首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到20条相似文献，搜索用时 15 毫秒
1.
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   

2.
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   

3.
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   

4.
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·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·min-1, but undercounted steps by approximately 20% at 42 m·min-1. Although age group, BMI, waist circumference, and %BF did not affect pedometer accuracy, children with large pedometer tilt angles (≥ 10°) showed significantly greater percent bias than those with small tilt angles (< 10°). 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   

5.
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   

6.
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   

7.
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   

8.
The aims of this study were to: (1) determine whether the number of pedometer counts recorded by adolescents differs according to the adiposity of the participant or location on the body; (2) assess the accuracy and reliability of pedometers during field activity; and (3) set adolescent pedometer-based physical activity targets. Seventy-eight 11- to 15-year-old Boy Scouts completed three types of activity: walking, fast walking and running. Each type was performed twice. Participants wore three pedometers and one activity monitor during all activities. Participants were divided into groups of normal weight (BMI < 85th percentile) and at risk of being overweight (BMI > or = 85th percentile). Intra-class correlations across the three activities indicated reliability (r = 0.51 - 0.92, P < 0.001). This conclusion was supported by narrow limits of agreement that were within a pre-set range that was practically meaningful. Multivariate analysis of covariance indicated adiposity group differences, but this difference was a function of the increased stature among the larger participants (P < 0.001). Ordinary least-squares regression models and multi-level regression models showed positive associations between the number of pedometer and activity monitor counts recorded by the three groups of participants during all activities (all P < 0.001). The mean number of counts recorded for all participants during the fast walk was 127 counts per minute. In conclusion, the pedometers provided an accurate assessment of adolescent physical activity, and a conservative estimate of 8000 pedometer counts in 60 min is equivalent to 60 min of moderate to vigorous physical activity.  相似文献   

9.
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   

10.
The purpose of this study was to determine the validity of the metabolic equivalent (MET) equation and step rate function of the ActivPAL? physical activity logger in a group of females. Using a standard treadmill protocol, 62 females aged 15-25 years walked on a treadmill at speeds between 3.2 and 7.0 km · h(-1) while wearing an ActivPAL. Oxygen consumption was measured using expired gas analysis at each speed and METs for each speed were estimated based on each participant's own resting metabolic rate. A sub-set of 18 participants also wore an Actigraph. Results showed that the in-built equation in the ActivPAL significantly underestimated (P < 0.001) METs under treadmill conditions at higher intensities. The ActivPAL equation is based on step rate yet the relationship between counts and measured METs (r = 0.76; P < 0.001) is stronger than that between steps and measured METs (r = 0.59; P < 0.001). Both the ActivPAL and Actigraph step functions showed no significant difference (P > 0.05) to video recorded step rate except at the slowest walking speed where the Actigraph significantly underestimated steps (P < 0.05). The development of a new equation based on the counts-METs relationship that includes a variety of speeds and activities would be useful. The ActivPAL step function performs better than the Actigraph at the slowest walking speed under treadmill conditions.  相似文献   

11.
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   

12.
Several attempts have been made to demonstrate the accuracy of the iPhone pedometer function in laboratory test conditions. However, no studies have attempted to evaluate evidence of convergent validity of the iPhone step counts as a surveillance tool in the field. This study takes a pragmatic approach to evaluating Health application derived iPhone step counts by measuring accuracy of a standardized criterion iPhone SE and a heterogeneous sample of participant owned iPhones (6 or newer) in a laboratory condition, as well as comparing personal iPhones to accelerometer derived steps in a free-living test. During lab tests, criterion and personal iPhones differed from manually counted steps by a mean bias of less than ±5% when walking at 5km/h, 7.5km/h and 10km/h on a treadmill, which is generally considered acceptable for pedometers. In the free-living condition steps differed by a mean bias of 21.5% or 1340 steps/day when averaged across observation days. Researchers should be cautioned in considering the use of iPhone models as a research grade pedometer for physical activity surveillance or evaluation, likely due to the iPhone not being continually carried by participants; if compliance can be maximized then the iPhone might be suitable.  相似文献   

13.
  相似文献   

14.
Integrating physical activity (PA) within a school curriculum is a promising approach for increasing PA in children. To date, no research has examined its effectiveness in increasing the low levels of PA witnessed in deprived South Asian (SA) children. The study aims to ascertain whether an integrated school-based curriculum and pedometer intervention could increase PA in children from deprived SA backgrounds. Following ethical approval and informed consent, 134 deprived SA children (63 boys, 71 girls, control (n?=?40, mean age?=?11.12 years, SD?=?0.32 years) and intervention (n?=?94, mean age?=?9.48 years, SD?=?0.62 years)) from a primary school in England, UK, completed a 6-week integrated PA intervention based on virtually walking from their school (middle of the country) to the coast and back (March–July 2013). Habitual PA was determined at baseline and post 6 weeks intervention for both groups, and determined weekly during the intervention in the experimental group. The results indicated that average daily steps were significantly higher at post 6 weeks compared to baseline for the intervention group (intervention mean change?=?8694 steps/day, SD?=?7428 steps/day vs. control mean change?=??1121 steps/day, SD?=?5592 steps/day, 95% CI of difference, 6726–7428 steps/day, P?=?.001, d?=?1.76). In addition, significant decreases in BF% and waist circumference were observed in the intervention group post 6 weeks (mean change for BF%?=??4.5%, mean change for WC?=??1.7?cm, P?=?.001). School-based integrated curriculum and pedometer interventions provide a feasible and effective mechanism for increasing habitual PA in primary school children from deprived SA backgrounds.  相似文献   

15.
Wireless sensing solutions that provide accurate long-term monitoring of walking and running gait characteristics in a real-world environment would be an excellent tool for sport scientist researchers and practitioners. The purpose of this study was to compare the performance of a body-worn wireless gyroscope-based gait analysis application to a marker-based motion capture system for the detection of heel-strike and toe-off and subsequent calculation of gait parameters during walking and running. The gait application consists of a set of wireless inertial sensors and an adaptive algorithm for the calculation of temporal gait parameters. Five healthy subjects were asked to walk and run on a treadmill at two different walking speeds (2 and 4?kph) and at a jogging (8?kph) and running (12?kph) speed. Data were simultaneously acquired from both systems. True error, percentage error and ICC scores indicate that the adaptive algorithm successfully calculated strides times across all speeds. However, results showed poor to moderate agreement for stance and swing times. We conclude that this gait analysis platform is valid for determining stride times in both walking and running. This is a useful application, particularly in the sporting arena, where long-term monitoring of running gait characteristics outside of the laboratory is of interest.  相似文献   

16.
The purpose of this study was to examine the accuracy of the SW-701 (Yamax Corporation, Tokyo, Japan) and NL-800 (New-Lifestyles, Inc., Lee's Summit, Missouri, USA) pedometer in fifth-grade students while walking, skipping, galloping, sliding, and hopping. Counts registered by both pedometer models were significantly lower than actual counts while skipping, galloping, and sliding, and counts from the NL-800 were significantly lower than the SW-701 during these same movements. No significant differences in step counts were detected between actual counts and the SW-701 and between the pedometer models while walking and hopping; however, the NL-800 registered counts significantly higher than actual counts while hopping. Bland–Altman plots suggest the greatest variability occurred while skipping, galloping, and sliding, with the percent error lowest in the SW-701 during these movements.  相似文献   

17.
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   

18.
Running on a treadmill is an activity that is novel to many people. Thus, a familiarisation period may be required before reliable and valid determinations of biomechanical parameters can be made. The current study investigated the time required for treadmill familiarisation under barefoot and shod running conditions. Twenty-six healthy men, who were inexperienced in treadmill running, were randomly allocated to run barefoot or shod for 20 minutes on a treadmill at a self-selected comfortable pace. Sagittal-plane kinematics for the ankle, knee and hip, and ground reaction force and spatio-temporal data were collected at two-minute intervals. For the barefoot condition, temporal differences were observed in peak hip flexion and peak knee flexion during swing. For the shod condition, temporal differences were observed for peak vertical ground reaction force. No temporal differences were observed after 8 minutes for either condition. Reliability analysis revealed high levels of consistency (ICC > 0.90) across all consecutive time-points for all dependent variables for both conditions after 8 minutes with the exception of maximal initial vertical ground reaction force loading rate. Participants in both barefoot and shod groups were therefore considered familiarised to treadmill running after 8 minutes.  相似文献   

19.
Ground reaction force measurements are a fundamental element of kinetic analyses of locomotion, yet they are traditionally constrained to laboratory settings or stationary frames. This study assessed the validity and reliability of a new wireless in-shoe system (Novel Loadsol/Pedoped) for field-based ground reaction force measurement in hopping, walking, and running. Twenty participants bilaterally hopped on a force plate and walked (5 km/hr) and ran (10 km/hr) on an instrumented treadmill on two separate days while wearing the insoles. GRFs were recorded simultaneously on each respective system. Peak GRF in hopping and peak GRF, contact time (CT), and impulse (IMP) in walking and running were compared on a per-hop and step-by-step basis. In hopping, the insoles demonstrated excellent agreement with the force plate (ICC: 0.96). In walking and running, the insoles demonstrated good-to-excellent agreement with the treadmill across all measures (ICCs: 0.88–0.96) and were reliable across sessions (ICCs within 0.00–0.03). A separate verification study with ten participants was conducted to assess a correction algorithm for further agreement improvement but demonstrated little meaningful change in systemic agreements. These results indicated that the Novel Loadsol system is a valid and reliable tool for wireless ground reaction force measurement in hopping, walking, and running.  相似文献   

20.
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   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号