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1.
This study examined the validity of the Actical accelerometer step count and energy expenditure (EE) functions in healthy young adults. Forty-three participants participated in study 1. Actical step counts were compared to actual steps taken during a 200 m walk around an indoor track at self-selected pace and during treadmill walking at different speeds (0.894, 1.56 and 2.01 m · s–1) for 5 min. The Actical was also compared to three pedometers. For study 2, 15 participants from study 1 walked on a treadmill at their predetermined self-selected pace for 15 min. Actical EE was compared to EE measured by indirect calorimetry. One-way analysis of variance and t-tests were used to examine differences. There were no statistical difference between Actical steps and actual steps in self-selected pace walking and during treadmill walking at moderate and fast speeds. During treadmill walking at slow speed, the Actical step counts significantly under predicted actual steps taken. For study 2, there was no statistical difference between measured EE and Actical-recorded EE. The Actical provides valid estimates of step counts at self-selected pace and walking at constant speeds of 1.56 and 2.01 m · s–1. The Actical underestimates EE of walking at constants speeds ≥1.38 m · s–1.  相似文献   

2.
Abstract

The aim of this study was to compare the outputs of three commonly used uniaxial Actigraph models (Actitrainer, 7164 and GT1M) under both free-living and controlled laboratory conditions. Ten adults (mean age = 24.7±1.1 years) wore the three Actigraph models simultaneously during one of day free-living and during a progressive exercise protocol on a treadmill at speeds between 1.5 and 5.5 miles per hour (mph). During free-living the three Actigraph models produced comparable outputs in moderate, vigorous and moderate-to-vigorous physical activity (MVPA) with effect sizes typically <0.2, but lower comparability was seen in sedentary and light categories, as well as in total step counts (effect sizes often >0.30). In controlled conditions, acceptable comparability between the three models was seen at all treadmill speeds, the exception being walking at 1.5 mph (mean effect size = 0.48). It is concluded that care should be taken if different Actigraph models are to be used to measure and compare light physical activity, step counts and walking at very low speeds. However, using any of these three different Actigraph models to measure and compare levels of MVPA in free-living adults seems appropriate.  相似文献   

3.
Activity monitors are frequently used to assess activity in many settings. But as technology advances, so do the mechanisms used to estimate activity causing a continuous need to validate newly developed monitors. The purpose of this study was to examine the step count validity of the Yamax Digiwalker SW-701 pedometer (YX), Omron HJ-720 T pedometer (OP), Polar Active accelerometer (PAC) and Actigraph gt3x+ accelerometer (AG) under controlled and free-living conditions. Participants completed five stages of treadmill walking (n = 43) and a subset of these completed a 3-day free-living wear period (n = 37). Manually counted (MC) steps provided a criterion measure for treadmill walking, whereas the comparative measure during free-living was the YX. During treadmill walking, the OP was the most accurate monitor across all speeds (±1.1% of MC steps), while the PAC underestimated steps by 6.7–16.0% per stage. During free-living, the OP and AG counted 97.5% and 98.5% of YX steps, respectively. The PAC overestimated steps by 44.0%, or 5,265 steps per day. The Omron pedometer seems to provide the most reliable and valid estimate of steps taken, as it was the best performer under lab-based conditions and provided comparable results to the YX in free-living. Future studies should consider these monitors in additional populations and settings.  相似文献   

4.
Wearable activity trackers have become popular for tracking individual’s daily physical activity, but little information is available to substantiate the validity of these devices in step counts. Thirty-five healthy individuals completed three conditions of activity tracker measurement: walking/jogging on a treadmill, walking over-ground on an indoor track, and a 24-hour free-living condition. Participants wore 10 activity trackers at the same time for both treadmill and over-ground protocol. Of these 10 activity trackers three were randomly given for 24-hour free-living condition. Correlations of steps measured to steps observed were r?=?0.84 and r?=?0.67 on a treadmill and over-ground protocol, respectively. The mean MAPE (mean absolute percentage error) score for all devices and speeds on a treadmill was 8.2% against manually counted steps. The MAPE value was higher for over-ground walking (9.9%) and even higher for the 24-hour free-living period (18.48%) on step counts. Equivalence testing for step count measurement resulted in a significant level within ±5% for the Fitbit Zip, Withings Pulse, and Jawbone UP24 and within ±10% for the Basis B1 band, Garmin VivoFit, and SenseWear Armband Mini. The results show that the Fitbit Zip and Withings Pulse provided the most accurate measures of step count under all three different conditions (i.e. treadmill, over-ground, and 24-hour condition), and considerable variability in accuracy across monitors and also by speeds and conditions.  相似文献   

5.
This study examined whether differences in waist circumference (WC) and pedometer placement (anterior vs. midaxillary vs. posterior) affect the agreement between pedometer and observed steps during treadmill and self-paced walking. Participants included 19 pairs of youth (9–15 years old) who were matched for sex, race, and height and stratified by WC (high WC: HWC; low WC: LWC). Participants performed 3-min treadmill-walking trials at speeds of 59, 72, and 86 m·min-1 and a 400-m self-paced walking trial on level ground. Bland-Altman plots were used to assess the agreement between pedometer and observed steps of spring-levered pedometers by WC, pedometer placement, and walking speed. In the HWC group, the posterior pedometer placement consistently agreed most closely with observed steps at all treadmill speeds and during self-paced walking. In the LWC group, no single pedometer placement consistently agreed most closely with observed steps at all treadmill speeds and during self-paced walking. We conclude that a posterior pedometer placement improves step-count accuracy in most youth with an HWC at a range of walking speeds on level ground.  相似文献   

6.
The purpose of this study was to verify within- and between-day repeatability and variability in children's oxygen uptake (VO2), gross economy (GE; VO2 divided by speed) and heart rate (HR) during treadmill walking based on self-selected speed (SS). Fourteen children (10.1 ± 1.4 years) undertook three testing sessions over 2 days in which four walking speeds, including SS were tested. Within- and between-day repeatability were assessed using the Bland and Altman method, and coefficients of variability (CV) were determined for each child across exercise bouts and averaged to obtain a mean group CV value for VO2, GE, and HR per speed. Repeated measures analysis of variance showed no statistically significant differences in within- or between-day CV for VO2, GE, or HR at any speed. Repeatability within- and between-day for VO2, GE, and HR for all speeds was verified. These results suggest that submaximal VO2 during treadmill walking is stable and reproducible at a range of speeds based on children's SS.  相似文献   

7.
The aim of this study was to evaluate the utility of the RT3 accelerometer in young children, compare its accuracy with heart rate monitoring, and develop an equation to predict energy expenditure from RT3 output. Forty-two volunteers (mean age 12.2 years, s = 1.1) exercised at two horizontal and graded walking speeds (4 and 6 km.h(-1), 0% grade and 6% grade), and one horizontal running speed (8 km.h(-1), 0% grade), on a treadmill. Energy expenditure and oxygen consumption (VO2) served as the criterion measures. Comparison of RT3 estimates (counts and energy expenditure) demonstrated significant differences at 4, 6, and 8 km.h(-1) on level ground (P < 0.01), while no significant differences were noted between horizontal and graded walking at 4 and 6 km.h(-1). Correlation and regression analyses indicated no advantage of vector magnitude over the vertical plane (X) alone. A strong relationship between RT3 estimates and indirect calorimetry across all speeds was obtained (r = 0.633-0.850, P < 0.01). A child-specific prediction equation (adjusted R2 = 0.753) was derived and cross-validated that offered a valid energy expenditure estimate for walking/running activities. Despite recognized limitations, the RT3 may be a useful tool for the assessment of children's physical activity during walking and running.  相似文献   

8.
ABSTRACT

The activPAL is a widely-used measure of sedentary time but few studies have evaluated its ability to estimate physical activity intensity. This study determined the accuracy of the algorithm used by the activPAL to predict metabolic equivalents (METs) from cadence and a curvilinear cadence-METs equation individualized for height. Thirty-six healthy adults (25 ± 6 years) completed a progressive walking protocol. Stepping cadence was video recorded and METs were determined via indirect calorimetry. Manually-counted cadence was input into the activPAL and curvilinear equations. The internal activPAL equation overpredicted METs at slower cadences (<120 steps/minute) but underpredicted METs at faster cadences (>120 step/minute) (proportional bias, p < .001). Conversely, the curvilinear equation exhibited neither fixed (p = .37) nor proportional bias (p = .07), and a lower absolute MET difference [0.87 ± 0.65 (range:0.0–3.2) vs. 0.56 ± 0.45 (range:0.0–2.7) METs]. The linear activPAL equation poorly estimates METs from stepping cadence but these inaccuracies may be lessened through the use of an individualized curvilinear equation.  相似文献   

9.
This study examines the accuracy of three popular, free Android-based pedometer applications (apps), namely, Runtastic (RT), Pacer Works (PW), and Tayutau (TY) in laboratory and free-living settings. Forty-eight adults (22.5 ± 1.4 years) completed 3-min bouts of treadmill walking at five incremental speeds while carrying a test smartphone installed with the three apps. Experiment was repeated thrice, with the smartphone placed either in the pants pockets, at waist level, or secured to the left arm by an armband. The actual step count was manually counted by a tally counter. In the free-living setting, each of the 44 participants (21.9 ± 1.6 years) carried a smartphone with installed apps and a reference pedometer (Yamax Digi-Walker CW700) for 7 consecutive days. Results showed that TY produced the lowest mean absolute percent error (APE 6.7%) and was the only app with acceptable accuracy in counting steps in a laboratory setting. RT consistently underestimated steps with APE of 16.8% in the laboratory. PW significantly underestimated steps when the smartphone was secured to the arm, but overestimated under other conditions (APE 19.7%). TY was the most accurate app in counting steps in a laboratory setting with the lowest APE of 6.7%. In the free-living setting, the APE relative to the reference pedometer was 16.6%, 18.0%, and 16.8% for RT, PW, and TY, respectively. None of the three apps counted steps accurately in the free-living setting.  相似文献   

10.
Abstract

Two experiments were conducted to examine the accuracy of mechanical pedometers in walking and running. Groups of 20 volunteer subjects were used in each experiment. In experiment 1, subjects wore 4 identical pedometers on the waist during six 1-mile walks on a motor driven treadmill, two at each of 3 speeds: 2, 3, and 4 mph. Experiment 2 required subjects wearing 5 pedometers to perform two 1-mile walks at their own pace under each of two different conditions: (1) on a 400 meter track and (2) along a jogging path over a measured mile. These subjects also completed two 1-mile runs at their own pace over the same measured mile course. In both experiments, a two-way ANOVA with replicates showed significant effects of subjects, condition (speed), and subjects-condition interaction. Test-retest reliability coefficients ranged from ?0.13 to 0.81. Results of these studies indicate that the ability of the mechanical pedometer to measure distance is inconsistent. The findings indicate that pedometers are more accurate for some individuals than others. Also their accuracy varies with the speed of walking and is different for walking compared to running.  相似文献   

11.
Abstract

The purpose of this study was to compare the physiological responses of Nordic walking on a specially designed treadmill and Nordic walking on a level over-ground surface. Thirteen participants completed three 1-h Nordic walking training sessions. Following the training sessions, each participant performed two 1600-m over-ground Nordic walking trials at a self-selected pace. Each participant then completed two 1600-m Nordic walking treadmill trials on a Hammer Nordic Walking XTR Treadmill®, at the mean walking speed of their two over-ground Nordic walking trials. Breath-by-breath analysis of oxygen uptake ([Vdot]O2) and heart rate was performed during each trial. Caloric expenditure was calculated using the [Vdot]O2. Rating of perceived exertion (RPE) was assessed at the end of each trial. We found no significant differences in physiological variables collected during the two over-ground Nordic walking trials or the two treadmill Nordic walking trials. Mean walking speed was 106.96±11.49 m · min?1. Mean heart rate during treadmill walking (99±13 beats · min?1) was 22% lower than that during the over-ground condition (126±17 beats · min?1). Mean [Vdot]O2 and mean caloric expenditure were also lower during treadmill walking (15.18±3.81 ml · min?1 · kg?1, 0.08±0.02 kcal · min?1 · kg?1) than over-ground walking (24.16±4.89 ml · min?1 · kg?1, 0.12±0.02 kcal · min?1 · kg?1). Analysis of variance demonstrated that all variables were significantly higher during over-ground Nordic walking (P<0.001). A Mann-Whitney U-test demonstrated that the RPE for over-ground Nordic walking was greater than that for treadmill Nordic walking (P=0.02). Thus over-ground Nordic walking created a greater physiological stress than treadmill Nordic walking performed at the same speed and distance. The reason for this difference may have been the relatively narrow walking and poling decks on the treadmill, which made it difficult for the participants to place their poles correctly and maintain a consistent walking pattern. This would decrease the contribution of the arm muscles to overall oxygen consumption. In conclusion, the Hammer Nordic Walking XTR Treadmill® does not replicate the physiological stress of over-ground Nordic walking. Increasing the width of the decks could eliminate the discrepancy.  相似文献   

12.
ABSTRACT

The aims of this study were to estimate the walking cadence required to elicit a VO2reserve (VO2R) of 40% and determine if fitness status moderates the relationship between walking cadence and %VO2R. Twenty participants (10 male, mean(s) age 32(10) years; VO2max 45(10) mL·kg?1·min?1) completed resting and maximal oxygen consumption tests prior to 7 x 5-min bouts of treadmill walking at increasing speed while wearing an Apple Watch and measuring oxygen consumption continuously. The 7 x 5-min exercise bouts were performed at speeds between 3 and 6 km·h?1 with 5-min seated rest following each bout. Walking cadence measured at each treadmill speed was recorded using the Apple Watch “Activity” app. Using Bayesian regression, we predict that participants need a walking cadence of 138 to 140 steps·min?1 to achieve a VO2R of 40%. However, these values are moderated by fitness status such that those with lower fitness can achieve 40% VO2R at a slower walking cadence. The results suggest that those with moderate fitness need to walk at ~40% higher than the currently recommended walking cadence (100 steps·min?1) to elicit moderate-intensity physical activity. However, walking cadence required to achieve moderate-intensity physical activity is moderated by fitness status.  相似文献   

13.
The purpose of this study was to assess the accuracy of energy expenditure (EE) estimation and step tracking abilities of six activity monitors (AMs) in relation to indirect calorimetry and hand counted steps and assess the accuracy of the AMs between high and low fit individuals in order to assess the impact of exercise intensity. Fifty participants wore the Basis watch, Fitbit Flex, Polar FT7, Jawbone, Omron pedometer, and Actigraph during a maximal graded treadmill test. Correlations, intra-class correlations, and t-tests determined accuracy and agreement between AMs and criterions. The results indicate that the Omron, Fitbit, and Actigraph were accurate for measuring steps while the Basis and Jawbone significantly underestimated steps. All AMs were significantly correlated with indirect calorimetry, however, no devices showed agreement (p < .05). When comparing low and high fit groups, correlations between AMs and indirect calorimetry improved for the low fit group, suggesting AMs may be better at measuring EE at lower intensity exercise.  相似文献   

14.
Abstract

The primary objective of this study was to examine the relationship between heart rate intensity and pedometer step counts in adolescents. To determine cardiorespiratory fitness, 106 participants (47 boys, 59 girls, mean age 14.2 years, s = 0.8) completed the Queen's College Step Test and were classified as having low, moderate or high cardiorespiratory fitness. Adolescents also completed a 10-min treadmill trial while wearing a pedometer and heart rate monitor. The participants were instructed to maintain their heart rate between 65 and 75% of their maximum heart rate while running or walking on a treadmill. A heart rate of 65–75% maximum was associated with 146 steps per minute (s = 22) in boys and 137 steps per minute (s = 22) in girls. Results of analysis of variance indicated that there was a main effect for level of fitness (F 2,102 = 9.36, P < 0.001). The correlation between mean steps per minute and estimated maximum oxygen consumption was statistically significant (r = 0.44, P < 0.001). The results from this study suggest that a step rate of 130 steps per minute is equal to 65–75% maximum heart rate in low-fit adolescents and achieving 130 steps per minute could be used as an initial goal to improve fitness.  相似文献   

15.
We aimed to investigate the step-to-step spatiotemporal variables and ground reaction forces during the acceleration phase for characterising intra-individual fastest sprinting within a single session. Step-to-step spatiotemporal variables and ground reaction forces produced by 15 male athletes were measured over a 50-m distance during repeated (three to five) 60-m sprints using a long force platform system. Differences in measured variables between the fastest and slowest trials were examined at each step until the 22nd step using a magnitude-based inferences approach. There were possibly–most likely higher running speed and step frequency (2nd to 22nd steps) and shorter support time (all steps) in the fastest trial than in the slowest trial. Moreover, for the fastest trial there were likely–very likely greater mean propulsive force during the initial four steps and possibly–very likely larger mean net anterior–posterior force until the 17th step. The current results demonstrate that better sprinting performance within a single session is probably achieved by 1) a high step frequency (except the initial step) with short support time at all steps, 2) exerting a greater mean propulsive force during initial acceleration, and 3) producing a greater mean net anterior–posterior force during initial and middle acceleration.  相似文献   

16.
The purpose of this study was to compare the accuracy of commercially-available physical activity devices when walking and running at various treadmill speeds using CTA 2056: Physical Activity Monitoring for Fitness Wearables: Step Counting, standard by the Consumer Technology Association (CTA). Twenty participants (10 males and 10 females) completed self-paced walking and running protocols on the treadmill for five minutes each. Eight devices (Apple iWatch series 1, Fitbit Surge, Garmin 235, Moto 360, Polar A360, Suunto Spartan Sport, Suunto Spartan Trainer, and TomTom Spark 3) were tested two at a time, one per wrist. Manual step counts were obtained from video to serve as the benchmark. The mean absolute percent error (MAPE) was calculated during walking and running. During walking, three devices: Fitbit Surge (11.20%), Suunto Sport (22.93%), and TomTom (10.11%) and during running, one device, Polar (10.66%), exceeded the CTA suggestion of a MAPE < 10%. The Moto 360 had the lowest MAPE of all devices for both walking and running. The devices tested had higher step accuracy with running than walking, except for the Polar. Overall, the Apple iWatch series 1, Moto 360, Garmin, and Suunto Spartan Trainer met the CTA standard for both walking and running.  相似文献   

17.
Abstract

The aim of this study was to evaluate the utility of the RT3 accelerometer in young children, compare its accuracy with heart rate monitoring, and develop an equation to predict energy expenditure from RT3 output. Forty-two volunteers (mean age 12.2 years, s = 1.1) exercised at two horizontal and graded walking speeds (4 and 6 km · h?1, 0% grade and 6% grade), and one horizontal running speed (8 km · h?1, 0% grade), on a treadmill. Energy expenditure and oxygen consumption ([Vdot]O2) served as the criterion measures. Comparison of RT3 estimates (counts and energy expenditure) demonstrated significant differences at 4, 6, and 8 km · h?1 on level ground (P < 0.01), while no significant differences were noted between horizontal and graded walking at 4 and 6 km · h?1. Correlation and regression analyses indicated no advantage of vector magnitude over the vertical plane (X) alone. A strong relationship between RT3 estimates and indirect calorimetry across all speeds was obtained (r = 0.633–0.850, P < 0.01). A child-specific prediction equation (adjusted R 2 = 0.753) was derived and cross-validated that offered a valid energy expenditure estimate for walking/running activities. Despite recognized limitations, the RT3 may be a useful tool for the assessment of children's physical activity during walking and running.  相似文献   

18.
Physical activity benefits for disease prevention are well-established. Smartphones offer a convenient platform for community-based step count estimation to monitor and encourage physical activity. Accuracy is dependent on hardware–software platforms, creating a recurring challenge for validation, but the Apple iPhone® M7 motion co-processor provides a standardised method that helps address this issue. Validity of the M7 to record step count for level-ground, able-bodied walking at three self-selected speeds, and agreement with the StepWatchTM was assessed. Steps were measured concurrently with the iPhone® (custom application to extract step count), StepWatchTM and manual count. Agreement between iPhone® and manual/StepWatchTM count was estimated through Pearson correlation and Bland-Altman analyses. Data from 20 participants suggested that iPhone® step count correlations with manual and StepWatchTM were strong for customary (1.3 ± 0.1 m/s) and fast (1.8 ± 0.2 m/s) speeds, but weak for the slow (1.0 ± 0.1 m/s) speed. Mean absolute error (manual–iPhone®) was 21%, 8% and 4% for the slow, customary and fast speeds, respectively. The M7 accurately records step count during customary and fast walking speeds, but is prone to considerable inaccuracies at slow speeds which has important implications for certain patient groups. The iPhone® may be a suitable alternative to the StepWatchTM for only faster walking speeds.  相似文献   

19.
The objective of this study was to investigate the effects of age group, walking speed, and body composition on the accuracy of pedometer-determined step counts in children. Eighty-five participants (43 boys, 42 girls), ages 5-7 and 9-11 years, walked on a treadmill for two-minute bouts at speeds of 42, 66, and 90 m x min(-1) while wearing a spring-levered (Yamax SW-200) and a piezoelectric (New Lifestyles NL-2000) pedometer. The number of steps taken during each bout was also recorded using a hand counter Body mass index (BMI) was calculated from height and mass, and percentage of body fat (%BF) was determined using hand-to-foot bioelectrical impedance analysis. The tilt angle of the pedometer was assessed using a magnetic protractor. Both pedometers performed well at 66 and 90 m x min(-1), but undercounted steps by approximately 20% at 42 m x min(-1). Although age group, BMI, waist circumference, and %BF did not affect pedometer accuracy, children with large pedometer tilt angles (> or =10 degrees) showed significantly greater percent bias than those with small tilt angles (< 10 degrees). We suggest that the style of waistband on the child's clothing is a more important determinant of tilt angle and thus pedometer accuracy than body composition. Our results also indicate that the NL-2000 pedometer provides similar accuracy and better precision than the SW-200 pedometer, especially in children with large tilt angles. We conclude that fastening pedometers to a firm elastic belt may improve stability and reduce undercounting in young people.  相似文献   

20.
Walking is one of the preferred exercises among elderly, but could a prolonged walking increase gait variability, a risk factor for a fall in the elderly? Here we determine whether 30 min of treadmill walking increases coefficient of variation of gait in elderly. Because gait responses to exercise depend on fitness level, we included 15 sedentary and 15 active elderly. Sedentary participants preferred a lower gait speed and made smaller steps than the actives. Step length coefficient of variation decreased ~16.9% by the end of the exercise in both the groups. Stride length coefficient of variation decreased ~9% after 10 minutes of walking, and sedentary elderly showed a slightly larger step width coefficient of variation (~2%) at 10 min than active elderly. Active elderly showed higher walk ratio (step length/cadence) than sedentary in all times of walking, but the times did not differ in both the groups. In conclusion, treadmill gait kinematics differ between sedentary and active elderly, but changes over time are similar in sedentary and active elderly. As a practical implication, 30 min of walking might be a good strategy of exercise for elderly, independently of the fitness level, because it did not increase variability in step and stride kinematics, which is considered a risk of fall in this population.  相似文献   

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