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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 primary aim was to examine the criterion and construct validity and test–retest reliability of the Lifesource XL-18 pedometer (A&D Medical, Toronto, ON, Canada) for measuring steps under controlled and free-living activities. The influence of body mass index, waist size and walking speed on the criterion validity of XL-18 was also explored. Forty adults (35–74 years) performed a 6-min walk test in the controlled condition, and the criterion validity of XL-18 was assessed by comparing it to steps counted manually. Thirty-five adults participated in the free-living condition and the construct validity of XL-18 was assessed by comparing it to Yamax SW-200 (YAMAX Health & Sports, Inc., San Antonio, TX, USA). During the controlled condition, XL-18 did not significantly differ from criterion (P > 0.05) and no systematic error was found using Bland–Altman analysis. The accuracy of XL-18 decreased with slower walking speed (P = 0.001). During the free-living condition, Bland–Altman analysis revealed that XL-18 overestimated daily steps by 327 ± 118 than Yamax (P = 0.004). However, the absolute percent error (APE) (6.5 ± 0.58%) was still within an acceptable range. XL-18 did not differ statistically between pant pockets. XL-18 is suitable for measuring steps in controlled and free-living conditions. However, caution may be required when interpreting the steps recorded under slower speeds and free-living conditions.  相似文献   

3.
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   

4.
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   

5.
The purpose of this study was to examine the validity of a highly popular pedometer application (Samsung Health). Sixteen adults (28.8 ± 8.9 years of age) wore two Samsung smartphone models, Samsung Galaxy Core Prime (SGCP) and Samsung Galaxy S4 (SGS4), at three body locations (waist, arm, and hand) while walking and running over a 50-m test. All trials were recorded using a video as a gold standard measure of step counts. Results indicated that the validity of Samsung Health varied depending on the smartphone model, its body location, and the type of gait (walking and running). Samsung Health showed acceptable validity when the SGCP was located on the hand (Bias = ?8.3%; RMSE = 5.6), and especially on the arm (Bias = ?7.2%; RMSE = 4.9) while running, and when the SGS4 was located on the arm (Bias = ?7.5%; RMSE = 5.4), and especially on the waist (Bias = 5.4%; RMSE = 3.7) while walking. Samsung Health only showed good validity when the SGS4 was located on the arm (Bias = 2.9%; RMSE = 3.6), and especially on the hand (Bias = 0.5%; RMSE = 2.5) while running. This application showed unacceptable validity in the remaining options.  相似文献   

6.
Supervised exercise has shown benefits for subjects with asthma, but little is known about the effectiveness of unsupervised physical activity on this population. We investigated the effects of a 12-week unsupervised pedometer-based physical activity program on daily steps and on clinical and psychological parameters of adults with asthma. Clinically stable adults with moderate to severe asthma were encouraged to take daily 30-minute walks and were randomized to pedometer and control groups. The pedometer group received pedometers and individualized daily step targets. Changes in daily steps (average of steps taken during six consecutive days), six-minute walk test (6MWT), health-related quality of life, asthma control and anxiety and depression levels were assessed 12 weeks after intervention and 24–28 weeks after randomization. Thirty-seven participants were recruited and 30 completed the intervention. At 12 weeks, the groups differed significantly in daily steps (adjusted average difference, 2488 steps; 95% confidence interval [CI], 803 to 4172; p = 0.005) and in the 6MWT (adjusted average difference, 21.9 m; 95% CI, 6.6 to 37.3; p = 0.006). These differences were not significant 24–28 weeks after randomization. The program was effective in increasing daily steps of adults with moderate to severe asthma 12 weeks after intervention.  相似文献   

7.
The purpose of this article was to examine the validity of self-reported pedometer steps/day. Forty-seven participants were provided a New Lifestyles NL-2000 (NL-2000; Lees Summit, MO, USA) pedometer and a physical activity (PA) diary for 3 weeks, but not informed of the data-storing capabilities. For weeks 2 and 3, each participant was given a step goal of 3,000 steps/day above week 1 average. A 2 × 3 repeated measures analysis of variance (ANOVA) was used to examine differences between reported steps/day. Bland–Altman plots assessed the mean bias and limits of agreement between reporting methods. Mean self-reported and NL-2000 steps/day were 9,264 ± 3,555 and 8,971 ± 3,590 steps/day (n = 26, p > .05). Mean biases were 216 ± 1,753 (week 1), –506 ± 1,355 (week 2), and –590 ± 1,360 (week 3) steps/day. Negative mean bias values indicate higher self-reported steps/day. Mean steps/day were similar between recording methods, but large differences were observed among individuals, suggesting self-reported steps/day may be valid for PA research at the population level, but not the individual level.  相似文献   

8.
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   

9.
ABSTRACT

The purpose of this study was to investigate the validity of a smartphone app to measure biomechanical barbell parameters during the snatch. Ten collegiate NCAA division I athletes performed two repetitions each at 40, 50, 60, 70, and 80% of their 1-repetition maximum snatch. Barbell motions were simultaneously recorded with a motion capture system and the smartphone app. The motion capture system recorded the 3-D position of a reflective marker attached to the end of the barbell while the smartphone app was used to record sagittal plane video and track the shape of the weight plate from which the barbell center was derived. Peak forward (PFD) and backward (PBD) displacements and peak vertical displacement (PVD) and velocity (PVV) were calculated from both sets of data. Significant, strong to very strong Pearson’s product-moment correlation coefficients between both systems were noted for all parameters (r = 0.729–0.902, all p < 0.001). Small significant biases between systems were observed for PVD (ES = 0.284, p < 0.001) and PFD (ES=0.340, p < 0.01), while trivial to small, non-significant biases were observed for PBD (ES = 0.143) and PVV (ES = –0.100). Collectively, the results suggest that the app can provide biomechanical data of barbell motions similar to a 3-D motion capture system.  相似文献   

10.
Our study investigated the performance of proximity sensor-based wear-time detection using the GT9X under laboratory and free-living settings. Fifty-two volunteers (23.2 ± 3.8 y; 23.2 ± 3.7 kg/m2) participated in either a laboratory or free-living protocol. Lab participants wore and removed a wrist-worn GT9X on 3–5 occasions during a 3-hour directly observed activity protocol. The 2-day free-living protocol used an independent temperature sensor and self-report as the reference to determine if wrist and hip-worn GT9X accurately determined wear (i.e., sensitivity) and non-wear (i.e., specificity). Free-living estimates of wear/non-wear were also compared to Troiano 2007 and Choi 2012 wear/non-wear algorithms. In lab, sensitivity and specificity of the wrist-worn GT9X in detecting total minutes of wear-on and off was 93% and 49%, respectively. The GT9X detected wear-off more often than wear-on, but with a greater margin of error (4.8 ± 11.6 vs. 1.4 ± 1.4 min). In the free-living protocol, wrist and hip-worn GT9X’s yielded sensitivity and specificity of 72 and 90% and 84 and 92%, respectively. GT9X estimations had inferior sensitivity but superior specificity to Troiano 2007 and Choi 2012 algorithms. Due to inaccuracies, it may not be advisable to singularly use the proximity-sensor-based wear-time detection method to detect wear-time.  相似文献   

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