“What Is a Step?” Differences in How a Step Is Detected among Three Popular Activity Monitors That Have Impacted Physical Activity Research

John, Dinesh; Morton, Alvin L.; Arguello, Diego; Lyden, Kate; Bassett, David R.

doi:10.3390/s18041206

Cited by 57 publications

(65 citation statements)

References 42 publications

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“…Albeit being an obvious limitation, studies have shown that individuals to a large extent maintain their relative ranks within the population over time 8,9 . Furthermore, accelerometers have been shown to underestimate daily steps in frail older individuals, 29 potentially understating the amount of physical activity most beneficial for health in these populations 30 . Lastly, we only investigated associations between daily steps and all‐cause mortality.…”

Section: Discussionmentioning

confidence: 99%

Step by step: Association of device‐measured daily steps with all‐cause mortality—A prospective cohort Study

Hansen

Dalene

Ekelund

et al. 2020

Scandinavian Med Sci Sports

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Introduction Walking is free, does not require special training, and can be done almost everywhere. Therefore, walking is a feasible behavior on which to tailor public health messages. This study assesses the prospective association and dose‐response relationship between daily steps and all‐cause mortality. Materials and Methods Daily steps were measured by waist‐mounted accelerometers in 2183 individuals (53% women) for seven consecutive days at baseline (2008‐09). Participants were followed for a median period of 9.1 years and associations between steps and all‐cause mortality determined by registry linkage were assessed using Cox proportional hazard regression with adjustment for relevant covariates. Results Mean age was 57.0 (SD 10.9) years at baseline. Median (IQR) daily steps across ascending quartiles were 4651 (3495‐5325), 6862 (6388‐7350), 8670 (8215‐9186), and 11 467 (10 556‐13 110), respectively. During follow‐up, 119 individuals died (68% men). Higher number of daily steps was associated with a lower risk of all‐cause mortality with hazard ratios of 1.00 (referent), 0.52 (0.29‐0.93), 0.50 (0.27‐0.94), and 0.43 (0.21‐0.88) across ascending quartiles of daily steps in the multivariable‐adjusted model with follow‐up commencing 2 years after baseline. Risk differences per 1000 individuals for ascending quartiles were 6.8 (2.9‐9.3), 7.1 (0.8‐11.1), and 8.0 (1.7‐12.1), respectively. Conclusions Daily steps were associated with lower mortality risk in a non‐linear dose‐response pattern. The risk is almost halved when comparing the least active referent against the second quartile equivalent to a difference of about 2200 daily steps. Encouraging those least active to increase their daily steps may have substantial public health implications.

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Section: Discussionmentioning

confidence: 99%

Step by step: Association of device‐measured daily steps with all‐cause mortality—A prospective cohort Study

Hansen

Dalene

Ekelund

et al. 2020

Scandinavian Med Sci Sports

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“…Furthermore, the step-counting algorithms provided by various manufacturers are all proprietary and use different thresholds of acceleration to detect a step, which limits the comparability among studies using different devices. 73 Despite numerous validation studies showing that most commercially available accelerometers are more or less equal in general populations with normal gait, 74,75 other studies have reported that step-counting accuracy deteriorates in patients with chronic conditions, particularly during slower gait speeds. 58,76 As such, steps can still remain a useful self-monitoring metric for patients but should be avoided by researchers striving for high accuracy and reproducibility of their findings.…”

Section: Physical Activity Metricsmentioning

confidence: 99%

Advances in accelerometry for cardiovascular patients: a systematic review with practical recommendations

et al. 2020

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Aims Accelerometers are becoming increasingly commonplace for assessing physical activity; however, their use in patients with cardiovascular diseases is relatively substandard. We aimed to systematically review the methods used for collecting and processing accelerometer data in cardiology, using the example of heart failure, and to provide practical recommendations on how to improve objective physical activity assessment in patients with cardiovascular diseases by using accelerometers. Methods and results Four electronic databases were searched up to September 2019 for observational, interventional, and validation studies using accelerometers to assess physical activity in patients with heart failure. Study and population characteristics, details of accelerometry data collection and processing, and description of physical activity metrics were extracted from the eligible studies and synthesized. To assess the quality and completeness of accelerometer reporting, the studies were scored using 12 items on data collection and processing, such as the placement of accelerometer, days of data collected, and criteria for non-wear of the accelerometer. In 60 eligible studies with 3500 patients (of those, 536 were heart failure with preserved ejection fraction patients), a wide variety of accelerometer brands (n = 27) and models (n = 46) were used, with Actigraph being the most frequent (n = 12), followed by Fitbit (n = 5). The accelerometer was usually worn on the hip (n = 32), and the most prevalent wear period was 7 days (n = 22). The median wear time required for a valid day was 600 min, and between two and five valid days was required for a patient to be included in the analysis. The most common measures of physical activity were steps (n = 20), activity counts (n = 15), and time spent in moderate-to-vigorous physical activity (n = 14). Only three studies validated accelerometers in a heart failure population, showing that their accuracy deteriorates at slower speeds. Studies failed to report between one and six (median 4) of the 12 scored items, with non-wear time criteria and valid day definition being the most underreported items. Conclusions The use of accelerometers in cardiology lacks consistency and reporting on data collection, and processing methods need to be improved. Furthermore, calculating metrics based on raw acceleration and machine learning techniques is lacking, opening the opportunity for future exploration. Therefore, we encourage researchers and clinicians to improve the quality and transparency of data collection and processing by following our proposed practical recommendations for using accelerometers in patients with cardiovascular diseases, which are outlined in the article.

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“…For these monitors, bias was close to zero, indicating that they were producing similar results, and the 95% limits of agreement were small, suggesting that the hip-worn monitors could be used as an alternative to measure steps. Additionally, there were similar patterns in tri-axial counts, especially on the vertical axis where steps are calculated in the ActiLife step-counting algorithm [ 1 , 22 ].…”

Section: Discussionmentioning

confidence: 99%

“…One of the most commonly used activity monitor brands in physical activity research, ActiGraph has developed multiple generations of activity monitors [ 19 ]. Researchers have validated different ActiGraph activity monitors—including GT3X vs. GT1M [ 4 ], GT1M, GT3X, vs. GT3X+ [ 20 ], and recently, GT3X+ vs. GT9X [ 21 ]—placed at different sites such as hip vs. wrist [ 15 , 22 , 23 ] during various physical activities. Although a hip placement site has been validated as an ideal location for accurately measuring steps and physical activity level in regular physical activities [ 15 ], the evaluation of multiple placement sites (hip vs. wrist) in exergaming research is needed as more upper limb movements (unlike most regular physical activity) are required for exergaming [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

Application and Validation of Activity Monitors’ Epoch Lengths and Placement Sites for Physical Activity Assessment in Exergaming

Hwang

Fernandez

2018

JCM

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We assessed the agreement of two ActiGraph activity monitors (wGT3X vs. GT9X) placed at the hip and the wrist and determined an appropriate epoch length for physical activity levels in an exergaming setting. Forty-seven young adults played a 30-min exergame while wearing wGT3X and GT9X on both hip and wrist placement sites and a heart rate sensor below the chest. Intraclass correlation coefficient indicated that intermonitor agreement in steps and activity counts was excellent on the hip and good on the wrist. Bland-Altman plots indicated good intermonitor agreement in the steps and activity counts on both placement sites but a significant intermonitor difference was detected in steps on the wrist. Time spent in sedentary and physical activity intensity levels varied across six epoch lengths and depended on the placement sites, whereas time spent from a 1-s epoch of the hip-worn monitors most accurately matched the relative exercise intensity by heart rate. Hip placement site was associated with better step-counting accuracy for both activity monitors and more valid estimation of physical activity levels. A 1-s epoch was the most appropriate epoch length to detect short bursts of intense physical activity and may be the best choice for data processing and analysis in exergaming studies examining intermittent physical activities.

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“What Is a Step?” Differences in How a Step Is Detected among Three Popular Activity Monitors That Have Impacted Physical Activity Research

Cited by 57 publications

References 42 publications

Step by step: Association of device‐measured daily steps with all‐cause mortality—A prospective cohort Study

Step by step: Association of device‐measured daily steps with all‐cause mortality—A prospective cohort Study

Advances in accelerometry for cardiovascular patients: a systematic review with practical recommendations

Application and Validation of Activity Monitors’ Epoch Lengths and Placement Sites for Physical Activity Assessment in Exergaming

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