Stepping up with GGIR: Validity of step cadence derived from wrist-worn research-grade accelerometers using the verisense step count algorithm

The Verisense Step Count Algorithm facilitates generation of steps from wrist-worn accelerometers. Based on preliminary evidence suggesting a proportional bias with overestimation at low steps/day, but underestimation at high steps/day, the algorithm parameters have been revised. We aimed to establi...

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Veröffentlicht in:Journal of sports sciences Jg. 40; H. 19; S. 2182 - 2190
Hauptverfasser: Rowlands, Alex V., Maylor, Benjamin, Dawkins, Nathan P., Dempsey, Paddy C., Edwardson, Charlotte L., Soczawa-Stronczyk, Artur A., Bocian, Mateusz, Patterson, Matthew R., Yates, Tom
Format: Journal Article
Sprache:Englisch
Veröffentlicht: England Routledge 02.10.2022
Taylor & Francis Ltd
Schlagworte:
Abdomen
Accelerometers
Accelerometry
ActiGraph
Aged
Algorithms
axivity
Bias
brisk walking
GENEActiv
Humans
Middle Aged
open-source
Step count
Walking
Wrist
Wrist Joint
GENEActiv
axivity
open-source
ActiGraph
brisk walking
Step count
ISSN:0264-0414, 1466-447X, 1466-447X
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Zusammenfassung:The Verisense Step Count Algorithm facilitates generation of steps from wrist-worn accelerometers. Based on preliminary evidence suggesting a proportional bias with overestimation at low steps/day, but underestimation at high steps/day, the algorithm parameters have been revised. We aimed to establish validity of the original and revised algorithms relative to waist-worn ActiGraph step cadence. We also assessed whether step cadence was similar across accelerometer brand and wrist. Ninety-eight participants (age: 58.6±11.1 y) undertook six walks (~500 m hard path) at different speeds (cadence: 92.9±9.5-127.9±8.7 steps/min) while wearing three accelerometers on each wrist (Axivity, GENEActiv, ActiGraph) and an ActiGraph on the waist. Of these, 24 participants also undertook one run (~1000 m). Mean bias for the original algorithm was −21 to −26.1 steps/min (95% limits of agreement (LoA) ~±65 steps/min) and mean absolute percentage error (MAPE) 17-22%. This was unevenly distributed with increasing error as speed increased. Mean bias and 95%LoA were halved with the revised algorithm parameters (~-10 to −12 steps/min, 95%LoA ~30 steps/min, MAPE ~10-12%). Performance was similar across brand and wrist. The revised step algorithm provides a more valid measure of step cadence than the original, with MAPE similar to recently reported wrist-wear summary MAPE (7-11%).
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SourceType-Scholarly Journals-1
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ISSN:0264-0414
1466-447X
1466-447X
DOI:10.1080/02640414.2022.2147134