Assessment of step accuracy using the Consumer Technology Association standard

Bunn, Jennifer; Jones, Caleb; Oliviera, A B; Webster, Michael J.

doi:10.1080/02640414.2018.1491941

Cited by 18 publications

(19 citation statements)

References 27 publications

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“…Accuracy was assessed for each device within each activity via mean bias, mean absolute percent error (MAPE), Bland-Altman analysis, an equivalence test, and intraclass correlation coefficient (ICC) using the two-way mixed model and absolute agreement in IBM SPSS (IBM Statistics version 26.0, Armonk, NY, USA). This analysis is consistent with previous literature employing multiple testing methods when aiming to prove that data are the same [6,14,20,21]. Equivalence tests were conducted using the two-one-sided-tests method with Jamovi statistical software [22].…”

Section: Methodssupporting

confidence: 71%

“…These standards provide guidance for researchers to evaluate research-grade devices as well as commercial devices used by the lay public. Since the CTA released their standards for protocol and validation, researchers have begun to acknowledge them in their designs for step count [6][7][8][9], and HR [10][11][12]. However, only limited studies have actually implemented these standards [6].…”

Section: Introductionmentioning

confidence: 99%

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Assessing Heart Rate Using Consumer Technology Association Standards

et al. 2021

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It is difficult for developers, researchers, and consumers to compare results among emerging wearable technology without using a uniform set of standards. This study evaluated the accuracy of commercially available wearable technology heart rate (HR) monitors using the Consumer Technology Association (CTA) standards. Participants (N = 23) simultaneously wore a Polar chest strap (criterion measure), Jabra Elite earbuds, Scosche Rhythm 24 armband, Apple Watch 4, and Garmin Forerunner 735 XT during sitting, activities of daily living, walking, jogging, running, and cycling, totaling 57 min of monitored activity. The Apple Watch mean bias was within ±1 bpm, and mean absolute percent error (MAPE) was <3% in all six conditions. Garmin underestimated HR in all conditions, except cycling and MAPE was >10% during sedentary, lifestyle, walk-jog, and running. The Jabra mean bias was within ±5 bpm for each condition, and MAPE exceeded 10% for walk-jog. The Scosche mean bias was within ±1 bpm and MAPE was <5% for all conditions. In conclusion, only the Apple Watch Series 4 and the Scosche Rhythm 24 displayed acceptable agreement across all conditions. By employing CTA standards, future developers, researchers, and consumers will be able to make true comparisons of accuracy among wearable devices.

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Section: Methodssupporting

confidence: 71%

Section: Introductionmentioning

confidence: 99%

Assessing Heart Rate Using Consumer Technology Association Standards

et al. 2021

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“…An et al [45], on the other hand, found higher validity for this device ( r range .4-.7). Bunn et al [46] tested the Polar A360 and also found it to have low validity (r range –.24 to .49). In addition, 4 studies compared steps in free-living populations.…”

Section: Discussionmentioning

confidence: 99%

Validity of the Polar M430 Activity Monitor in Free-Living Conditions: Validation Study

Henriksen¹,

Grimsgaard²,

Horsch³

et al. 2019

JMIR Form Res

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Background Accelerometers, often in conjunction with heart rate sensors, are extensively used to track physical activity (PA) in research. Research-grade instruments are often expensive and have limited battery capacity, limited storage, and high participant burden. Consumer-based activity trackers are equipped with similar technology and designed for long-term wear, and can therefore potentially be used in research. Objective We aimed to assess the criterion validity of the Polar M430 sport watch, compared with 2 research-grade instruments (ActiGraph and Actiheart), worn on 4 different locations using 1- and 3-axis accelerometers. Methods A total of 50 participants wore 2 ActiGraphs (wrist and hip), 2 Actihearts (upper and lower chest position), and 1 Polar M430 sport watch for 1 full day. We compared reported time (minutes) spent in sedentary behavior and in light, moderate, vigorous, and moderate to vigorous PA, step counts, activity energy expenditure, and total energy expenditure between devices. We used Pearson correlations, intraclass correlations, mean absolute percentage errors (MAPEs), and Bland-Altman plots to assess criterion validity. Results Pearson correlations between the Polar M430 and all research-grade instruments were moderate or stronger for vigorous PA (r range .59-.76), moderate to vigorous PA (r range .51-.75), steps (r range .85-.87), total energy expenditure (r range .88-.94), and activity energy expenditure (r range .74-.79). Bland-Altman plots showed higher agreement for higher intensities of PA. MAPE was high for most outcomes. Only total energy expenditure measured by the hip-worn ActiGraph and both Actiheart positions had acceptable or close to acceptable errors with MAPEs of 6.94% (ActiGraph, 3 axes), 8.26% (ActiGraph, 1 axis), 14.54% (Actiheart, upper position), and 14.37% (Actiheart, lower position). The wrist-worn ActiGraph had a MAPE of 15.94% for measuring steps. All other outcomes had a MAPE of 22% or higher. For most outcomes, the Polar M430 was most strongly correlated with the hip-worn triaxial ActiGraph, with a moderate or strong Pearson correlation for sedentary behavior (r=.52) and for light (r=.7), moderate (r=.57), vigorous (r=.76), and moderate to vigorous (r=.75) PA. In addition, correlations were strong or very strong for activity energy expenditure (r=.75), steps (r=.85), and total energy expenditure (r=.91). Conclusions The Polar M430 can potentially be used as an addition to established research-grade instruments to collect some PA variables over a prolonged period. However, due to the high MAPE of most outcomes, only total energy expenditure can be trusted to provide close to valid results. Depending on the variable, the Polar M430 over- or underreported most metrics, and may therefore be better suited to report changes in PA over time for some outcomes, rather than as an accurate instrument for PA status in a population.

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“…(2) Considering the rather modest decreases in fat mass (−6.3 ± 7.8 to −10.7 ± 8.7%) in this cohort of overweight to obese women, it is unlikely that net energy deficiency truly fell within the range of about 650–700 kcal/day (i.e., ≈75.000 kcal/16 weeks). While physical activity was tracked by calibrated, valid devices and can be thus considered as a reliable outcome (Bunn et al, 2019), results on energy restriction as reported by the participants were dubious. Although we strictly emphasized a practicable protocol that focused on carbohydrate reduction only, extensively discussed the dietary protocol with the participants and contacted participants every second week to check compliance with the dietary recommendations, the majority of participants obviously “over-reported” their caloric restriction.…”

Section: Discussionmentioning

confidence: 99%

Effects of Whole-Body Electromyostimulation on the Energy-Restriction-Induced Reduction of Muscle Mass During Intended Weight Loss

et al. 2019

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Purpose: Overweight and obesity are an increasing problem worldwide. However, most studies that focus on weight reduction by energy restriction and/or aerobic exercise reported considerable loss of muscle mass as well. Increased protein intake and/or resistance exercise might inhibit this detrimental effect during a negative energy balance. Whole-body electromyostimulation (WB-EMS), a time effective, joint-friendly, and highly customizable training technology, showed similar hypertrophic effects compared with high-intensity resistance training. The aim of this study is to evaluate the effect of WB-EMS on body composition during negative energy balance with maintained/increased protein intake in overweight premenopausal women. Patients and Methods: Ninety premenopausal, 25–50-year-old, overweight women were randomly assigned to three groups ( n = 30 each). (1) Negative energy balance (−500 kcal/day) by energy restriction with compensatory protein intake (CG). (2) Negative energy balance (−500 kcal/day) by energy restriction (−250 kcal/day) and increased physical activity (−250 kcal/day) with increased protein intake (PA). (3) Negative energy balance (−500 kcal/day) due to energy restriction and increased physical activity with increased protein intake plus WB-EMS. The duration of the intervention was 16 weeks. Participants underwent restrictions in kcal per days and supplementation of protein (CG: 1.2 or PA/WB-EMS: 1.7 g/kg body mass/day) where needed. Bipolar WB-EMS was applied 1.5× week for 20 min (85 Hz; 350 μs; intermittent 6 s impulse, 4 s rest; rectangular). The primary study endpoint “lean body mass” (LBM) and secondary endpoint body fat mass (BFM) were assessed by bio-impedance analysis (BIA). Results: LBM decreased in the CG and PA group (CG: −113 ± 1,872 g; PA: −391 ± 1,832 g) but increased in the WB-EMS group (387 ± 1,769 g). However, changes were not significant ( p > 0.05). Comparing the groups by ANOVA, no significant differences were observed ( p = 0.070). However, pairwise adjusted comparisons determined significant differences between WB-EMS and PA ( p = 0.049). BFM decreased significantly ( p < 0.001) in all groups (CG: −2,174 ± 4,331 g; PA: −3,743 ± 4,237 g; WB-EMS: −3,278 ± 4,023 g) without any significant difference between the groups (ANOVA: p = 0.131). Conclusion: WB-EMS is an efficient, joint-friendly, and highly customizable training technology for maintaining muscle mass during energy restriction and can thus be considered as an alternative to more demanding resistance exercise protocols.

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Assessment of step accuracy using the Consumer Technology Association standard

Cited by 18 publications

References 27 publications

Assessing Heart Rate Using Consumer Technology Association Standards

Assessing Heart Rate Using Consumer Technology Association Standards

Validity of the Polar M430 Activity Monitor in Free-Living Conditions: Validation Study

Effects of Whole-Body Electromyostimulation on the Energy-Restriction-Induced Reduction of Muscle Mass During Intended Weight Loss

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