Effects of age, walking speed, and body composition on pedometer accuracy in children

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.     

Effects of Age,Walking Speed,and Body Composition on Pedometer Accuracy in Children

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.     

Waist Circumference,Pedometer Placement,and Step-Counting Accuracy in Youth

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.     

Concurrent validation of the Actigraph gt3x+, Polar Active accelerometer,Omron HJ-720 and Yamax Digiwalker SW-701 pedometer step counts in lab-based and free-living settings

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.     

Pedometer reliability, validity and daily activity targets among 10- to 15-year-old boys

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.     

Validity of the Actical activity monitor for assessing steps and energy expenditure during walking

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.     

Validity of Self-Reported Pedometer Steps per Day in College Students

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.     

Validity of the “Samsung Health” application to measure steps: A study with two different samsung smartphones

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.     

Validation of a one-day self-report questionnaire for physical activity assessment in healthy adults

Abstract

A self-report physical activity scale (PAS) has previously been developed to document physical activity (MET-hours) undertaken by adults during an average weekday. The current study aimed to validate the PAS over 24 hours via pedometer determinations of physical activity in healthy, active adults, and to determine possible influences of gender and body mass status on this relationship. One-hundred and seven healthy university students (age 18–41 years) wore a pedometer (Yamax DigiWalker SW-700) during the waking hours of an average weekday followed by successful completion of the PAS. Relationships between the PAS and pedometer measures (steps taken and energy expenditure) were examined by Pearson's correlation coefficients. Significant (P<0.05) gender and body mass status differences were examined by two-way analysis of variance with Tukey post-hoc tests. Participants reported 48.0±10.4 MET-hours of activity, completed 11,506±4195 steps, and expended 499±227 kcal during an average weekday. Physical activity measures, except energy expenditure, were similar across groups by gender and body mass status. The total number of MET-hours was significantly associated with pedometer steps taken (r=0.375–0.568, P<0.01), and this relationship varied by gender and to a lesser extent by body mass status. The results of the current study show that the self-reported physical activity of healthy active adults was in line with the popular recommended dose of daily physical activity (10,000 steps per day) and was not influenced by gender or body mass status. Furthermore, over an average weekday, the PAS provided a simple, quick, and valid method to document physical activity undertaken by young healthy active adults that is comparable to pedometer readings.     

Accuracy of three Android-based pedometer applications in laboratory and free-living settings

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.     

Lifesource XL-18 pedometer for measuring steps under controlled and free-living conditions

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.     

Comparison of three models of actigraph accelerometers during free living and controlled laboratory conditions

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.     

跳绳对提高不同性别大学生体能成绩的实验研究

以60名普通大学生为研究对象,在体育课中实施10周的跳绳运动干预,结果发现:在体育课中加入跳绳,不同性别的大学生实验后较实验前体能成绩明显提高;在同等负荷条件下,不同性别大学生心率下降,心肺功能均有所提高;男生1000m体能成绩的提高与4min跳绳有明显的相关,女生800m成绩的提高与4min跳绳不存在相关性。     

High Versus Low Theoretical Fidelity Pedometer Intervention Using Social-Cognitive Theory on Steps and Self-Efficacy

Purpose: This study was designed to compare a low versus high theoretical fidelity pedometer intervention applying social-cognitive theory on step counts and self-efficacy. Method: Fifty-six public university employees participated in a 10-week randomized controlled trial with 2 conditions that varied in theoretical fidelity. Participants in the high theoretical fidelity condition wore a pedometer and participated in a weekly group walk followed by a meeting to discuss cognitive-behavioral strategies targeting self-efficacy. Participants in the low theoretical fidelity condition met for a group walk and also used a pedometer as a motivational tool and to monitor steps. Step counts were assessed throughout the 10-week intervention and after a no-treatment follow-up (20 weeks and 30 weeks). Self-efficacy was measured preintervention and postintervention. Results: Participants in the high theoretical fidelity condition increased daily steps by 2,283 from preintervention to postintervention, whereas participants in the low fidelity condition demonstrated minimal change during the same time period (p = .002). Individuals attending at least 80% of the sessions in the high theoretical fidelity condition showed an increase of 3,217 daily steps (d = 1.03), whereas low attenders increased by 925 (d = 0.40). Attendance had minimal impact in the low theoretical fidelity condition. Follow-up data revealed that step counts were at least somewhat maintained. For self-efficacy, participants in the high, compared with those in the low, theoretical fidelity condition showed greater improvements. Conclusion: Findings highlight the importance of basing activity promotion efforts on theory. The high theoretical fidelity intervention that included cognitive-behavioral strategies targeting self-efficacy was more effective than the low theoretical fidelity intervention, especially for those with high attendance.     

Validity of the ActiGraph GT1M during walking and cycling

Abstract

The ActiGraph activity monitors have developed and newer versions of the ActiGraph accelerometers (GT1M, GT3X and GT3X +) are now available, including changes in hardware and software compared to the old version (AM7164). This is problematic as most of the validation and calibration work includes the AM7164. The aims of the study were to validate the ActiGraph GT1M during level and graded walking and to assess the potential underestimation of physical activity during cycling. Data were obtained from 20 participants during treadmill walking and ergometer cycling. Energy expenditure was measured via indirect calorimetry and used as the criterion method. Activity counts were highly correlated with energy expenditure during level walking (R² = 0.82) and graded walking at 5% and 8% (R² = 0.82 and R² = 0.67, respectively). There was no linear relationship between activity counts and energy expenditure during cycling. The average activity counts for all data points during cycling was 1,157 counts per minute (CPM) (SD = 974), and mean energy expenditure was 5.0 metabolic equivalents. The GT1M is a valid tool for assessing walking across a wide range of speeds and gradients. However, there is no relationship between activity counts and energy expenditure during cycling and physical activity is underestimated by ≈73% during cycling compared to walking.     

Walk this way: validity evidence of iphone health application step count in laboratory and free-living conditions

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.     

Evaluation of Low-Cost,Objective Instruments for Assessing Physical Activity in 10–11-Year-Old Children

This study compared step counts detected by four, low-cost, objective, physical-activity-assessment instruments and evaluated their ability to detect moderate-to-vigorous physical activity (MVPA) compared to the ActiGraph accelerometer (AG). Thirty-six 10–11-year-old children wore the NL-1000, Yamax Digiwalker SW 200, Omron HJ-151, and Walk4Life MVP concurrently with the AG during school hours on a single day. AG MVPA was derived from activity count data using previously validated cut points. Two of the evaluated instruments provided similar group mean MVPA and step counts compared to AG (dependent on cut point). Low-cost instruments may be useful for measurement of both MVPA and steps in children's physical activity interventions and program evaluation.     

Validity of the New Lifestyles NL-1000 Accelerometer for Measuring Time Spent in Moderate-to-Vigorous Physical Activity in School Settings

Current interest in promoting physical activity in the school environment necessitates an inexpensive, accurate method of measuring physical activity in such settings. Additionally, it is recognized that physical activity must be of at least moderate intensity in order to yield substantial health benefits. The purpose of the study, therefore, was to determine the validity of the New Lifestyles NL-1000 (New Lifestyles, Inc., Lee's Summit, Missouri, USA) accelerometer for measuring moderate-to-vigorous physical activity in school settings, using the Actigraph GT1M (ActiGraph, Pensacola, Florida, USA) as the criterion. Data were collected during a cross-country run (n = 12), physical education (n = 18), and classroom-based physical activities (n = 42). Significant and meaningful intraclass correlations between methods were found, and NL-1000 estimates of moderate-to-vigorous physical activity were not meaningfully different from GT1M-estimated moderate-to-vigorous physical activity. The NL-1000 therefore shows promising validity evidence as an inexpensive, convenient method of measuring moderate-to-vigorous physical activity in school settings.     

Validation of two accelerometers to determine mechanical loading of physical activities in children

The purpose of this study was to assess the validity of accelerometers using force plates (i.e., ground reaction force (GRF)) during the performance of different tasks of daily physical activity in children. Thirteen children (10.1 (range 5.4–15.7) years, 3 girls) wore two accelerometers (ActiGraph GT3X+ (ACT), GENEA (GEN)) at the hip that provide raw acceleration signals at 100 Hz. Participants completed different tasks (walking, jogging, running, landings from boxes of different height, rope skipping, dancing) on a force plate. GRF was collected for one step per trial (10 trials) for ambulatory movements and for all landings (10 trials), rope skips and dance procedures. Accelerometer outputs as peak loading (g) per activity were averaged. ANOVA, correlation analyses and Bland–Altman plots were computed to determine validity of accelerometers using GRF. There was a main effect of task with increasing acceleration values in tasks with increasing locomotion speed and landing height (P < 0.001). Data from ACT and GEN correlated with GRF (r = 0.90 and 0.89, respectively) and between each other (r = 0.98), but both accelerometers consistently overestimated GRF. The new generation of accelerometer models that allow raw signal detection are reasonably accurate to measure impact loading of bone in children, although they systematically overestimate GRF.     

Assessment of step accuracy using the Consumer Technology Association standard

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.