scholarly journals How Well iPhones Measure Steps in Free-Living Conditions: Cross-Sectional Validation Study (Preprint)

2018 ◽  
Author(s):  
Shiho Amagasa ◽  
Masamitsu Kamada ◽  
Hiroyuki Sasai ◽  
Noritoshi Fukushima ◽  
Hiroyuki Kikuchi ◽  
...  
Keyword(s):  
Physical Activity ◽  
Linear Trend ◽  
Living Conditions ◽  
Step Count ◽  
Spearman Correlation ◽  
Free Living ◽  
Convenience Sample ◽  
Step Counts ◽  
Steps Per Day ◽  
Free Living Conditions

BACKGROUND Smartphones have great potential for monitoring physical activity. Although a previous laboratory-based study reported that smartphone apps were accurate for tracking step counts, little evidence on their accuracy in free-living conditions currently exists. OBJECTIVE We aimed to investigate the accuracy of step counts measured using iPhone in the real world. METHODS We recruited a convenience sample of 54 adults (mean age 31 [SD 10] years) who owned an iPhone and analyzed data collected in 2016 and 2017. Step count was simultaneously measured using a validated pedometer (Kenz Lifecorder) and the iPhone. Participants were asked to carry and use their own iPhones as they typically would while wearing a pedometer on the waist for 7 consecutive days during waking hours. To assess the agreement between the two measurements, we calculated Spearman correlation coefficients and prepared a Bland-Altman plot. RESULTS The mean step count measured using the iPhone was 9253 (3787) steps per day, significantly lower by 12% (1277/10,530) than that measured using the pedometer, 10,530 (3490) steps per day (P<.001). The Spearman correlation coefficient between devices was 0.78 (P<.001). The largest underestimation of steps by the iPhone was observed among those who reported to have seldom carried their iPhones (seldom carry: mean −3036, SD 2990, steps/day; sometimes carry: mean −1424, SD 2619, steps/day; and almost always carry: mean −929, SD 1443, steps/day; P for linear trend=.08). CONCLUSIONS Smartphones may be of practical use to individuals, clinicians, and researchers for monitoring physical activity. However, their data on step counts should be interpreted cautiously because of the possibility of underestimation due to noncarrying time.

scholarly journals Development of Step-Count Cut Points for School-Day Vigorous Physical Activity

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Ryan D. Burns ◽  
Timothy A. Brusseau ◽  
You Fu ◽  
Peng Zhang
Keyword(s):  
Physical Activity ◽  
Vigorous Physical Activity ◽  
Area Under The Curve ◽  
Roc Curves ◽  
Step Count ◽  
Convenience Sample ◽  
Cut Points ◽  
Step Counts ◽  
School Day ◽  
The Usa

Background. No study has established step-count cut points for varying amounts of accelerometer-assessed vigorous physical activity (VPA) accrued during the school day in children. The purpose of this study was to establish step-count cut points for discriminating children meeting VPA in 5 minutes, 10 minutes, 15 minutes, and 20 minutes per 7-hour school day. Methods. Participants were a convenience sample of 1,053 children (mean age = 8.4 (1.8) years) recruited from 5 schools from the Mountain West region of the USA. Data within students were observed across multiple semesters totaling 2,119 separate observations. Step counts and time in VPA were assessed using ActiGraph wGT3X-BT triaxial accelerometers that were worn during the entirety of a 7-hour school day for one school week. Average censored step counts and minutes in VPA were calculated across 3 to 5 days. Receiver operating characteristic (ROC) curves were employed to derive step counts via calculation of the maximum Youden J statistic. Results. Area-under-the-curve (AUC) scores ranged from AUC = 0.81 (95% CI: 0.78–0.83; p<0.001) for meeting at least 5 minutes of VPA to AUC = 0.94 (95% CI: 0.88–1.00, p<0.001) for meeting at least 20 minutes of VPA. Approximately 3,460 steps best discriminated children meeting at least 5 minutes of VPA (sensitivity = 74.0%, specificity = 74.0%, and accuracy = 74.1%) and approximately 5,628 steps best discriminated children meeting at least 20 minutes per day of VPA (sensitivity = 85.7%, specificity = 95.1%, and accuracy = 95.1%). Conclusion. Step counts can discriminate with reasonable accuracy children that meet at least 5 minutes of school-day VPA and with strong accuracy children that meet 20 minutes of school-day VPA.

Validity, Reliability and Sensitivity to Change of Three Consumer-grade Activity Trackers in Controlled and Free-living Conditions among Older Adults (Preprint)

2021 ◽  
Author(s):  
Kaja Kastelic ◽  
Marina Dobnik ◽  
Stefan Loefler ◽  
Christian Hofer ◽  
Nejc Šarabon
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Intraclass Correlation ◽  
Sleep Time ◽  
Living Conditions ◽  
Percentage Error ◽  
Sensitivity To Change ◽  
Free Living ◽  
Activity Trackers ◽  
Free Living Conditions

BACKGROUND Wrist worn consumer-grade activity trackers are popular devices, developed mainly for personal use, but with the potential to be used also for clinical and research purposes. OBJECTIVE The objective of this study was to explore the validity, reliability and sensitivity to change of movement behaviours metrics from three popular activity trackers (POLAR Vantage M, Garmin Vivosport and Garmin Vivoactive 4s) in controlled and free-living conditions when worn by older adults. METHODS Participants (n = 28; 74 ± 5 years) underwent a videotaped laboratory protocol while wearing all three activity trackers. On a separate occasion, participants wore one (randomly assigned) activity tracker and a research grade physical activity monitor ActiGraph wGT3X-BT simultaneously for six consecutive days for comparisons. RESULTS Both Garmin activity trackers showed excellent performance for step counts, with mean absolute percentage error (MAPE) below 20 % and intraclass correlation coefficient (ICC2,1) above 0.90 (P < .05), while Polar Vantage M substantially over counted steps (MAPE = 84 % and ICC2,1 = 0.37 for free-living conditions). MAPE for sleep time was within 10 % for all the trackers tested, while far beyond 20 % for all the physical activity and calories burned outputs. Both Garmin trackers showed fair agreement (ICC2,1 = 0.58–0.55) for measuring calories burned when compared with ActiGraph. CONCLUSIONS Garmin Vivoactive 4s showed overall best performance, especially for measuring steps and sleep time in healthy older adults. Minimal detectible change was consistently lower for an average day measures than for a single day measure, but still relatively high. The results provided in this study could be used to guide choice on activity trackers aiming for different purposes – individual use/care, longitudinal monitoring or in clinical trial setting.

scholarly journals The Choice of Pedometer Impacts on Daily Step Counts in Primary School Children under Free-Living Conditions

2019 ◽  
Vol 16 (22) ◽  
pp. 4375 ◽  
Author(s):  
Chiaki Tanaka ◽  
Yuki Hikihara ◽  
Shigeru Inoue ◽  
Shigeho Tanaka
Keyword(s):  
Primary School ◽  
School Children ◽  
Living Conditions ◽  
Primary School Children ◽  
Evidence Based ◽  
Daily Step ◽  
Free Living ◽  
Substantial Impact ◽  
Step Counts ◽  
Free Living Conditions

Background: We examined whether daily step counts under free-living conditions differed among four types of pedometers used by primary school children. Methods: In Study one, we compared the Yamax SW-200 (widely used in research) and the Kenz Lifecorder (accelerometer-based pedometer) in 30 children (6–12 years). In Study two, after confirming good correlation between these devices, we used Kenz Lifecorder as the criterion device and compared it with the Yamasa EX-200 (pants pocket-type pedometer) and the Omron Active style Pro (accelerometer-based pedometer) among 48 (7–12 years) or 108 children (7–12 years). Results: In Study one, comparable mean step counts between pedometers were observed. The correlation was strong (r = 0.91); the average difference between these two pedometers was +4.5%. In Study two, the average differences between Kenz Lifecorder and Yamasa EX-200 and Kenz Lifecorder and Omron Active style Pro were −7.9% and −18.2%, respectively, and those were not significantly equivalent according to the two one-sided-tests method. The correlations between Yamasa or Omron Active style Pro and Lifecorder were moderate and strong, respectively. Conclusions: The choice of pedometer had a substantial impact on step counts. A consensus on the appropriate pedometer for quantifying daily step counts is needed for evidence-based recommendations for health promotion.

Measuring Children’s Activity Levels: The Association Between Step-Counts and Activity Time

2006 ◽  
Vol 3 (2) ◽  
pp. 221-229 ◽  
Author(s):  
Aaron Beighle ◽  
Robert P. Pangrazi
Keyword(s):  
Physical Activity ◽  
Strong Association ◽  
Activity Levels ◽  
Activity Time ◽  
Free Living ◽  
Step Counts ◽  
Steps Per Day

Background:The primary purpose of this study was to describe the association between activity time and step counts in children.Methods:Subjects were 590 students (334 girls, 256 boys) with each gender having a mean age of 9.2 ± 1.8 y. All subjects wore the Walk4Life 2505 pedometer for four consecutive weekdays. This pedometer simultaneously measures both step counts and activity time.Results:Boys accumulated significantly more minutes of activity time/day (140.9 ± 39.6 vs. 126.3 ± 38.1), steps/day (13,348 ± 4131 vs. 11,702 ± 3923), and steps per min (93.99 ± 5.8 vs. 91.85 ± 5.8) than girls (P < 0.001) Steps/day was a significant predictor of activity time/day (P < 0.0001).Conclusions:Boys accumulate more steps per day and more activity time per day than girls. There is a strong association between steps per day and activity time in children. Daily steps per minute as a measure of free living physical activity in children is explored

Physical Activity Monitor Accuracy for Overground Walking and Free-Living Conditions Among Pregnant Women

2020 ◽  
Vol 3 (2) ◽  
pp. 100-109
Author(s):  
Christopher P. Connolly ◽  
Jordana Dahmen ◽  
Robert D. Catena ◽  
Nigel Campbell ◽  
Alexander H.K. Montoye
Keyword(s):  
Physical Activity ◽  
Pregnant Women ◽  
Living Conditions ◽  
Overground Walking ◽  
Third Trimester ◽  
Free Living ◽  
Activity Monitors ◽  
Step Counting ◽  
Physical Activity Monitors ◽  
Free Living Conditions

Purpose: We aimed to determine the step-count validity of commonly used physical activity monitors for pregnancy overground walking and during free-living conditions. Methods: Participants (n = 39, 12–38 weeks gestational age) completed six 100-step overground walking trials (three self-selected “normal pace”, three “brisk pace”) while wearing five physical activity monitors: Omron HJ-720 (OM), New Lifestyles 2000 (NL), Fitbit Flex (FF), ActiGraph Link (AG), and Modus StepWatch (SW). For each walking trial, monitor-recorded steps and criterion-measured steps were assessed. Participants also wore all activity monitors for an extended free-living period (72 hours), with the SW used as the criterion device. Mean absolute percent error (MAPE) was calculated for overground walking and free-living protocols and compared across monitors. Results: For overground walking, the OM, NL, and SW performed well (<5% MAPE) for normal and brisk pace walking trials, and also when trials were analyzed by actual speeds. The AG and FF had significantly greater MAPE for overground walking trials (11.9–14.7%). Trimester did affect device accuracy to some degree for the AG, FF, and SW, with error being lower in the third trimester compared to the second. For the free-living period, the OM, NL, AG, and FF significantly underestimated (>32% MAPE) actual steps taken per day as measured by the criterion SW (M [SD] = 9,350 [3,910]). MAPE for the OM was particularly high (45.3%). Conclusion: The OM, NL, and SW monitors are valid measures for overground step-counting during pregnancy walking. However, the OM and NL significantly underestimate steps by second and third trimester pregnant women in free-living conditions.

Assessment of Physical Activity Under Free-Living Conditions in Children

2004 ◽  
Vol 36 (Supplement) ◽  
pp. S329
Author(s):  
Jennifer L. Caputo ◽  
Richard S. Farley ◽  
Wayland Tseh
Keyword(s):  
Physical Activity ◽  
Living Conditions ◽  
Free Living ◽  
Free Living Conditions

scholarly journals Evaluations of Actiheart, IDEEA® and RT3 monitors for estimating activity energy expenditure in free-living women

2013 ◽  
Vol 2 ◽  
Author(s):  
Marie Löf ◽  
Hanna Henriksson ◽  
Elisabet Forsum
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Living Conditions ◽  
Reproductive Age ◽  
Women Of Reproductive Age ◽  
Free Living ◽  
Doubly Labelled Water ◽  
Further Development ◽  
Activity Energy ◽  
Free Living Conditions

AbstractActivity energy expenditure (AEE) during free-living conditions can be assessed using devices based on different principles. To make proper comparisons of different devices' capacities to assess AEE, they should be evaluated in the same population. Thus, in the present study we evaluated, in the same group of subjects, the ability of three devices to assess AEE in groups and individuals during free-living conditions. In twenty women, AEE was assessed using RT3 (three-axial accelerometry) (AEERT3), Actiheart (a combination of heart rate and accelerometry) (AEEActi) and IDEEA (a multi-accelerometer system) (AEEIDEEA). Reference AEE (AEEref) was assessed using the doubly labelled water method and indirect calorimetry. Average AEEActi was 5760 kJ per 24 h and not significantly different from AEEref (5020 kJ per 24 h). On average, AEERT3 and AEEIDEEA were 2010 and 1750 kJ per 24 h lower than AEEref, respectively (P < 0·001). The limits of agreement (± 2 sd) were 2940 (Actiheart), 1820 (RT3) and 2650 (IDEEA) kJ per 24 h. The variance for AEERT3 was lower than for AEEActi (P = 0·006). The RT3 classified 60 % of the women in the correct activity category while the corresponding value for IDEEA and Actiheart was 30 %. In conclusion, the Actiheart may be useful for groups and the RT3 for individuals while the IDEEA requires further development. The results are likely to be relevant for a large proportion of Western women of reproductive age and demonstrate that the procedure selected to assess physical activity can greatly influence the possibilities to uncover important aspects regarding interactions between physical activity, diet and health.

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