992 resultados para activity monitor


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Purpose The purpose of this study was to evaluate the validity of the CSA activity monitor as a measure of children's physical activity using energy expenditure (EE) as a criterion measure. Methods Thirty subjects aged 10 to 14 performed three 5-min treadmill bouts at 3, 4, and 6 mph, respectively. While on the treadmill, subjects wore CSA (WAM 7164) activity monitors on the right and left hips. (V) over dot O-2 was monitored continuously by an automated system. EE was determined by multiplying the average (V) over dot O-2 by the caloric equivalent of the mean respiratory exchange ratio. Results Repeated measures ANOVA indicated that both CSA monitors were sensitive to changes in treadmill speed. Mean activity counts from each CSA unit were not significantly different and the intraclass reliability coefficient for the two CSA units across all speeds was 0.87. Activity counts from both CSA units were strongly correlated with EE (r = 0.86 and 0.87, P < 0.001). An EE prediction equation was developed from 20 randomly selected subjects and cross-validated on the remaining 10. The equation predicted mean EE within 0.01 kcal.min(-1). The correlation between actual and predicted values was 0.93 (P < 0.01) and the SEE was 0.93 kcal.min(-1). Conclusion These data indicate that the CSA monitor is a valid and reliable tool for quantifying treadmill walking and running in children.

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The unique physical and movement characteristics of children necessitate the development of accelerometer equations and cut points that are population specific. The purpose of this study is to develop an ecologically valid cut point for the Biotrainer Pro monitor that reflects a threshold for moderate-intensity physical activity in elementary school children. A sample of 30 children (ages 8-12) wore a Biotrainer monitor while completing a series of 7 movement tasks (calibration phase) and while participating in an organized group activity (cross-validation phase). Videotapes from each session were processed using a computerized direct-observation technique to provide a criterion measure of physical activity. Analyses involved the use of mixed-model regression and receiver operator characteristic (ROC) curves. The results indicated that a cut point of 4 counts/min provides the optimal balance between the related needs for sensitivity (accurately detecting activity) and specificity (limiting misclassification of activity as inactivity). Results with the cross-validation data demonstrated that this value yielded the best overall kappa (.58) and a high classification agreement (84%) for activity determination. The specificity of 93% demonstrates that the proposed cut point can accurately detect activity; however, the lower sensitivity value of 61% suggests that some minutes of activity might be incorrectly classified as inactivity. The cut point of 4 counts/min provides an ecologically valid cut point to capture physical activity in children using the Biotrainer Pro activity monitor.

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BACKGROUND: The new generation of activity monitors allow users to upload their data to the internet and review progress. The aim of this study is to validate the Fitbit Zip as a measure of free-living physical activity.

FINDINGS: Participants wore a Fitbit Zip, ActiGraph GT3X accelerometer and a Yamax CW700 pedometer for seven days. Participants were asked their opinion on the utility of the Fitbit Zip. Validity was assessed by comparing the output using Spearman's rank correlation coefficients, Wilcoxon signed rank tests and Bland-Altman plots. 59.5% (25/47) of the cohort were female. There was a high correlation in steps/day between the Fitbit Zip and the two reference devices (r = 0.91, p < 0.001). No statistically significant difference between the Fitbit and Yamax steps/day was observed (Median (IQR) 7477 (3597) vs 6774 (3851); p = 0.11). The Fitbit measured significantly more steps/day than the Actigraph (7477 (3597) vs 6774 (3851); p < 0.001). Bland-Altman plots revealed no systematic differences between the devices.

CONCLUSIONS: Given the high level of correlation and no apparent systematic biases in the Bland Altman plots, the use of Fitbit Zip as a measure of physical activity. However the Fitbit Zip recorded a significantly higher number of steps per day than the Actigraph.

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OBJECTIVES: This study aimed to validate SenseWear Mini software algorithm versions 2.2 (SW2.2) and 5.2 (SW5.2) for estimating energy expenditure (EE) in children. DESIGN: Laboratory-based validation study. METHODS: 57 children aged 5-12 y completed a protocol involving 15 semi-structured sedentary (SED), light-intensity (LPA), and moderate- to vigorous-intensity (MVPA) physical activities. EE was estimated using portable indirect calorimetry (IC). The accuracy of EE estimates (kcal·min(-1)) from SW2.2 and SW5.2 were examined at the group level and individual level using the mean absolute percentage error (MAPE), Bland-Altman plots and equivalence testing. RESULTS: MAPE values were lower for SW5.2 (30.1±10.7%) than for SW2.2 (44.0±6.2%). Although mean differences for SW5.2 were smaller than for SW2.2 during SED (-0.23±0.22 vs. -0.61±0.20kcal·min(-1)), LPA (-0.69±0.76 vs. -1.07±0.46kcal·min(-1)) and MVPA (-2.22±1.15 vs. -2.57±1.15kcal·min(-1)), limits of agreement did not decrease for the updated algorithms. For all activities, SW2.2 and SW5.2 were not equivalent to IC (p>0.05). Errors increased with increasing intensity. CONCLUSION: The current SenseWear Mini algorithms SW5.2 underestimated EE. The overall improved accuracy for SW5.2 was not accompanied with improved accuracy at the individual level and EE estimates were not equivalent to IC.

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The Achilles tendon has been seen to exhibit time-dependent conditioning when isometric muscle actions were of a prolonged duration, compared to those involved in dynamic activities, such as walking. Since, the effect of short duration muscle activation associated with dynamic activities is yet to be established, the present study aimed to investigate the effect of incidental walking activity on Achilles tendon diametral strain. Eleven healthy male participants refrained from physical activity in excess of the walking required to carry out necessary daily tasks and wore an activity monitor during the 24 h study period. Achilles tendon diametral strain, 2 cm proximal to the calcaneal insertion, was determined from sagittal sonograms. Baseline sonographic examinations were conducted at ∼08:00 h followed by replicate examinations at 12 and 24 h. Walking activity was measured as either present (1) or absent (0) and a linear weighting function was applied to account for the proximity of walking activity to tendon examination time. Over the course of the day the median (min, max) Achilles tendon diametral strain was −11.4 (4.5, −25.4)%. A statistically significant relationship was evident between walking activity and diametral strain (P < 0.01) and this relationship improved when walking activity was temporally weighted (AIC 131 to 126). The results demonstrate that the short yet repetitive loads generated during activities of daily living, such as walking, are sufficient to induce appreciable time-dependant conditioning of the Achilles tendon. Implications arise for the in vivo measurement of Achilles tendon properties and the rehabilitation of tendinopathy.

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The purpose of this review is to update expected values for pedometer-determined physical activity in free-living healthy older populations. A search of the literature published since 2001 began with a keyword (pedometer, "step counter," "step activity monitor" or "accelerometer AND steps/day") search of PubMed, Cumulative Index to Nursing & Allied Health Literature (CINAHL), SportDiscus, and PsychInfo. An iterative process was then undertaken to abstract and verify studies of pedometer-determined physical activity (captured in terms of steps taken; distance only was not accepted) in free-living adult populations described as ≥ 50 years of age (studies that included samples which spanned this threshold were not included unless they provided at least some appropriately age-stratified data) and not specifically recruited based on any chronic disease or disability. We identified 28 studies representing at least 1,343 males and 3,098 females ranging in age from 50–94 years. Eighteen (or 64%) of the studies clearly identified using a Yamax pedometer model. Monitoring frames ranged from 3 days to 1 year; the modal length of time was 7 days (17 studies, or 61%). Mean pedometer-determined physical activity ranged from 2,015 steps/day to 8,938 steps/day. In those studies reporting such data, consistent patterns emerged: males generally took more steps/day than similarly aged females, steps/day decreased across study-specific age groupings, and BMI-defined normal weight individuals took more steps/day than overweight/obese older adults. The range of 2,000–9,000 steps/day likely reflects the true variability of physical activity behaviors in older populations. More explicit patterns, for example sex- and age-specific relationships, remain to be informed by future research endeavors.

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This thesis studied technology’s role in promoting and supporting active lifestyles through behavioural strategies to reduce sedentary time and increase physical activity. The five studies included (1) development of a self-report instrument quantifying daily sedentary behaviour and light-intensity physical activity; (2) establishment of instrument validity and reliability; (3) use of an online personal activity monitor to successfully reduce sedentary time and increase physical activity; (4) identification of positive differences in total wellness as related to high/low levels of sitting time combined with insufficient/sufficient physical activity; and (5) improvement of total wellness through positive changes in sedentary behaviour and physical activity.

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Background The construct of total wellness includes a holistic approach to the body, mind and spirit components of life. While the health benefits of reducing sedentary behavior and increasing physical activity are well documented, little is known about the influence on total wellness of an internet-based physical activity monitor designed to help people to achieve higher physical activity levels. Purpose The purpose of this four-week, personal activity monitor-based intervention program was to reduce sedentary behavior and increase physical activity levels in daily living for sedentary adults and to determine if these changes would also be associated with improvement in total wellness. Methods Twenty-two men and 11 women (27 years ± 4.0) were randomly assigned to either an intervention (n = 18) or control group (n = 15). The intervention group interacted with an online personal activity monitor (Gruve Solution™) designed to reduce sedentary time and increase physical activity during activities of daily living. The control group did not interact with the monitor, as they were asked to follow their normal daily physical activities and sedentary behavior routines. The Wellness Evaluation of Lifestyle (WEL) inventory was used to assess total wellness. Sedentary time, light, walking, moderate and vigorous intensity physical activities were assessed for both intervention and control groups at baseline and at week-4 by the 7-day Sedentary and Light Intensity Physical Activity Log (7-day SLIPA Log) and the International Physical Activity Questionnaire (IPAQ). Results Significant increases in pre-post total wellness scores (from 64% ± 5.7 to 75% ± 8.5) (t (17) = -6.5, p < 0.001) were observed in the intervention group by the end of week four. Intervention participants decreased their sedentary time (21%, 2.3 hours/day) and increased their light (36.7%, 2.5 hours/day), walking (65%, 1057 MET-min/week), moderate (67%, 455 MET-min/week) and vigorous intensity (60%, 442 MET-min/week) physical activity (all p < 0.001). No significant differences for total wellness were observed between the groups at baseline and no pre-post significant differences were observed for any outcome variable in the control group. Conclusion Total wellness is improved when sedentary, but sufficiently physically active adults, reduce sedentary time and increase physical activity levels (i.e. light, walking, moderate and vigorous).

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Purpose The purpose of this study was to evaluate age and gender differences in objectively measured physical activity (PA) in a population-based sample of students in grades 1–12. Methods Participants (185 male, 190 female) wore a CSA 7164 accelerometer for 7 consecutive days. To examine age-related trends, students were grouped as follows: grades 1–3 (N = 90), grades 4–6 (N = 91), grades 7–9 (N = 96), and grades 10–12 (N = 92). Bouts of PA and minutes spent in moderate-to-vigorous PA (MVPA) and vigorous PA (VPA) were examined. Results Daily MVPA and VPA exhibited a significant inverse relationship with grade level, with the largest differences occurring between grades 1–3 and 4–6. Boys were more active than girls; however, for overall PA, the magnitudes of the gender differences were modest. Participation in continuous 20-min bouts of PA was low to nonexistent. Conclusion Our results support the notion that PA declines rapidly during childhood and adolescence and that accelerometers are feasible alternatives to self-report methods in moderately sized population-level surveillance studies.

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Purpose The purpose of this review is to address important methodological issues related to conducting accelerometer-based assessments of physical activity in free-living individuals. Methods We review the extant scientific literature for empirical information related to the following issues: product selection, number of accelerometers needed, placement of accelerometers, epoch length, and days of monitoring required to estimate habitual physical activity. We also discuss the various options related to distributing and collecting monitors and strategies to enhance compliance with the monitoring protocol. Results No definitive evidence exists currently to indicate that one make and model of accelerometer is more valid and reliable than another. Selection of accelerometer therefore remains primarily an issue of practicality, technical support, and comparability with other studies. Studies employing multiple accelerometers to estimate energy expenditure report only marginal improvements in explanatory power. Accelerometers are best placed on hip or the lower back. Although the issue of epoch length has not been studied in adults, the use of count cut points based on 1-min time intervals maybe inappropriate in children and may result in underestimation of physical activity. Among adults, 3–5 d of monitoring is required to reliably estimate habitual physical activity. Among children and adolescents, the number of monitoring days required ranges from 4 to 9 d, making it difficult to draw a definitive conclusion for this population. Face-to-face distribution and collection of accelerometers is probably the best option in field-based research, but delivery and return by express carrier or registered mail is a viable option. Conclusion Accelerometer-based activity assessments requires careful planning and the use of appropriate strategies to increase compliance.

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Purpose To evaluate the validity of a uniaxial accelerometer (MTI Actigraph) for measuring physical activity in people with acquired brain injury (ABI) using portable indirect calorimetry (Cosmed K4b(2)) as a criterion measure. Methods Fourteen people with ABI and related gait pattern impairment (age 32 +/- 8 yr) wore an MTI Actigraph that measured activity (counts(.)min-(1)) and a Cosmed K4b(2) that measured oxygen consumption (mL(.)kg(-1.)min(-1)) during four activities: quiet sitting (QS) and comfortable paced (CP), brisk paced (BP), and fast paced (FP) walking. MET levels were predicted from Actigraph counts using a published equation and compared with Cosmed measures. Predicted METs for each of the 56 activity bouts (14 participants X 4 bouts) were classified (light, moderate, vigorous, or very vigorous intensity) and compared with Cosmed-based classifications. Results Repeated-measures ANOVA indicated that walking condition intensities were significantly different (P < 0.05) and the Actigraph detected the differences. Overall correlation between measured and predicted METs was positive, moderate, and significant (r = 0.74). Mean predicted METs were not significantly different from measured for CP and BP, but for FP walking, predicted METs were significantly less than measured (P < 0.05). The Actigraph correctly classified intensity for 76.8% of all activity bouts and 91.5% of light- and moderate-intensity bouts. Conclusions Actigraph counts provide a valid index of activity across the intensities investigated in this study. For light to moderate activity, Actigraph-based estimates of METs are acceptable for group-level analysis and are a valid means of classifying activity intensity. The Actigraph significantly underestimated higher intensity activity, although, in practice, this limitation will have minimal impact on activity measurement of most community-dwelling people with ABI.

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In order to effectively measure the physical activity of children, objective monitoring devices must be able to quantify the intermittent and nonlinear movement of free play. The purpose of this study was to investigate the validity of the Computer Science and Applications (CSA) uniaxial accelerometer and the TriTrac-R3D triaxial accelerometer with respect to their ability to measure 8 "free-play" activities of different intensity. The activities ranged from light to very vigorous in intensity and included activities such as throwing and catching, hopscotch, and basketball. Twenty-eight children, ages 9 to 11, wore a CSA and a heart rate monitor while performing the activities. Sixteen children also wore a Tritrac. Counts from the CSA, Tritrac, and heart rates corresponding to the last 3 min of the 5 min spent at each activity were averaged and used in correlation analyses. Across all 8 activities, Tritrac counts were significantly correlated with predicted MET level (r= 0.69) and heart rate (r= 0.73). Correlations between CSA output, predicted MET level (0.43), and heart rate (0.64) were also significant but were lower than those observed for the Tritrac. These data indicate that accelerometers are an appropriate methodology for measuring children's free-play physical activities.