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Background: Children have alarmingly low levels of competency in fundamental motor skills (FMS) and high levels of physical inactivity. e:health interventions, interventions delivered electronically, are useful tools for intervention in the home through parents, but less is known about the effects of these interventions in early childhood education centers or settings. Therefore, we created the Motor skills At Playtime (MAP) e:health intervention (e:MAP) to be delivered in an early childhood education setting. The goals of this pilot study on e:MAP are to (1) determine the intervention effects on children's FMS and physical activity and (2) explore the teachers' perceptions and ability to facilitate e:MAP. Methods: This pilot study uses a pretest/posttest randomized cluster control design. We will recruit at least 64 children (3.5–5 years of age) enrolled in a single early childhood education center. Children will be randomly assigned at the level of the classroom to an e:MAP group (n~30) or a control group (n~30). Children in classrooms assigned to e:MAP will complete an 8-week intervention. We will collect measures of child FMS and physical activity, and teacher's perceptions of the program before (pretest) and after the intervention (posttest). FMS measures include process (Test of Gross Motor Development-3rd Edition) and product-oriented scores. Physical activity will be assessed using a 7-day accelerometer wear protocol. Teachers' perceptions will be assessed through a brief survey. Lastly, we will collect data on teachers' ability to facilitate e:MAP through a daily survey. Potential significance: This study will yield novel insights into the effectiveness and feasibility of a health intervention in an early childhood education setting. Results from this work will expand our knowledge of how to harness e:health modalities, which have the potential to significantly expand the distribution and scalability of FMS interventions. [ABSTRACT FROM AUTHOR]

This cross-sectional study aimed to identify and validate cut-points for measuring physical activity using Axivity AX6 accelerometers positioned at the shank in older adults. Free-living physical activity was assessed in 35 adults aged 55 and older, where each participant wore a shank-mounted Axivity and a waist-mounted ActiGraph simultaneously for 72 hours. Optimized cut-points for each participant's Axivity data were determined using an optimization algorithm to align with ActiGraph results. To assess the validity between the physical activity assessments from the optimized Axivity cut-points, a leave-one-out cross-validation was conducted. Bland-Altman plots with 95% limits of agreement, intraclass correlation coefficients (ICC), and mean differences were used for comparing the systems. The results indicated good agreement between the two accelerometers when classifying sedentary behaviour (ICC = 0.85) and light physical activity (ICC = 0.80), and moderate agreement when classifying moderate physical activity (ICC = 0.67) and vigorous physical activity (ICC = 0.70). Upon removal of a significant outlier, the agreement was slightly improved for sedentary behaviour (ICC = 0.86) and light physical activity (ICC = 0.82), but substantially improved for moderate physical activity (ICC = 0.81) and vigorous physical activity (ICC = 0.96). Overall, the study successfully demonstrated the capability of the resultant cut-point model to accurately classify physical activity using Axivity AX6 sensors placed at the shank. [ABSTRACT FROM AUTHOR]

Spending time outdoors is associated with increased time spent in physical activity, lower chronic disease risk, and wellbeing. Many studies rely on self-reported measures, which are prone to recall bias. Other methods rely on features and functions only available in some GPS devices. Thus, a reliable and versatile method to objectively quantify time spent outdoors is needed. This study sought to develop a versatile method to classify indoor and outdoor (I/O) GPS data that can be widely applied using most types of GPS and accelerometer devices. To develop and test the method, five university students wore an accelerometer (ActiGraph wGT3X-BT) and a GPS device (Canmore GT-730FL-S) on an elastic belt at the right hip for two hours in June 2022 and logged their activity mode, setting, and start time via activity diaries. GPS trackers were set to collect data every 5 seconds. A rule-based point cluster-based method was developed to identify indoor, outdoor, and in-vehicle time. Point clusters were detected using an application called GPSAS_Destinations and classification were done in R using accelerometer lux, building footprint, and park location data. Classification results were compared with the submitted activity diaries for validation. A total of 7,006 points for all participants were used for I/O classification analyses. The overall I/O GPS classification accuracy rate was 89.58% (Kappa = 0.78), indicating good classification accuracy. This method provides reliable I/O clarification results and can be widely applied using most types of GPS and accelerometer devices. [ABSTRACT FROM AUTHOR]

Self-report and device-based measures of physical activity (PA) both have unique strengths and limitations; combining these measures should provide complementary and comprehensive insights to PA behaviours. Therefore, we aim to 1) identify PA clusters and clusters of change in PA based on self-reported daily activities and 2) assess differences in device-based PA between clusters in a lifestyle intervention, the PREVIEW diabetes prevention study. In total, 232 participants with overweight and prediabetes (147 women; 55.9 ± 9.5yrs; BMI ≥25 kg·m-2; impaired fasting glucose and/or impaired glucose tolerance) were clustered using a partitioning around medoids algorithm based on self-reported daily activities before a lifestyle intervention and their changes after 6 and 12 months. Device-assessed PA levels (PAL), sedentary time (SED), light PA (LPA), and moderate-to-vigorous PA (MVPA) were assessed using ActiSleep+ accelerometers and compared between clusters using (multivariate) analyses of covariance. At baseline, the self-reported "walking and housework" cluster had significantly higher PAL, MVPA and LPA, and less SED than the "inactive" cluster. LPA was higher only among the "cycling" cluster. There was no difference in the device-based measures between the "social-sports" and "inactive" clusters. Looking at the changes after 6 months, the "increased walking" cluster showed the greatest increase in PAL while the "increased cycling" cluster accumulated the highest amount of LPA. The "increased housework" and "increased supervised sports" reported least favourable changes in device-based PA. After 12 months, there was only minor change in activities between the "increased walking and cycling", "no change" and "increased supervised sports" clusters, with no significant differences in device-based measures. Combining self-report and device-based measures provides better insights into the behaviours that change during an intervention. Walking and cycling may be suitable activities to increase PA in adults with prediabetes. [ABSTRACT FROM AUTHOR]

There is growing interest in identifying valid and reliable methods for detecting early mobility limitations in aging populations. A multi-sensor approach that combines accelerometry with Global Positioning System (GPS) devices could provide valuable insights into late-life mobility decline; however, this innovative approach requires more investigation. We conducted a series of two experiments with 25 older participants (66.2±8.5 years) to determine the validity of a GPS enabled smartwatch (TicWatch S2 and Pro 3 Ultra GPS) and separate accelerometer (ActiGraph wGT3X-BT) to collect movement, navigation and body posture data relevant to mobility. In experiment 1, participants wore the TicWatchS2 and ActiGraph simultaneously on the wrist for 3 days. In experiment 2, participants wore the TicWatch Pro 2 Ultra GPS on the wrist and ActiGraph on the thigh for 3 days. In both experiments participants also carried a Qstarz data logger for trips outside the home. The TicWatch Pro 3 Ultra GPS performed better than the S2 model and was similar to the Qstarz in all tested trip-related measures, and it was able to estimate both passive and active trip modes. Both models showed similar results to the gold standard Qstarz in life-space-related measures. The TicWatch S2 demonstrated good to excellent overall agreement with the ActiGraph algorithms for the time spent in sedentary and non-sedentary activities, with 84% and 87% agreement rates, respectively. Under controlled conditions, the TicWatch Pro 3 Ultra GPS consistently measured step count in line with the participants' self-reported data, with a bias of 0.4 steps. The thigh-worn ActiGraph algorithm accurately classified sitting and lying postures (97%) and standing postures (90%). Our multi-sensor approach to monitoring mobility has the potential to capture both accelerometer-derived movement data and trip/life-space data only available through GPS. In this study, we found that the TicWatch models were valid devices for capturing GPS and raw accelerometer data, making them useful tools for assessing real-life mobility in older adults. [ABSTRACT FROM AUTHOR]

Clinical rating scales typically includes subjective evaluations, and their time-limited duration may fail to capture daily fluctuations in motor symptoms resulting from Parkinson's disease (PD). Recently, a new tool (i.e. the PD-Watch) has been proposed for the objective and continuous assessment of PD motor manifestations based on evaluating frequency data from a wrist-worn tri-axial accelerometer and identifying specific movement patterns typically associated with disorders. This reduces the probability of confusing physiological or pathological movements occurring at the same frequency. In this work, we present a new method for assessing motor fluctuations through a wrist-worn accelerometer. We also explore the agreement between the continuous data generated by the proposed method and data reported in the patient diaries. In this study, twelve PD patients were recruited with an overall recording duration of 528 hours. Results of this preliminary study show that the proposed tool has suitable and adequate performances for analysing the motor signs of PD patients, and the estimated sensitivity, specificity, and accuracy of the tool are 85%, 94%, and 91%, respectively. [ABSTRACT FROM AUTHOR]

It is desirable to attend to the mare at the time of foaling in order to assist fetal delivery and prevent complications. The early detection of the onset of labor is an important issue for the equine industry. The purpose of this study was to examine the applicability of a sensor for foaling detection using the data of surface temperature (ST), roll angle (rotation about the y-axis) and y-axis (long axis of the tail) acceleration which were collected from a multimodal device attached to the ventral tail base of the mare. The data were collected every 3 minutes in 17 pregnant mares. Roll angle differences from the reference values and the mare's posture (standing or recumbent) confirmed by video were compared and associated. Cohen's kappa coefficient was 0.99 when the threshold was set as ± 0.3 radian in roll angle differences. This result clearly showed that the sensor data can accurately distinguish between standing and recumbent postures. The hourly sensor data with a lower ST (LST < 35.5°C), a recumbent posture determined by the roll angle, and tail-raising (TR, decline of 200 mg or more from the reference value in y-axis acceleration) was significantly higher during the last hour prepartum than 2−120 hours before parturition (P < 0.01). The accuracy of foaling detection within one hour was verified using the following three indicators: LST; lying down (LD, change from standing to recumbent posture); and TR. When LST, LD and TR were individually examined, even though all indicators showed that sensitivity was 100%, the precision was 13.1%, 8.1% and 2.8%, respectively. When the data were combined as LST+LD, LST+TR, LD+TR and LST+LD+TR, detection of foaling improved, with precisions of 100%, 32.1%, 56.7% and 100%, respectively. In conclusion, the tail-attached multimodal device examined in this present study is useful for detecting foaling. [ABSTRACT FROM AUTHOR]

Background: Reliable physical activity measurements in community-dwelling older adults are important to determine effects of targeted health promotion interventions. Many exercise interventions aim to improve time spent sedentary (SED), in light-intensity-physical-activity (LPA) and moderate-to-vigorous-intensity-physical-activity (MVPA), since these parameters have independently proposed associations with health and longevity. However, many previous studies rely on self-reports which have lower validity compared to accelerometer measured physical activity patterns. In addition, separating intervention-effects from reactivity measurements requires sufficient test-retest reliability for accelerometer assessments, which is lacking in older adults. Objectives: The study objective was to investigate the reliability of sensor-based PA-patterns in community-dwelling older adults. Furthermore, to investigate change over time of physical activity patterns and examine any compensatory-effect from the eight-week supervised exercise-intervention. Methods: An exercise-group (n = 78, age-range:65-91yrs) performed two 1h-exercise sessions/week during eight-weeks. PA-pattern was assessed (using hip-worn accelerometers), twice before and once during the last-week of the intervention. A control-group (n = 43, age-range:65-88yrs) performed one pre-test and the end-test with no exercise-intervention. A dependent-t-test, mean-difference (95%-CI), limits-of-agreement and intraclass-correlation-coefficient-ICC were used between the two pre-tests. Repeated-measures-ANOVA were used to analyze any intervention-effects. Results: The exercise-groups´ two pre-tests showed generally no systematic change in any PA- or SED-parameter (ICC ranged 0.75–0.90). Compared to the control group, the exercise intervention significantly (time x group-interaction, p<0.05) increased total-PA-cpm (exercise-group/control-group +17%/+7%) and MVPA-min/week (+41/-2min) and decreased %-of-wear-time for SED-total (-4.7%/-2.7%) and SED-bouts (-5.7%/-1.8%), and SED-bouts min/d (-46/-16min). At baseline level, no significant differences were found between the two groups for any parameter. Conclusions: The current study presents a good test-retest-reliability of sensor-based-one-week-assessed-PA-pattern in older-adults. Participating in an 8-week supervised exercise intervention improved some physical activity and sedentary parameters compared to the control group. No compensatory-effect was noted in the intervention-group i.e., no decrease in any PA-parameter or increase in SED at End-test (in %-of-wear-time, min/day or total-PA). [ABSTRACT FROM AUTHOR]

Marine protected areas (MPAs) are widely utilized for conservation of the world's marine resources. Yet, compliance with MPA regulations remains difficult to measure because of limits to human resources and a lack of affordable technologies to automate monitoring over time. The Marine Monitor, an autonomous vessel monitoring, recording, and reporting system leveraging commercial off-the-shelf X-band marine radar to detect and track vessels, was used to monitor five nearshore California MPAs simultaneously and continuously to identify and compare site-specific use patterns over one year. Vessel tracks were classified into two movement patterns to capture likely fishing activity, "focal" or "linear", that corresponded with local targeted species. Some illegal fishing potentially occurred at all sites (7–17% of tracks depending on site) most frequently on weekends and at mid-day, but the majority of activity occurred just outside the MPAs and in the near vicinity suggesting both a high level of compliance with regulations and awareness of MPA boundaries. Time spent engaged in potential fishing activity compared to track counts suggests that unique vessels may spend more time fishing inside area boundaries at some sites than others. The spatial distribution of activity shows distinct concentrations near MPA boundaries at all sites which strongly suggests vessels purposefully target the narrow area at the MPA boundary or "fish the line", a potential acknowledgement of successful spillover. This activity increased significantly during some local fishing seasons. Concentration of activity at MPA boundaries highlights the importance of continuous monitoring at a high spatial and temporal resolution. Reporting of vessel behavior at a fine-scale using radar can help resource managers target enforcement efforts and understand human use patterns near coastal MPAs. [ABSTRACT FROM AUTHOR]

External peak power in the countermovement jump is frequently used to monitor athlete training. The gold standard method uses force platforms, but they are unsuitable for field-based testing. However, alternatives based on jump flight time or Newtonian methods applied to inertial sensor data have not been sufficiently accurate for athlete monitoring. Instead, we developed a machine learning model based on characteristic features (functional principal components) extracted from a single body-worn accelerometer. Data were collected from 69 male and female athletes at recreational, club or national levels, who performed 696 jumps in total. We considered vertical countermovement jumps (with and without arm swing), sensor anatomical locations, machine learning models and whether to use resultant or triaxial signals. Using a novel surrogate model optimisation procedure, we obtained the lowest errors with a support vector machine when using the resultant signal from a lower back sensor in jumps without arm swing. This model had a peak power RMSE of 2.3 W·kg-1 (5.1% of the mean), estimated using nested cross validation and supported by an independent holdout test (2.0 W·kg-1). This error is lower than in previous studies, although it is not yet sufficiently accurate for a field-based method. Our results demonstrate that functional data representations work well in machine learning by reducing model complexity in applications where signals are aligned in time. Our optimisation procedure also was shown to be robust can be used in wider applications with low-cost, noisy objective functions. [ABSTRACT FROM AUTHOR]

To reexamine the relationship between leisure-time physical activity (LTPA) and the built environment (BE), this paper takes advantage of the massive amount of data collected by an accelerometer and GPS-based fitness mobile app. Massive LTPA data from more than 3 million users were recorded by Codoon in 500m by 500m grid cells and aggregated to 742 natural cities in mainland China. Six BE indicators were quantified using GIS at the city scale. Robust regression analysis was used to estimate the correlation between LTPA and BE. Five of six BE indicators—connectivity, road density, land use mix, points of interest density, and density of parks and squares—were significantly, positively, independently, and linearly related to LTPA in the regression analysis. The study obtains findings that are consistent with the previous literature but also provides novel insights into the important role of POI density in encouraging LTPA, as well as how the relationship between LTPA and BE varies by time of day. The study also sheds light on the embrace of new technology and new data in public health and urban studies. [ABSTRACT FROM AUTHOR]

Wearable sensor systems are a emerging tools for the evaluation of the sport's activity and can be used to quantify the external workload of the athlete. The main goal of this paper was to evaluate the validity and reliability of the "Armbeep inertial measurement unit" (IMU) sensor both in a closed tennis exercise and in open matchplay. Twentyfour junior tennis players performed a baseline drill and played matches, during which they wore a combined accelerometer and gyroscope sensor. Video footage was concomitantly recorded using a digital video camera. The agreement between the measurements was assessed with the intraclass correlation coefficient (ICC) and the standard error of measurement (SEM). A simple linear regression was used to predict the number of shots registered from the video and from the Armbeep IMU sensor's data. The number of total forehand and backhand shots during the drill repetitions showed an excellent test and re-test reproducibility (ICC≥0.90). There was a significant relationship between the Armbeep IMU sensor's number of contacts and the total number of shots (R2 = 0.938) which indicated the excellent reliability of the tested Armbeep IMU sensor for those parameters. Considering the accuracy of the total tennis shots and the small magnitude of error for wrist speed and acceleration, the Armbeep IMU sensor appears to be an appropriate on-court tool that can be used to monitor the hitting load during tennis practice and matches. [ABSTRACT FROM AUTHOR]

We examined the influence of using different epoch lengths on the classification accuracy of laboratory-controlled sedentary behaviour (SB), and free-living total time and time spent in bouts of SB and moderate-to-vigorous physical activity (MVPA), in children and adolescents. We used two studies including accelerometer-derived data of: 1) controlled activities, i.e. seven sedentary, one standing and one dancing (n = 90); 2) free-living activities (n = 902). For the controlled-activity data, we calculated percentages of time classified as SB and MVPA. For the free-living data, we calculated medians (25th–75th percentiles) of total time and time spent in bouts of SB and MVPA. Applying 8counts/5seconds, 25counts/15seconds and 100counts/60seconds for SB on controlled-activity data revealed respectively (1) 92–96%, 89–99% and 98–100% of sedentary time accurately classified as SB (activity- and age-dependent); (2) 91–98%, 88–99% and 97–100% of standing time classified as SB (age-dependent); (3) 25–37%, 20–25% and 25–38% of dancing time classified as SB (age-dependent). Using longer epochs, children's total time in SB and MVPA decreased while time accumulated in bouts of SB and MVPA accumulated in bouts increased. We conclude that a 60-second epoch seems preferable when the aim is to classify sedentary behaviour, while a shorter epoch length is needed to capture children's short bursts of MPVA. Furthermore, we should be aware that a longer epoch results in averaging of intensities to the middle category. [ABSTRACT FROM AUTHOR]

The present work explores the distinctive contribution of motor planning and control to human reaching movements. In particular, the movements were triggered by the selection of a prepotent response (Dominant) or, instead, by the inhibition of the prepotent response, which required the selection of an alternative one (Non-dominant). To this end, we adapted a Go/No-Go task to investigate both the dominant and non-dominant movements of a cohort of 19 adults, utilizing kinematic measures to discriminate between the planning and control components of the two actions. In this experiment, a low-cost, easy to use, 3-axis wrist-worn accelerometer was put to good use to obtain raw acceleration data and to compute and break down its velocity components. The values obtained with this task indicate that with the inhibition of a prepotent response, the selection and execution of the alternative one yields both a longer reaction time and movement duration. Moreover, the peak velocity occurred later in time in the non-dominant response with respect to the dominant response, revealing that participants tended to indulge more in motor planning than in adjusting their movement along the way. Finally, comparing such results to the findings obtained by other means in the literature, we discuss the feasibility of an accelerometer-based analysis to disentangle distinctive cognitive mechanisms of human movements. [ABSTRACT FROM AUTHOR]

The study of physical activity in older adults is becoming more and more relevant. For evaluation of physical activity recommendations, intensity-specific accelerometer cut-points are utilized. However, research on accelerometer cut-points for older adults is still scarce. The aim of the study was to generate placement-specific cut-points of ActiGraph GT3X+ activity counts and raw measures of acceleration to determine physical activity intensity in older adults. A further aim was to compare the validity of the generated cut-points for a range of different physical activities. The study was a single experimental trial using a convenience sample. Study participants were 20 adults aged 59 to 73 years. Accelerometers were worn at six different placements (one on each wrist, one on each ankle, and two at the hip) and breath-by-breath indirect calorimetry was used as the reference for energy. The experiment comprised of two parts; a) The first required participants to walk on a treadmill at incremental speeds (3.0–5.0 km·h-1), and b) Five different everyday activities (reading, cleaning, shopping, cycling, aerobics) were staged in the laboratory setting. Accelerometer cut-points (activity counts, raw data) were derived for each of the investigated placements by linear regression using the treadmill part. Performance of the cut-points was assessed by applying the cut-points to the everyday activities. We provide cut-points for six placements and two accelerometer metrics in the specific age group. However, the derived cut-points did not outperform published ones. More research and innovative approaches are needed for improving internal and external validity of research results across populations and age groups. [ABSTRACT FROM AUTHOR]

Seefeldt's classic motor development pyramid model recognizes the significance of fundamental movement skills (FMS) in physical activities and proposes a "proficiency barrier" between FMS and higher-level specific sports skills during middle childhood. However, the relationship between the layers of the conceptual model has not been empirically tested. This study investigated motor fitness (MF), FMS, and quality of movement patterns (QMP) in 7–10 years old children and evaluated the relationships among them. A total of 117 children were randomly selected to take tests of MF, the Test of Gross Motor Development-2 (TGMD-2), and the Functional Movement Screen (FMS™). MF and FMS levels were classified according to percentile ranges. Two multiple (R×C) Chi-Square tests were applied to analyze the relationships between MF, FMS, and QMP. Post-hoc testing estimated the possibility of FMS and QMP to predict MF. The results showed that boys scored significantly higher on the object-control subtest and on the TGMD-2 compared to girls (p<0.001), while girls scored significantly higher on the FMS™ (p = 0.001). FMS score and QMP level were weakly correlated with MF (FMS: χ2 = 14.605, p = 0.006, Cramer's V = 0.25; QMP: χ2 = 13.943, p = 0.007, Cramer's V = 0.24). Thus, 60.5% of children with "excellent" FMS and 59.6% with "high" QMP were categorized as having a "good" MF. In contrast, only 23.1% of children with "poor" FMS and 24.3% with "low" QMP were classified as having a "good" MF. Our results confirm MF, FMS, and QMP are correlated with each other, although this relationship is weak. Further, a possible motor skill proficiency barrier exists already in children 7–10 years old. The study results support the promotion of physical activity and motor skill development in primary school children. [ABSTRACT FROM AUTHOR]

Recognition of early signs of deterioration in postoperative course could be improved by continuous monitoring of vital parameters. Wearable sensors could enable this by wireless transmission of vital signs. A novel accelerometer-based device, called Healthdot, has been designed to be worn on the skin to measure the two key vital parameters respiration rate (RespR) and heart rate (HeartR). The goal of this study is to assess the reliability of heart rate and respiration rate measured by the Healthdot in comparison to the gold standard, the bedside patient monitor, during the postoperative period in bariatric patients. Data were collected in a consecutive group of 30 patients who agreed to wear the device after their primary bariatric procedure. Directly after surgery, a Healthdot was attached on the patients' left lower rib. Vital signs measured by the accelerometer based Healthdot were compared to vital signs collected with the gold standard patient monitor for the period that the patient stayed at the post-anesthesia care unit. Over all patients, a total of 22 hours of vital signs obtained by the Healthdot were recorded simultaneously with the bedside patient monitor data. 87.5% of the data met the pre-defined bias of 5 beats per minute for HeartR and 92.3% of the data met the pre-defined bias of 5 respirations per minute for RespR. The Healthdot can be used to accurately derive heart rate and respiration rate in postbariatric patients. Wireless continuous monitoring of key vital signs has the potential to contribute to earlier recognition of complications in postoperative patients. Future studies should focus on the ability to detect patient deterioration in low-care environments and at home after discharge from the hospital. [ABSTRACT FROM AUTHOR]

Purpose: To adapt and validate a previously developed decision tree for youth to identify bedrest for use in preschool children. Methods: Parents of healthy preschool (3-6-year-old) children (n = 610; 294 males) were asked to help them to wear an accelerometer for 7 to 10 days and 24 hours/day on their waist. Children with ≥3 nights of valid recordings were randomly allocated to the development (n = 200) and validation (n = 200) groups. Wear periods from accelerometer recordings were identified minute-by-minute as bedrest or wake using visual identification by two independent raters. To automate visual identification, chosen decision tree (DT) parameters (block length, threshold, bedrest-start trigger, and bedrest-end trigger) were optimized in the development group using a Nelder-Mead simplex optimization method, which maximized the accuracy of DT-identified bedrest in 1-min epochs against synchronized visually identified bedrest (n = 4,730,734). DT's performance with optimized parameters was compared with the visual identification, commonly used Sadeh's sleep detection algorithm, DT for youth (10-18-years-old), and parental survey of sleep duration in the validation group. Results: On average, children wore an accelerometer for 8.3 days and 20.8 hours/day. Comparing the DT-identified bedrest with visual identification in the validation group yielded sensitivity = 0.941, specificity = 0.974, and accuracy = 0.956. The optimal block length was 36 min, the threshold 230 counts/min, the bedrest-start trigger 305 counts/min, and the bedrest-end trigger 1,129 counts/min. In the validation group, DT identified bedrest with greater accuracy than Sadeh's algorithm (0.956 and 0.902) and DT for youth (0.956 and 0.861) (both P<0.001). Both DT (564±77 min/day) and Sadeh's algorithm (604±80 min/day) identified significantly less bedrest/sleep than parental survey (650±81 min/day) (both P<0.001). Conclusions: The DT-based algorithm initially developed for youth was adapted for preschool children to identify time spent in bedrest with high accuracy. The DT is available as a package for the R open-source software environment ("PhysActBedRest"). [ABSTRACT FROM AUTHOR]

Sport is becoming increasingly competitive and athletes are being exposed to greater physical demands, leaving them prone to injuries. Monitoring athletes with the use of wearable technology could provide a way to potentially manage training and competition loads and reduce injuries. One such technology is the VERT inertial measurement unit, a commercially available discrete wearable device containing a 3-axis accelerometer, 3-axis gyroscope and 3-axis magnetometer. Some of the main measurement outputs include jump count, jump height and landing impacts. While several studies have examined the accuracy of the VERT's measures of jump height and jump count, landing impact force has not yet been investigated. The objective of this research study was to explore the validity of the VERT landing impact values. We hypothesized that the absolute peak VERT acceleration values during a jump-land cycle would fall within 10% of the peak acceleration values derived simultaneously from a research-grade accelerometer (Shimmer). Fourteen elite university-level volleyball players each performed 10 jumps while wearing both devices simultaneously. The results showed that VERT peak accelerations were variable (limits of agreement of -84.13% and 52.37%) and had a propensity to be lower (mean bias of -15.88%) when compared to the Shimmer. In conclusion, the validity of the VERT device's landing impact values are generally poor, when compared to the Shimmer. [ABSTRACT FROM AUTHOR]

Objective: This study examined the association between ActiGraph accelerometer output and energy expenditure across different speeds of walking in persons with Parkinson's disease (PD), and further generated cut-points that represent a metric for quantifying time spent in moderate-to-vigorous physical activity (MVPA) among persons with PD. Methods: The sample included 30 persons with mild-to-moderate PD (Hoehn and Yahr stages 2–3) and 30 adults without PD matched by sex and age. All participants completed 5 minutes of quiet, seated rest and then underwent three, 6-minute bouts of walking on a treadmill at three different speeds relative to the individual's self-selected pace. Activity counts were measured using an ActiGraph accelerometer worn at the waist level on the least affected side for persons with PD and the dominant side for controls. The rate of oxygen consumption, or energy expenditure, was measured using a portable, open-circuit spirometry system. Results: Our results indicated a strong association between activity counts and energy expenditure for persons with PD (R2 = 0.87) and controls (R2 = 0.89). However, the significant difference in slopes resulted in a lower cut-point of 1,354 counts·min-1 for persons with PD than the cut-point of 2,010 counts·min-1 for controls. Conclusion: Our results support the application of the disease-specific cut-point for quantifying the amount of time spent in MVPA using ActiGraph accelerometers among persons with mild-to-moderate PD. Such an application may provide accurate estimates of MVPA in this population, and better inform future research examining the possible determinants and consequences of physical activity as well as testing of interventions for changing MVPA in PD. [ABSTRACT FROM AUTHOR]

Background: Studies have shown a positive correlation between higher physical activity (PA) and health benefits. However, device-based assessment of PA and sedentary time (ST) in people with adolescent idiopathic scoliosis (AIS) has not been deeply investigated. Objective: Analysis and comparison of weekend and weekdays PA and ST using multiple accelerometers in people with AIS with different curvature severity compared to healthy controls. Methods: 24 participants with AIS divided into 2 groups of 12 with Cobb angles < 40° and > 40°, along with 12 age and BMI matched healthy controls. Daily PA and ST during four consecutive days were measured using four tri-axial accelerometers. Clinical functional assessment was performed using the scoliosis research society (SRS-22) questionnaire. Results: The combined weekend and weekdays average daily step count was found to be 22% and 29% lower in the AIS groups with Cobb angle < 40° and > 40°, respectively, compared to the controls. The average ST was also reported to be 5% and 7% higher in the AIS groups with Cobb angle < 40° and > 40°, respectively, compared to the controls. The reported differences were significant in the AIS group with higher Cobb angle (p≤0.05). No significant differences in PA or ST were reported between the AIS groups based on curvature severity. Conclusions: Decreased PA and increased ST observed in patients with AIS may have long term health implications and may play a role in the disease process. The device-based assessment of PA to understand potential benefits in clinical practice is recommended. [ABSTRACT FROM AUTHOR]

Training prescription and monitoring of team-sport athletes rely on accurate quantification of player movement. Our aim was to determine the sensitivity, reliability and construct validity of measures derived from a wearable device incorporating Global Positioning System (GPS) and accelerometer technology to quantify the peak periods of rugby competition. Match movement data were collected from 30 elite and 30 sub-elite rugby union players across respective competitive seasons. Accelerometer and GPS measures were analysed using a rolling average to identify peak movement for epochs ranging from 5 to 600 seconds. General linear mixed modelling was used to quantify the effects of playing position and match-half on the peak movement and variabilities within and between players represented reliability of each measure. Mean positional differences and match-half changes were assessed via standardisation and magnitude-based decisions. Sensitivity of measures was quantified via evaluation of ("signal") and typical error of measurement ("noise"). GPS and accelerometer measures had poor sensitivity for quantifying peak movement across all epochs and both levels of rugby union competition (noise 4× to 5× the signal). All measures displayed correspondingly low reliability across most epochs and both levels of competition (ICC<0.50). Construct validity was evident in mean differences between playing positions and match halves that were consistent with expected activity profiles in rugby union. However, it was clear from the pattern of differences across epoch durations and levels of competition that GPS and accelerometer measures provided different information about player movement. The poor sensitivity and low reliability of GPS and accelerometer measures of peak movement imply that rugby union players need to be monitored across many matches to obtain adequate precision for assessing individuals. Although all measures displayed construct validity, accelerometers provided meaningful information additional to that of GPS. We recommend using accelerometers alongside GPS to monitor and prescribe match respresentative training. [ABSTRACT FROM AUTHOR]

Background: Single repetition, contraction-phase specific and total time-under-tension (TUT) are crucial mechano-biological descriptors associated with distinct morphological, molecular and metabolic muscular adaptations in response to exercise, rehabilitation and/or fighting sarcopenia. However, to date, no simple, reliable and valid method has been developed to measure these descriptors. Objective: In this study we aimed to test whether accelerometer data obtained from a standard smartphone placed on the weight stack can be used to extract single repetition, contraction-phase specific and total TUT. Methods: Twenty-two participants performed two sets of ten repetitions of their 60% one repetition maximum with a self-paced velocity on nine commonly used resistance exercise machines. Two identical smartphones were attached on the resistance exercise weight stacks and recorded all user-exerted accelerations. An algorithm extracted the number of repetitions, single repetition, contraction-phase specific and total TUT. All exercises were video-recorded. The TUT determined from the algorithmically-derived mechano-biological descriptors was compared with the video recordings that served as the gold standard. The agreement between the methods was examined using Limits of Agreement (LoA). The association was calculated using the Pearson correlation coefficients and interrater reliability was determined using the intraclass correlation coefficient (ICC 2.1). Results: The error rate of the algorithmic detection of single repetitions derived from two smartphones accelerometers was 0.16%. Comparing algorithmically-derived, contraction-phase specific TUT against video, showed a high degree of correlation (r>0.93) for all exercise machines. Agreement between the two methods was high on all exercise machines as follows: LoA ranged from -0.3 to 0.3 seconds for single repetition TUT (0.1% of mean TUT), from -0.6 to 0.3 seconds for concentric contraction TUT (7.1% of mean TUT), from -0.3 to 0.5 seconds for eccentric contraction TUT (4.1% of mean TUT) and from -1.9 to 1.1 seconds for total TUT (0.5% of mean TUT). Interrater reliability for single repetition, contraction-phase specific TUT was high (ICC > 0.99). Conclusion: Data from smartphone accelerometer derived resistance exercise can be used to validly and reliably extract crucial mechano-biological descriptors. Moreover, the presented multi-analytical algorithmic approach enables researchers and clinicians to reliably and validly report missing mechano-biological descriptors. [ABSTRACT FROM AUTHOR]

Background: The current international physical activity guidelines for health recommend children to engage in at least 60 minutes of moderate-to-vigorous physical activity (MVPA) daily. Yet, accurate prevalence estimates of physical activity levels of children are unavailable in many African countries due to the dearth of accelerometer-measured physical activity data. The aim of this study was to describe the prevalence and examine the socio-demographic correlates of accelerometer-measured physical activity among school-going children in Kampala city, Uganda. Methods: A cross-sectional study design was used to recruit a sample of 10–12 years old school-going children (n = 256) from 7 primary schools (3 public schools and 4 private schools) in Kampala city, Uganda. Sedentary time, light-intensity physical activity (LPA), moderate-intensity physical activity (MPA) and vigorous-intensity physical activity (VPA) were measured by accelerometers (ActiGraph GT3X+ [Pensacola, Florida, USA]) over a seven-day period. Socio-demographic factors were assessed by a parent/guardian questionnaire. Weight status was generated from objectively measured height and weight and computed as body mass index (BMI). Multi-level logistic regressions identified socio-demographic factors that were associated with meeting physical activity guidelines. Results: Children's sedentary time was 9.8±2.1 hours/day and MVPA was 56±25.7 minutes/day. Only 36.3% of the children (38.9% boys, 34.3% girls) met the physical activity guidelines. Boys, thin/normal weight and public school children had significantly higher mean daily MVPA levels. Socio-demographic factors associated with odds of meeting physical activity guidelines were younger age (OR = 0.68; 95% CI = 0.55–0.84), thin/normal weight status (OR = 4.08; 95% CI = 1.42–11.76), and socioeconomic status (SES) indicators such as lower maternal level of education (OR = 2.43; 95% CI = 1.84–3.21) and no family car (OR = 0.31; 95% CI = 0.17–0.55). Conclusion: Children spent a substantial amount of time sedentary and in LPA and less time in MVPA. Few children met the physical activity guidelines. Lower weight status, lower maternal education level and no family car were associated with meeting physical activity guidelines. Effective interventions and policies to increase physical activity among school-going children in Kampala, are urgently needed. [ABSTRACT FROM AUTHOR]

Objective: The objective of this study was to evaluate the responsiveness of the single item measure (SIM) to detect change in PA when compared to hip-worn accelerometry. A secondary aim was to provide further data on validity of the measure at a single time point. Methods: Validity of the SIM to determine the number of days of ≥30 minutes of accelerometer-derived moderate-to-vigorous physical activity (MVPA) was assessed in 120 participants (78% female, 19% male, 3% other; age: 46 ± 11 years). Analysis of change was based on change in the number of days that participants completed ≥30 minutes of MVPA determined by the SIM and accelerometry over two 7-day periods in 90 participants (age: 47±11 years). Accelerometer data were analysed as total minutes of MVPA per day (MVPA-total) and as sustained bouts of 10 minutes or more of MVPA (MVPA-bouts). Validity of the SIM to detect change in MVPA, using accelerometer data as the reference measurement, was examined through Spearman's correlation and agreement in classification of change between SIM and accelerometry. Responsiveness to change was assessed by standardised response means and Cohen's d. Results: Standardised response means for PA change were moderate for the SIM (0.77), MVPA-total (0.57) and MVPA-bouts (0.79). The correlation for change in number of days ≥30 minutes MVPA between the SIM and accelerometry were small to moderate (MVPA-total: r = 0.36 and MVP-bouts: r = 0.40). The SIM displayed moderate accuracy (60%-63%), using accelerometer data as the reference measurement, in detecting increases in days ≥30 minutes of MVPA. Conclusion: The SIM is a potentially useful assessment tool for evaluating change in MVPA, particularly when device-based measures or longer self-report measures are not feasible. [ABSTRACT FROM AUTHOR]

Background: A variety of wearable monitors are available for objectively assessing physical activity but there is a lack of established values for the activity intensity of MotionWatch8 (MW8) and a similar lack of studies on comparability across devices. Our study aimed to establish activity intensity cutpoints for the MW8 accelerometer in children, which are necessary to determine whether they are meeting physical activity guidelines. Methods: Children (n = 39, ages 9–13 years) were asked to wear two different accelerometers (MW8 and ActiGraph) simultaneously on the same dominant wrist as they performed different activities designed to mimic activities of variable intensity that a child might perform in a free-living environment. Linear regression and receiver operating characteristic (ROC) curves were performed to assess sensitivity and specificity of the identified MW8 intensity cutpoints compared to established ActiGraph cutpoints. Results: Mean values for each activity were positively correlated using the MW8 and ActiGraph monitors (r = 0.85, p<0.001). The optimal cutpoints for differentiating sedentary from light physical activity, light from moderate, and moderate from vigorous activity were ≤32 counts, ≥ 371.5 counts, and ≥ 859.5 counts per 30 seconds, respectively. Conclusions: Our study demonstrated the ability of MW8 to discriminate different intensity activities and provided the first cutoff values for researchers using the MW8 to measure physical activity patterns among children. [ABSTRACT FROM AUTHOR]

Background: Most population-based studies from Latin America have used questionnaires to measure physical activity (PA) and sedentary behaviors (SB). Low reliability and validity of the questionnaires has limited the capacity to examine associations between PA and health. The purpose of this study was to compare self-reported and accelerometer–measured PA and SB and their associations with body composition in Latin American countries. Methods: Data were obtained from the Latin American Study of Nutrition and Health (aged 15–65 years), collected from September 2014 to February 2015. PA and SB were assessed using the International Physical Activity Questionnaire (long version) and the Actigraph GT3X+ accelerometer. Outcomes of interest included: body mass index (BMI), waist (WC) and neck circumference (NC). We used the Pearson and intraclass correlation coefficient, Bland-Altman plots, and multilevel linear regression models. Results: Mean moderate-to-vigorous physical activity (MVPA) by accelerometer and IPAQ were 34.4 min/day (95% CI: 33.4 to 35.4) and 45.6 min/day (95% CI: 43.2 to 48.1), respectively. For SB (accelerometer and IPAQ) the means were 573.1 (95% CI: 568.2 to 577.9) and 231.9 min/day (95% CI: 225.5 to 238.3). MVPA, measured by the accelerometer was negatively associated with BMI (β = -1.95; 95% CI: -2.83 to -1.08), WC (β = -5.04; 95% CI: -7.18 to -2.89) and NC (β = -1.21; 95% CI: -1.79 to -0.63). The MVPA estimated through IPAQ was not significantly associated with any of the three outcome variables. SB, measured by the accelerometer, was positively associated with BMI (β = 0.26; 95% CI: 0.08 to 0.44) and WC (β = 0.48; 95% CI: 0.13 to 0.91). SB estimated through IPAQ was positively associated with NC only. Conclusions: Low correlation coefficients were observed for accelerometer-derived and IPAQ-reported estimates of PA and SB. Caution is advised when making comparisons between accelerometer-measured and self-reported PA and SB. Further, studies examining associations between movement and health should discuss the impact of PA and SB measurement methodology on the results obtained. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to analyze the effect of epoch length on intensity classification during continuous and intermittent activities. Methods: Ten active students exercised under controlled conditions on a treadmill for four 5-min bouts by combining two effort intensities (running and walking) and two physical activity (PA) patterns (continuous or intermittent). The testing session was designed to generate a known level of moderate to vigorous PA (MVPA) for each condition. These PA levels were used as criterion measures to compare with the accelerometer measures. Data obtained from the accelerometer were reintegrated into 1-sec, 10-sec, 30-sec and 60-sec epochs. Equivalence testing was used to examine measurement agreements between MVPA values obtained with the different epochs and the reference values. Mean absolute percent errors (MAPE) were also calculated to provide an indicator of overall measurement error. Results: During the intermittent conditions, only the value obtained with the 1-sec epoch was significantly equivalent to the reference value. With longer epochs the difference increased for both intermittent conditions but in an opposite way: with longer epochs, MVPA decreased during walking but increased during running. Regarding the measurement accuracy, the pattern of variations according to the epoch length selected during the intermittent conditions was identical between walking and running: MAPE increased with the increase in epoch length. MAPE remained low only for the 1-sec epoch (7.6% and 2.7% for walking and running, respectively), increased at 31.3% and 34% for the 10-sec epoch and until near 100% with the 30- and 60-sec epoch lengths. Conclusion: This study highlighted the misclassification of exercise intensity based on accelerometer measurement and described for the first time the extent and the direction of this misclassification. Moreover, we can confirm that the shorter epochs are more accurate to measure the real exercise intensity during intermittent PA whatever the intensity. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the concurrent validity of two different inertial measurement units for measuring spatiotemporal parameters during running on a treadmill, by comparing data with a high-speed video analysis (VA) at 1,000 Hz. Forty-nine endurance runners performed a running protocol on a treadmill at comfortable velocity (i.e., 3.25 ± 0.36 m.s-1). Those wearable devices (i.e., Stryd™ and RunScribe™ systems) were compared to a high-speed VA, as a reference system for measuring spatiotemporal parameters (i.e. contact time [CT], flight time [FT], step frequency [SF] and step length [SL]) during running at comfortable velocity. The pairwise comparison revealed that the Stryd™ system underestimated CT (5.2%, p < 0.001) and overestimated FT (15.1%, p < 0.001) compared to the VA; whereas the RunScribe™ system underestimated CT (2.3%, p = 0.009). No significant differences were observed in SF and SL between the wearable devices and VA. The intra class correlation coefficient (ICC) revealed an almost perfect association between both systems and high-speed VA (ICC > 0.81). The Bland-Altman plots revealed heteroscedasticity of error (r2 = 0.166) for the CT from the Stryd™ system, whereas no heteroscedasticity of error (r2 < 0.1) was revealed in the rest of parameters. In conclusion, the results obtained suggest that both foot pods are valid tools for measuring spatiotemporal parameters during running on a treadmill at comfortable velocity. If the limits of agreement of both systems are considered in respect to high-speed VA, the RunScribe™ seems to be a more accurate system for measuring temporal parameters and SL than the Stryd™ system. [ABSTRACT FROM AUTHOR]

Most species-climate models relate range margins to long-term mean climate but lack mechanistic understanding of the ecological or demographic processes underlying the climate response. We examined the case of a climatically limited edge-of-range population of a medium-sized grassland bird, for which climate responses may involve a behavioural trade-off between temperature stress and reproduction. We hypothesised that temperature will be a limiting factor for the conspicuous, male snort-call display behaviour, and high temperatures would reduce the display activity of male birds. Using remote tracking technology with tri-axial accelerometers we classified and studied the display behaviour of 17 free-ranging male little bustards, Tetrax tetrax, at 5 sites in the Iberian Peninsula. Display behaviour was related to temperature using two classes of Generalized Additive Mixed Models (GAMMs) at different temporal resolutions. GAMMs showed that temperature, time of the day and Julian date explained variation in display behaviour within the day, with birds snort-calling significantly less during higher temperatures. We also showed that variation in daily snort-call activity was related to average daytime temperatures, with our model predicting an average decrease in daytime snort-call display activity of up to 10.4% for the temperature increases projected by 2100 in this region due to global warming. For lekking birds and mammals undertaking energetically-costly displays in a warming climate, reduced display behaviour could impact inter- and intra-sex mating behaviour interactions through sexual selection and mate choice mechanisms, with possible consequences on mating and reproductive success. The study provides a reproducible example for how accelerometer data can be used to answer research questions with important conservation inferences related to the impacts of climate change on a range of taxonomic groups. [ABSTRACT FROM AUTHOR]

Low levels of physical activity in youth are an issue internationally, with the age related decline in levels over the adolescent period of particular concern. This study evaluated a multi-component school-based intervention (Y-PATH: Youth-Physical Activity Towards Health), focused on halting the age-related decline in physical activity of youth in early adolescence. A cluster randomized controlled trial in 20 post primary schools (10 control, 10 intervention) was conducted. Data were collected from all 20 schools at baseline (2013), and 12 months (2014), and from 10 of these schools (5 intervention) at 24 months (2015). The setting was mixed gender post primary schools residing in the greater area of Dublin, Ireland. Principals from each school were asked to nominate one first year class group attending their school in September 2013 to participate in the study (N = 564). Intervention schools implemented the Y-PATH whole school intervention, comprising teacher component, parent component, and PE component; while control schools continued with usual care. The main outcome measure was accelerometer derived average minutes of daily moderate to vigorous physical activity (MVPA). Data were analysed from October 2015 –November 2017. At baseline 490 participants were assessed (mean age 12.78y ± .42). Results of the multilevel regression analysis confirmed that there was a significant time intervention effect, and this was predominantly contributed by the difference between control and intervention groups within females. Findings support the case for national dissemination of the Y-PATH intervention so that the knowledge learned can be translated to routine practice in schools. [ABSTRACT FROM AUTHOR]

Introduction: Although numerous activity trackers have been validated in healthy populations, validation is lacking in chronic heart failure patients who normally walk at a slower pace, making it difficult for researchers and clinicians to implement activity monitors during physical activity interventions. Methods: Six consumer-level activity monitors were validated in a 3-day field study in patients with chronic heart failure and healthy individuals under free living conditions. Furthermore, the same devices were evaluated in a lab-based study during treadmill walking at speeds of 2.4, 3.0, 3.6, and 4.2 km·h-1. Concordance correlation coefficients (CCC) were used to evaluate the agreement between the activity monitors and the criterion, and mean absolute percentage errors (MAPE) were calculated to assess differences between each device and the criterion (MAPE <10% was considered as a threshold for validity). Results: In the field study of healthy individuals, all but one of the activity monitors showed a substantial correlation (CCC ≥0.95) with the criterion device and MAPE <10%. In patients with heart failure, the correlation of only two activity monitors (Garmin vívofit 3 and Withings Go) was classified as at least moderate (CCC ≥0.90) and none of the devices had MAPE <10%. In the lab-based study at speeds 4.2 and 3.6 km·h-1, all activity monitors showed substantial to almost perfect correlations (CCC ≥0.95) with the criterion and MAPE in the range 1%-3%. However, at slower speeds of 3.0 and 2.4 km·h-1, the accuracy of all devices substantially deteriorated: their correlation with the criterion decreased below 90% and their MAPE increased to 4–8% and 10–45%, respectively. Conclusions: Even though none of the tested activity monitors fall within arbitrary thresholds for validity, most of them perform reasonably well enough to be useful tools that clinicians can use to simply motivate chronic heart failure patients to walk more. [ABSTRACT FROM AUTHOR]

Sensor-based human activity recognition aims at detecting various physical activities performed by people with ubiquitous sensors. Different from existing deep learning-based method which mainly extracting black-box features from the raw sensor data, we propose a hierarchical multi-view aggregation network based on multi-view feature spaces. Specifically, we first construct various views of feature spaces for each individual sensor in terms of white-box features and black-box features. Then our model learns a unified representation for multi-view features by aggregating views in a hierarchical context from the aspect of feature level, position level and modality level. We design three aggregation modules corresponding to each level aggregation respectively. Based on the idea of non-local operation and attention, our fusion method is able to capture the correlation between features and leverage the relationship across different sensor position and modality. We comprehensively evaluate our method on 12 human activity benchmark datasets and the resulting accuracy outperforms the state-of-the-art approaches. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate the long-term performance of the SonRtip atrial lead. Background: To optimize atrioventricular and interventricular timing and thereby potentially improving cardiac resynchronization therapy (CRT) responder rates, a lead integrated technology and a cardioverter/defibrillator-based algorithm measuring peak endocardial acceleration have been introduced. Long-term performance of the atrial lead (SonRtip PS55D, Sorin/MicroPort CRM, Italy) embedded with such a sensor has not been reported so far. Methods: Between 2012 and 2018, 143 patients underwent implantation of the SonRtip atrial lead in four Austrian medical centers. Conventional bipolar atrial leads implanted during the same period in 526 patients receiving CRT were used as control cohort. Results: Among 669 patients included in the study, 10 (1.5%) showed increased atrial pacing thresholds and/or decreased atrial sensing amplitudes and/or sudden increase in atrial lead impedance (above 3000 Ω) after an uneventful early postoperative period. Seven (70%) of the malfunctioning leads were SonRtip leads (p <0.001). Lead replacement was needed in 4.2% of SonRtip leads (six out of 143) and in 0.38% of all other conventional atrial leads (two out of 526) (p <0.001). Because of unaltered atrial sensing properties, a wait and see strategy was chosen in two patients–one of them with a SonRtip lead. The implanted atrial lead in the latter person experienced a sudden increase in pacing threshold (4V/0.35ms). Conclusions: While short-term safety and stable technical performance of the SonRtip atrial lead could be confirmed, our study found an unexpectedly high malfunction rate over a longer follow-up period. [ABSTRACT FROM AUTHOR]

A limited number of studies have used objective measures to examine the associations between the built environment and physical activity (PA) among older adults. This study aimed to examine geographic information systems-derived neighborhood walkability attributes and accelerometer measured PA in older adults. Data were collected from 124 older Taiwanese adults aged over 60 years (mean age: 69.9). Adjusted multiple linear regression was performed to explore the associations between five neighborhood walkability factors (population density, street connectivity, sidewalk availability, access to destinations, and public transportation) and five metrics of accelerometer-measured physical activity (total PA, moderate-to-vigorous PA, light PA, long moderate-to-vigorous PA bouts, and daily step counts). After adjusting for potential confounders, we found that greater sidewalk availability was positively associated with daily step counts in older adults (β = 0.165; 95% confidence interval: 0.006, 0.412; P = 0.043). No associations between other neighborhood environment attributes and PA metrics were observed. In conclusion, high sidewalk availability in the neighborhood may be supportive for older adults’ daily step counts. Further longitudinal research is needed to establish the causality between the built environment and objectively measured PA in older adults. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to describe the physical demands during U18 elite basketball games according to the game quarter and to identify a smaller subset of variables and threshold scores that distinguish players’ physical performance in each quarter. Methods: Data was collected from ninety-four players who participated in the study (age: 17.4 ± 0.74 years; height: 199.0 ± 0.1 cm; body mass: 87.1 ± 13.1 kg) competing in the Euroleague Basketball Next Generation Tournament. Players’ movements during the games were measured using a portable local positioning system (LPS) (WIMU PRO®, Realtrack Systems SL, Almería, Spain) and included relative distance (total distance / playing duration), relative distance in established speed zones, high-intensity running (18.1–24.0 km·h-1) and sprinting (> 24.1 km·h-1). player load, peak speed (km·h-1) and peak acceleration (m·s-2) number of total accelerations and total decelerations, high intensity accelerations (> 2 m·s-2) and decelerations (< -2 m·s-2). Results: There was an overall decrease in distance covered, player load, number of high intensity accelerations and decelerations between the first and last quarter of the games in all playing positions. A classification tree analysis showed that the first quarter had much influence of distance covered (above 69.0 meters), distance covered <6.0 km·h-1 and accelerations (> 2 m·s-2), whereas the fourth quarter performance had much influence of distance covered (below 69.0) and distance covered 12.1–18.0 km·h-1. Conclusions: A significant reduction in physical demands occurs during basketball, especially between first and last quarter for players in all playing positions during basketball games of under 18 elite players. [ABSTRACT FROM AUTHOR]

Background: Mobile accelerometry is a powerful and promising option to capture long-term changes in gait in both clinical and real-world scenarios. Increasingly, gait parameters have demonstrated their value as clinical outcome parameters, but validation of these parameters in elderly patients is still limited. Objective: The aim of this study was to implement a validation framework appropriate for elderly patients and representative of real-world settings, and to use this framework to test and improve algorithms for mobile accelerometry data in an orthogeriatric population. Methods: Twenty elderly subjects wearing a 3D-accelerometer completed a parcours imitating a real-world scenario. High-definition video and mobile reference speed capture served to validate different algorithms. Results: Particularly at slow gait speeds, relevant improvements in accuracy have been achieved. Compared to the reference the deviation was less than 1% in step detection and less than 0.05 m/s in gait speed measurements, even for slow walking subjects (< 0.8 m/s). Conclusion: With the described setup, algorithms for step and gait speed detection have successfully been validated in an elderly population and demonstrated to have improved performance versus previously published algorithms. These results are promising that long-term and/or real-world measurements are possible with an acceptable accuracy even in elderly frail patients with slow gait speeds. [ABSTRACT FROM AUTHOR]

Background: Walking capacity tests are commonly used to evaluate interventions aiming at reducing walking impairment in people with multiple sclerosis (pwMS). However, their ecological validity has recently been questioned. The aim of the present study was to investigate the ecological validity of the 2- and 6-minutes walking tests (2MWT and 6MWT) and the timed 25-foot walk (T25FW) after 28 days of multidisciplinary inpatient rehabilitation (MIR) in pwMS using accelerometry. Methods: PwMS wore an accelerometer on 7 consecutive days within a 14-day period prior to MIR, performed 2/6MWT and T25FW at the beginning and at the end of MIR, followed by another 7 consecutive days of accelerometry. Results: Significant improvements in 2/6MWT and T25FW after MIR in a cohort of 76 pwMS (mean age = 47.9, SD 8.3 years) were overall correlated to a significant gain in everyday life mobility (total steps/day). However, the correlation was strongly dependent on pre-existing walking disability defined by EDSS and only pwMS with “mild” walking impairment (EDSS 2–3.5) were able to transfer benefits measurable by walking capacity tests into improved everyday life mobility, while pwMS with “moderate to severe” walking disability (EDSS 4–6.5) were not. Conclusion: Ecological validity of changes in walking capacity tests following MIR is strongly dependent on pre-existing walking impairment. [ABSTRACT FROM AUTHOR]

Introduction: Compositional data analysis is one appropriate method for co-dependent data, even when data are collected for a subdivision of the 24-hour period, such as the waking day. Objectives were to use compositional analyses to examine the combined and relative associations of sedentary time (ST), light-intensity physical activity (LPA), moderate-intensity physical activity (MPA), and vigorous-intensity physical activity (VPA) with cardiometabolic biomarkers in a representative sample of children and youth. Methods: This cross-sectional study included 2544 participants aged 6–17 years from the 2003–2006 United States National Health and Nutrition Examination Survey. ST (<100 counts per minute), LPA (100 counts per minute to <4 METs; Freedson age-specific equation), MPA (4 to <7 METs), and VPA (≥7 METs) were accelerometer-derived. Cardiometabolic biomarkers included waist circumference, body mass index (BMI) z-score, HDL-cholesterol, C-reactive protein, and blood pressure. Triglycerides, glucose, insulin, and LDL-cholesterol were measured in a fasting sub-sample of adolescents (n = 670). Compositional linear regression models were conducted. Results: The composition of ST, LPA, MPA, and VPA was significantly associated with BMI z-score, log waist circumference, systolic and diastolic blood pressure, HDL-cholesterol, and log plasma glucose (variance explained: 1–29%). Relative to the other three behaviors, VPA was negatively associated with BMI z-score (γVPA = -0.206, p = 0.005) and waist circumference (γVPA = -0.03, p = 0.001). Conversely, ST was positively associated with waist circumference (γST = 0.029, p = 0.013). ST and VPA were also positively associated with diastolic blood pressure (γST = 2.700, p = 0.018; γVPA = 1.246, p = 0.038), relative to the other behaviors, whereas negative associations were observed for LPA (γLPA = -2.892, p = 0.026). Finally, VPA was positively associated with HDL-cholesterol, relative to other behaviors (γVPA = 0.058, p<0.001). Conclusions: The ST and physical activity composition appears important for many aspects of cardiometabolic health in children and youth. Compositions with more time in higher-intensity activities may be better for some aspects of cardiometabolic health. [ABSTRACT FROM AUTHOR]

Orthostatic tremor (OT) is a rare movement disorder characterized by a fast tremor (13–18 Hz) in the lower extremities during stance. Patients with OT typically complain of instability while standing/walking. However, due to the geographical limitation, the standing instability or gait problems in patients with OT cannot be assessed and monitored frequently. The increasing popularity of using smartphone-based accelerometers could be a solution to eliminate this limitation. This study examined the feasibility of using smartphone-based accelerometers to identify the changes in body movement in different standing and locomotor tasks. Twenty patients with OT and seven healthy controls were consented to participate in this study. Subjects stood with eyes open or eyes closed for 20 seconds. They also performed four different locomotor tasks (normal walking, tandem walk, walking on an elevated surface, and obstacle negotiation). When performed different locomotor tasks, patients with OT had a larger acceleration of body movement than controls in the medial-lateral direction (tandem walk: p = 0.026, walking on an elevated surface: p = 0.002, and stepping over the obstacle: p = 0.028). Patients with OT had smaller acceleration of body movement than controls while standing with eyes open in the vertical direction (p = 0.012), in the anterior-posterior direction (p = 0.013) and in the medial-lateral direction (p = 0.011). This study provides objective evidence of balance instability in patients with OT not only while standing but also during different challenging locomotor tasks by using smartphone-based accelerometers. [ABSTRACT FROM AUTHOR]

Patterns of spatial behavior dictate how we use our infrastructure, encounter other people, or are exposed to services and opportunities. Understanding these patterns through the analysis of data commonly available through commodity smartphones has become an important arena for innovation in both academia and industry. The resulting datasets can quickly become massive, indicating the need for concise understanding of the scope of the data collected. Some data is obviously correlated (for example GPS location and which WiFi routers are seen). Codifying the extent of these correlations could identify potential new models, provide guidance on the amount of data to collect, and even provide actionable features. However, identifying correlations, or even the extent of correlation, is difficult because the form of the correlation must be specified. Fractal-based intrinsic dimensionality directly calculates the minimum number of dimensions required to represent a dataset. We provide an intrinsic dimensionality analysis of four smartphone datasets over seven input dimensions, and empirically demonstrate an intrinsic dimension of approximately two. [ABSTRACT FROM AUTHOR]

Objectives: Independently, physical activity (PA), sedentary behavior (SB), and sleep are related to the development and progression of chronic diseases. Less is known about how rest-activity behaviors cluster within individuals and how rest-activity behavior profiles relate to health. In this study we aimed to investigate if adult women cluster into profiles based on how they accumulate rest-activity behavior (including accelerometer-measured PA, SB, and sleep), and if participant characteristics and health outcomes differ by profile membership. Methods: A convenience sample of 372 women (mean age 55.38 + 10.16) were recruited from four US cities. Participants wore ActiGraph GT3X+ accelerometers on the hip and wrist for a week. Total daily minutes in moderate-to-vigorous PA (MVPA) and percentage of wear-time spent in SB was estimated from the hip device. Total sleep time (hours/minutes) and sleep efficiency (% of in bed time asleep) were estimated from the wrist device. Latent profile analysis (LPA) was performed to identify clusters of participants based on accumulation of the four rest-activity variables. Adjusted ANOVAs were conducted to explore differences in demographic characteristics and health outcomes across profiles. Results: Rest-activity variables clustered to form five behavior profiles: Moderately Active Poor Sleepers (7%), Highly Actives (9%), Inactives (41%), Moderately Actives (28%), and Actives (15%). The Moderately Active Poor Sleepers (profile 1) had the lowest proportion of whites (35% vs 78–91%, p < .001) and college graduates (28% vs 68–90%, p = .004). Health outcomes did not vary significantly across all rest-activity profiles. Conclusions: In this sample, women clustered within daily rest-activity behavior profiles. Identifying 24-hour behavior profiles can inform intervention population targets and innovative behavioral goals of multiple health behavior interventions. [ABSTRACT FROM AUTHOR]

Background: Objective methods to measure physical activity (PA) can lead to better cross-cultural comparisons, monitoring temporal PA trends, and measuring the effect of interventions. However, when applying this technology in field-work, the accelerometer data processing is prone to methodological issues. One of the most challenging issues relates to standardizing total wear time to provide reliable data across participants. It is generally accepted that at least 4 complete days of accelerometer wear represent a week for adults. It is not known if this same assumption holds true for pregnant women. Aim: We assessed the optimal number of days needed to obtain reliable estimates of overall PA and moderate-to-vigorous physical activity (MVPA) during the 2nd trimester in pregnancy using a raw triaxial wrist-worn accelerometer. Methods: Cross-sectional analyses were carried out in the antenatal wave of the 2015 Pelotas (Brazil) Birth Cohort Study. Participants wore the wrist ActiGraph wGT3X-BT accelerometer for seven consecutive days. The daily average acceleration, which indicated overall PA, was measured as milli-g (mg), and time spent in MVPA (minutes/day) was analyzed in 5-minute bouts. ANOVA and Kruskal-Wallis tests were used to compare variability across days of the week. Bland-Altman plots and the Spearman-Brown Prophecy Formula were applied to determine the reliability coefficient associated with one to seven days of measurement. Results: Among 2,082 pregnant women who wore the accelerometer for seven complete days, overall and MVPA were lower on Sundays compared to other days of the week. Reliability of > = 0.80 to evaluate overall PA was reached with at least three monitoring days, whereas seven days were needed to estimate reliable measures of MVPA. Conclusions: Our findings indicate that obtaining one week of accelerometry in adults is appropriate for pregnant women, particularly to obtain differences on weekend days and reliably estimate overall PA and MVPA. [ABSTRACT FROM AUTHOR]

Purpose: Video corroboration of player incurred impacts (PII) using trunk-worn wearable sensors (WS) among national ice-hockey team members. Methods: 23 members of the U.S. National (NTDP) U18 team consented to procedures approved by EMU Human Subjects Committee. Bioharness-3 (Zephyr, MD) WS recorded occurrences of PII during games and impacts were generated using Impact Processor (Zephyr, MD). Eight players with the top activity levels each game determined by WS, were observed using video and synchronized with game video collected by NTDP staff. Impacts identified by WS of 6–7.9 g (Z3), 8–9.9 g (Z4) and 10+ g (Z5) were used to corroborate PII. Magnitude and duration of each identified impact were compared by category using MANOVA with Tukey post hoc (α = 0.05; SPSS 22.0, IBM, NY). Results: Of 419 on-ice impacts, 358 were confirmed true PII (85.5%), 60 as other non-PII (14.3%) and 1 false positive (0.2%). For 358 PII, 17 (4.1%) were 1) Board contact/no check, 74 (17.7%), 2) Board contact/check, 202 (48.2%), 3) Open ice check, 65 (15.5%), 4) Player fall. Of 60 Non-PII, 19 (4.5%) as 5) other form of player to player event, 16 (3.8%) as 6) Hard Stop, 19 (4.5%) as 7) Slapshots and 6 (1.4%) as 8) other identifiable player events. 160 of the 200 Z3 events were PII (80%), 103 of 110 Z4 events (93.6%) and 95 of 109 Z5 events were PII (87.2%). The magnitude of impacts was not different by category, but the duration of category 6 (Hard stop; .058 s) was lower than categories 2, 4 and 7 (.112, .112, .133 s, respectively, p < .05). Conclusion: These data show that using some limited criteria (e.g. impact magnitude and duration), PII can be identified with relatively high accuracy in ice hockey using trunk-worn wearable sensors. [ABSTRACT FROM AUTHOR]

The advent of smartphones has advanced the use of embedded sensors to acquire various physiological information. For example, smartphone camera sensors and accelerometers can provide heart rhythm signals to the subjects, while microphones can give respiratory signals. However, the acquired smartphone-based physiological signals are more vulnerable to motion and noise artifacts (MNAs) compared to using medical devices, since subjects need to hold the smartphone with proper contact to the smartphone camera and lens stably and tightly for a duration of time without any movement in the hand or finger. This results in more MNA than traditional methods, such as placing a finger inside a tightly enclosed pulse oximeter to get PPG signals, which provides stable contact between the sensor and the subject’s finger. Moreover, a smartphone lens does not block ambient light in an effective way, while pulse oximeters are designed to block the ambient light effectively. In this paper, we propose a novel diversity method for smartphone signals that reduces the effect of MNAs during heart rhythm signal detection by 1) acquiring two heterogeneous signals from a color intensity signal and a fingertip movement signal, and 2) selecting the less MNA-corrupted signal of the two signals. The proposed method has advantages in that 1) diversity gain can be obtained from the two heterogeneous signals when one signal is clean while the other signal is corrupted, and 2) acquisition of the two heterogeneous signals does not double the acquisition procedure but maintains a single acquisition procedure, since two heterogeneous signals can be obtained from a single smartphone camera recording. In our diversity method, we propose to choose the better signal based on the signal quality indices (SQIs), i.e., standard deviation of instantaneous heart rate (STD–HR), root mean square of the successive differences of peak-to-peak time intervals (RMSSD–T), and standard deviation of peak values (STD–PV). As a performance metric evaluating the proposed diversity method, the ratio of usable period is considered. Experimental results show that our diversity method increases the usable period 19.53% and 6.25% compared to the color intensity or the fingertip movement signals only, respectively. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to investigate the hypothesized negative association between duration of work time spent at a high relative aerobic workload and leisure time movement behaviours among blue-collar workers. Methods: This was a cross-sectional study based on heart rate and accelerometer data from 803 blue-collar workers (447 men and 356 women). Relative aerobic workload was measured as percentage of heart rate reserve during work (%HRR). Leisure time movement behaviours were expressed in terms of leisure time spent in sedentary and active behaviours in uninterrupted bouts (i.e. <10 min, ≥10–30 min and >30 min). Compositional regression and isotemporal substitution models were used to assess the association between the predominance of work time spent at ≥40%HRR and leisure time spent in sedentary and active bouts. All analyses were stratified by sex. Results: For men, there was no statistically significant association between the predominance of work time spent at ≥40%HRR and leisure time movement behaviours. Among women, the predominance of ≥40%HRR at work was negatively associated with relative leisure time spent in ≥10 min bouts of active behaviour ( = -0.21, p = 0.02) and a theoretical 15 min reallocation of work time from <40%HRR to ≥40%HRR was estimated to decrease active behaviour by 6 min during leisure time. Conclusion: Our result highlights the need for considering work-related barriers for an active leisure time in high-risk populations. Longitudinal studies are warranted to disentangle the relationship between physically demanding work characteristics and leisure time movement behaviours in such populations. [ABSTRACT FROM AUTHOR]

Oral meloxicam is labelled for reducing pain and inflammation associated with castration in cattle in Canada, however, subcutaneous meloxicam is only labelled for pain associated with dis-budding and abdominal surgery. The aim of this project was to determine the pharmacokinetic profile of oral (PO; 1.0 mg/kg BW) and subcutaneous meloxicam (SC; 0.5 mg/kg BW), and to assess the effect of meloxicam on physiological and behavioural indicators of pain associated with knife castration in 7–8 month old calves. Twenty-three Angus crossbred beef calves (328 ± 4.4 kg BW) were randomly assigned to two treatments: PO n = 12 or SC n = 11 administration of meloxicam immediately before knife castration. Physiological parameters included salivary and hair cortisol, substance P, haptoglobin, serum amyloid-A, weight, complete blood count, scrotal and rectal temperature. Behavioural parameters included standing and lying behaviour, pen behaviour and feeding behaviour. Data were analyzed using PROC GLIMMIX (SAS), with repeated measures using mixed procedures including treatment as a fixed effect and animal and pen as a random effect. The pharmacokinetic profile of the drug including area under the curve, volume of distribution and clearance was greater (P < 0.05) in PO than SC calves. After surgery, substance P concentrations, white blood cell counts (WBC), weight and lying duration were greater (P < 0.05) in PO than SC calves, while scrotal circumference was lower (P < 0.05) in PO calves than SC calves. Although statistical differences were observed for pharmacokinetic, physiological and behavioural parameters differences were small and may lack biological relevance. [ABSTRACT FROM AUTHOR]

Background: Hospital stays are associated with high levels of sedentary behavior and physical inactivity. To objectively investigate physical behavior of hospitalized patients, these is a need for valid measurement instruments. The aim of this study was to assess the criterion validity of three accelerometers to measure lying, sitting, standing and walking. Methods: This cross-sectional study was performed in a university hospital. Participants carried out several mobility tasks according to a structured protocol while wearing three accelerometers (ActiGraph GT9X Link, Activ8 Professional and Dynaport MoveMonitor). The participants were guided through the protocol by a test leader and were recorded on video to serve as reference. Sensitivity, specificity, positive predictive values (PPV) and negative predictive values (NPV) were determined for the categories lying, sitting, standing and walking. Results: In total 12 subjects were included with a mean age of 49.5 (SD 21.5) years and a mean body mass index of 23.8 kg/m2 (SD 2.4). The ActiGraph GT9X Link showed an excellent sensitivity (90%) and PPV (98%) for walking, but a poor sensitivity for sitting and standing (57% and 53%), and a poor PPV (43%) for sitting. The Activ8 Professional showed an excellent sensitivity for sitting and walking (95% and 93%), excellent PPV (98%) for walking, but no sensitivity (0%) and PPV (0%) for lying. The Dynaport MoveMonitor showed an excellent sensitivity for sitting (94%), excellent PPV for lying and walking (100% and 99%), but a poor sensitivity (13%) and PPV (19%) for standing. Conclusions: The validity outcomes for the categories lying, sitting, standing and walking vary between the investigated accelerometers. All three accelerometers scored good to excellent in identifying walking. None of the accelerometers were able to identify all categories validly. [ABSTRACT FROM AUTHOR]

Introduction: The Ciclovía is a worldwide program in which streets are temporarily closed to motorized transport to create a space for recreation and outdoor play among children and adults. The aim of this study was to assess the associations between physical activity (PA), sedentary time (SED), body mass index and Ciclovía participation among children aged 9 to 13 years. Methods: All students in the 4th and 5th grades from the selected schools were invited to participate in the study. The study included 923 children. PA and SED were measured using waist-worn accelerometers, and height and weight were measured using standardized procedures. Ciclovía participation was self-reported. The analyses included multilevel linear, generalized mixed and generalized additive models. Results: The mean age of the sample was 10.1±0.7 years, and 49.5% were boys. In the last year, 46% of the children participated in the Ciclovía, and 34% reported participating frequently (at least once per month). No differences were found in the mean minutes of moderate-to-vigorous PA on weekdays between frequent Ciclovía users and sporadic and non-Ciclovía users (72 vs 69; p = 0.09). In contrast, frequent Ciclovía users had higher moderate-to-vigorous PA on Sundays than sporadic and non-Ciclovía users (65.6 vs 59.2; p = 0.01), specifically between the hours of 12:00 and 16:00. In addition, frequent Ciclovía users did not differ from the sporadic and non-Ciclovía users in SED (515.3 vs 521.3; p = 0.19). Frequent Ciclovía users had lower SED on Sundays than the sporadic and non-Ciclovía users (437.7 vs 456.5; p = 0.005). Additionally, frequent Ciclovía users were more likely to be overweight (28.3% vs 20.4% p = 0.01). We did not find differences in participation by sex, and low-to-middle income children were more likely to participate. Conclusions: The Ciclovías offer an innovative, inclusive recreational space and consequently provide opportunities to increase moderate-to-vigorous PA and reduce SED among children. [ABSTRACT FROM AUTHOR]

Digital public displays installed in various locations provide valuable information for the passers-by. However, the static characteristic of the digital public display limits the consumption of the displayed content to a small area. Personal mobile devices such as smartphones are now capable of interacting with digital public displays, which enables the passers-by to “take-away” the content and consume it on-the-go. This process requires device binding, content selection, and transfer between the two devices. In this paper, we propose a device binding method which utilizes the content brightness changing pattern as a unique content ID on the public display and an illuminance sensor on the mobile to bind and transfer between two devices. We conducted performance evaluations for binding algorithm robustness in different conditions. Also comparative studies among other binding interaction methods were conducted. Our results show that our proposed method performed stably across the various conditions and overall performance in interaction completion time and error rate was similar or superior to the existing methods. [ABSTRACT FROM AUTHOR]