI, 0.34-0.99; P for trend = .004) after additional adjustment for education, current smoking, alcohol consumption, physical functioning, comorbidity, and self-rated health. Corresponding HRs for CVD in the highest vs lowest quartiles of light PA were 0.63 (95% CI, 0.49-0.81; P for trend <.001) and 0.78 (95% CI, 0.60-1.00; P for trend = .004). The HRs for a 1-hour/day increment in light PA after additional adjustment for MVPA were 0.86 (95% CI, 0.73-1.00; P for trend = .05) for CHD and 0.92 (95% CI, 0.85-0.99; P for trend = .03) for CVD. The present findings support the conclusion that all movement counts for the prevention of CHD and CVD in older women. Large, pragmatic randomized trials are needed to test whether increasing light PA among older women reduces cardiovascular risk.

Background Sedentary behavior (SB) is a recognized risk factor for many chronic diseases. ActiGraph and activPAL are two commonly used wearable accelerometers in SB research. The former measures body movement and the latter measures body posture. The goal of the current study is to quantify the pattern and variation of movement (by ActiGraph activity counts) during activPAL-identified sitting events, and examine associations between patterns and health-related outcomes, such as systolic and diastolic blood pressure (SBP and DBP). Methods The current study included 314 overweight postmenopausal women, who were instructed to wear an activPAL (at thigh) and ActiGraph (at waist) simultaneously for 24 hours a day for a week under free-living conditions. ActiGraph and activPAL data were processed to obtain minute-level time-series outputs. Multilevel functional principal component analysis (MFPCA) was applied to minute-level ActiGraph activity counts within activPAL-identified sitting bouts to investigate variation in movement while sitting across subjects and days. The multilevel approach accounted for the nesting of days within subjects. Results At least 90% of the overall variation of activity counts was explained by two subject-level principal components (PC) and six day-level PCs, hence dramatically reducing the dimensions from the original minute-level scale. The first subject-level PC captured patterns of fluctuation in movement during sitting, whereas the second subject-level PC delineated variation in movement during different lengths of sitting bouts: shorter (< 30 minutes), medium (30 -39 minutes) or longer (> 39 minute). The first subject-level PC scores showed positive association with DBP (standardized β ^ : 2.041, standard error: 0.607, adjusted p = 0.007), which implied that lower activity counts (during sitting) were associated with higher DBP. Conclusion In this work we implemented MFPCA to identify variation in movement patterns during sitting bouts, and showed that these patterns were associated with cardiovascular health. Unlike existing methods, MFPCA does not require pre-specified cut-points to define activity intensity, and thus offers a novel powerful statistical tool to elucidate variation in SB patterns and health. Trial registration ClinicalTrials.gov NCT03473145; Registered 22 March 2018; https://clinicaltrials.gov/ct2/show/NCT03473145 ; International Registered Report Identifier (IRRID): DERR1-10.2196/28684

Objective: First, to investigate the effects of a telerehabilitation intervention on health status and activity level of patients with Chronic Obstructive Pulmonary Disease (COPD), compared to usual care. Second, to investigate how patients comply with the intervention and whether compliance is related to treatment outcomes. Design: a randomized controlled pilot trial Subjects: Thirty-four patients diagnosed with COPD. Intervention: The telerehabilitation application consists of an activity coach (3D-accelerometer with smartphone) for ambulant activity registration and real-time feedback, complemented by a web portal with a symptom diary for self-treatment of exacerbations. The intervention group used the application for 4 weeks. The control group received usual care. Main measures: Activity level measured by a pedometer (in steps/day), health status by the Clinical COPD Questionnaire at baseline and after intervention. Compliance was expressed as the time the activity coach was worn. Results: Fourteen intervention and 16 control patients completed the study. Activity level (steps/day) was not significantly affected by the intervention over time. There was a non-significant difference in improvement in health status between the intervention (−0.34±0.55) and control group (0.02±0.57, p=0.10). Health status significantly improved within the intervention group (p=0.05). The activity coach was used more than prescribed (108%) and compliance was related to the increase in activity level for the first two feedback weeks (r=0.62, p=0.03). Conclusions: This pilot study shows the potential of the telerehabilitation intervention: compliance with the activity coach was high, which directly related to an improvement in activity levels.

Background Individuals with knee and hip osteoarthritis (OA) are less physically active than people in general, and many of these individuals have adopted a sedentary lifestyle. In this study we evaluate the outcome of education and supervised exercise on the level of physical activity in individuals with knee or hip OA. We also evaluate the effect on pain, quality of life and self-efficacy. Methods Of the 264 included individuals with knee or hip OA, 195 were allocated to the intervention group. The intervention group received education and supervised exercise that comprised information delivered by a physiotherapist and individually adapted exercises. The reference group consisted of 69 individuals with knee or hip OA awaiting joint replacement and receiving standard care. The primary outcome was physical activity (as measured with an accelerometer). The secondary outcomes were pain (Visual Analog Scale), quality of life (EQ-5D), and self-efficacy (Arthritis Self-Efficacy Scale, pain and other symptoms subscales). Participants in both groups were evaluated at baseline and after 3 months. The intervention group was also evaluated after 12 months. Results No differences were found in the number of minutes spent in sedentary or in physical activity between the intervention and reference groups when comparing the baseline and 3 month follow-up. However, there was a significant difference in mean change (mean diff; 95% CI; significance) between the intervention group and reference group favoring the intervention group with regard to pain (13; 7 to 19; p  < 0.001), quality of life (− 0.17; − 0.24 to − 0.10; p  < 0.001), self-efficacy/other symptoms (− 5; − 10 to − 0.3; p  < 0.04), and self-efficacy/pain (− 7; − 13 to − 2; p  < 0.01). Improvements in pain and quality of life in the intervention group persisted at the 12-month follow-up. Conclusions Participation in an education and exercise program following the Swedish BOA program neither decreased the average amount of sedentary time nor increased the level of physical activity. However, participation in such a program resulted in decreased pain, increased quality of life, and increased self-efficacy. Trial registration The trial is registered with ClinicalTrials.gov. Registration number: NCT02022566 . Retrospectively registered 12/18/2013.