ArticleThe international journal of behavioral nutrition and physical activity2022
A catalog of validity indices for step counting wearable technologies during treadmill walking: the CADENCE-adults study.
Article in The international journal of behavioral nutrition and physical activity, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02650258 (Cadence and Intensity Across the Adult Lifespan), which is not on this map. Cited by 24 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Cadence and Intensity Across the Adult Lifespan
Who cites it
24 citing papers in PubMed, 2 syntheses or guidelines pooled it, 41 citations in OpenAlex.
- Effectiveness of Physical Activity Interventions Using Wearables and Smartphone Applications for Individuals With Cardiovascular Diseases and Stroke: A Systematic Review and Meta-Analysis.Journal of the American Heart Association · 2026Pooled it
- Current Knowledge about ActiGraph GT9X Link Activity Monitor Accuracy and Validity in Measuring Steps and Energy Expenditure: A Systematic Review.Sensors (Basel, Switzerland) · 2024Pooled it
- Evaluation of the implementation of a mobility plan in a geriatric clinic in Switzerland - a quality improvement study.BMC geriatrics · 2026Article
- Molecular Transducers of Physical Activity Consortium (MoTrPAC): Initial Insights into the Dynamic Human Responses to Exercise.bioRxiv : the preprint server for biology · 2026Article
- Unveiling age-differentiated pathways: spiritual well-being links to quality of life in breast cancer survivors through network analysis.Frontiers in public health · 2026Article
- Network Analysis of Social Anxiety, Avoidant Behavior, and Spiritual Well-Being in Breast Cancer Patients: A Pathway to Targeted Psychosocial Interventions.Depression and anxiety · 2026Article
- Article
- Sensors in Multiple Sclerosis.Current neurology and neuroscience reports · 2025Review
- Validation of an Open-Source Smartwatch for Continuous Monitoring of Physical Activity and Heart Rate in Adults.Sensors (Basel, Switzerland) · 2025Article
- Accurate measurement of simulated slow and altered walking activity: Apple Watch best in class wearable devices.PloS one · 2025Article
- Accelerometers can correctly count orthopaedic patients' early post-operative steps while using walking aids.Journal of experimental orthopaedics · 2025Article
- Comparison of Step-Based Metrics Under Laboratory and Free-Living Conditions in Femoroacetabular Impingement Syndrome.Journal of athletic training · 2024Article
- Agreement Between Apple Watch and Actical Step Counts in a Community Setting: Cross-Sectional Investigation From the Framingham Heart Study.JMIR biomedical engineering · 2024Article
- Device-assessed physical activity and sleep quality of post-COVID patients undergoing a rehabilitation program.BMC sports science, medicine & rehabilitation · 2024Article
- Physical activity and sleep changes among children during the COVID-19 pandemic.NPJ digital medicine · 2024Article
- Incorporating Wearable Technology for Enhanced Rehabilitation Monitoring after Hip and Knee Replacement.Sensors (Basel, Switzerland) · 2024Article
- Temporal Interactions between Maintenance of Cerebral Cortex Thickness and Physical Activity from an Individual Person Micro-Longitudinal Perspective and Implications for Precision Medicine.Journal of personalized medicine · 2024Article
- Validity of the Actigraph-GT9X accelerometer for measuring steps and energy expenditures in heart failure patients.PloS one · 2024Article
- Cadence (steps/min) and relative intensity in 61 to 85-year-olds: the CADENCE-Adults study.The international journal of behavioral nutrition and physical activity · 2023Article
- Accuracy and Reliability of a Suite of Digital Measures of Walking Generated Using a Wrist-Worn Sensor in Healthy Individuals: Performance Characterization Study.JMIR human factors · 2023Article
Corrections and comments
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Authors and funding
12 authors at 7 institutions in 2 countries.
Funding
Abstract
backgroundStandardized validation indices (i.e., accuracy, bias, and precision) provide a comprehensive comparison of step counting wearable technologies. PURPOSE: To expand a previously published child/youth catalog of validity indices to include adults (21-40, 41-60 and 61-85 years of age) assessed across a range of treadmill speeds (slow [0.8-3.2 km/h], normal [4.0-6.4 km/h], fast [7.2-8.0 km/h]) and device wear locations (ankle, thigh, waist, and wrist).
methodsTwo hundred fifty-eight adults (52.5 ± 18.7 years, 49.6% female) participated in this laboratory-based study and performed a series of 5-min treadmill bouts while wearing multiple devices; 21 devices in total were evaluated over the course of this multi-year cross-sectional study (2015-2019). The criterion measure was directly observed steps. Computed validity indices included accuracy (mean absolute percentage error, MAPE), bias (mean percentage error, MPE), and precision (correlation coefficient, r; standard deviation, SD; coefficient of variation, CoV).
resultsOver the range of normal speeds, 15 devices (Actical, waist-worn ActiGraph GT9X, activPAL, Apple Watch Series 1, Fitbit Ionic, Fitbit One, Fitbit Zip, Garmin vivoactive 3, Garmin vivofit 3, waist-worn GENEActiv, NL-1000, PiezoRx, Samsung Gear Fit2, Samsung Gear Fit2 Pro, and StepWatch) performed at < 5% MAPE. The wrist-worn ActiGraph GT9X displayed the worst accuracy across normal speeds (MAPE = 52%). On average, accuracy was compromised across slow walking speeds for all wearable technologies (MAPE = 40%) while all performed best across normal speeds (MAPE = 7%). When analyzing the data by wear locations, the ankle and thigh demonstrated the best accuracy (both MAPE = 1%), followed by the waist (3%) and the wrist (15%) across normal speeds. There were significant effects of speed, wear location, and age group on accuracy and bias (both p < 0.001) and precision (p ≤ 0.045).
conclusionsStandardized validation indices cataloged by speed, wear location, and age group across the adult lifespan facilitate selecting, evaluating, or comparing performance of step counting wearable technologies. Speed, wear location, and age displayed a significant effect on accuracy, bias, and precision. Overall, reduced performance was associated with very slow walking speeds (0.8 to 3.2 km/h). Ankle- and thigh-located devices logged the highest accuracy, while those located at the wrist reported the worst accuracy.
trial registrationClinicaltrials.gov NCT02650258. Registered 24 December 2015.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.