- Title
- Non-wear or sleep? Evaluation of five non-wear detection algorithms for raw accelerometer data
- Creator
- Ahmadi, Matthew N.; Nathan, Nicole; Sutherland, Rachel; Wolfenden, Luke; Trost, Stewart G.
- Relation
- Journal of Sports Sciences Vol. 38, Issue 4, p. 399-404
- Publisher Link
- http://dx.doi.org/10.1080/02640414.2019.1703301
- Publisher
- Routledge
- Resource Type
- journal article
- Date
- 2020
- Description
- Detection of non-wear periods is an important step in accelerometer data processing. This study evaluated five non-wear detection algorithms for wrist accelerometer data and two rules for non-wear detection when non-wear and sleep algorithms are implemented in parallel. Non-wear algorithms were based on the standard deviation (SD), the high-pass filtered acceleration, or tilt angle. Rules for differentiating sleep from non-wear consisted of an override rule in which any overlap between non-wear and sleep was deemed non-wear; and a 75% rule in which non-wear periods were deemed sleep if the duration was < 75% of the sleep period. Non-wear algorithms were evaluated in 47 children who wore an ActiGraph GT3X+ accelerometer during school hours for 5 days. Rules for differentiating sleep from non-wear were evaluated in 15 adults who wore a GeneActiv Original accelerometer continuously for 24 hours. Classification accuracy for the non-wear algorithms ranged between 0.86-0.95, with the SD of the vector magnitude providing the best performance. The override rule misclassified 37.1 minutes of sleep as non-wear, while the 75% rule resulted in no misclassification. Non-wear algorithms based on the SD of the acceleration signal can effectively detect non-wear periods, while application of the 75% rule can effectively differentiate sleep from non-wear when examined concurrently.
- Subject
- accelerometry; physical activity; measurement; wearable sensor; sleep
- Identifier
- http://hdl.handle.net/1959.13/1419639
- Identifier
- uon:37477
- Identifier
- ISSN:0264-0414
- Rights
- This is an Accepted Manuscript of an article published by Taylor & Francis Group in the Journal of Sports Sciences on 11/12/2019, available online: http://dx.doi.org/10.1080/02640414.2019.1703301
- Language
- eng
- Full Text
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