Article Text

Classification of accelerometer wear and non-wear events in seconds for monitoring free-living physical activity
  1. Shang-Ming Zhou1,
  2. Rebecca A Hill1,
  3. Kelly Morgan1,
  4. Gareth Stratton2,
  5. Mike B Gravenor1,
  6. Gunnar Bijlsma1,
  7. Sinead Brophy1
  1. 1College of Medicine, Swansea University, Wales, UK
  2. 2College of Engineering, Swansea University, Wales, UK
  1. Correspondence to Dr Shang-Ming Zhou; s.zhou{at}swansea.ac.uk

Abstract

Objective To classify wear and non-wear time of accelerometer data for accurately quantifying physical activity in public health or population level research.

Design A bi-moving-window-based approach was used to combine acceleration and skin temperature data to identify wear and non-wear time events in triaxial accelerometer data that monitor physical activity.

Setting Local residents in Swansea, Wales, UK.

Participants 50 participants aged under 16 years (n=23) and over 17 years (n=27) were recruited in two phases: phase 1: design of the wear/non-wear algorithm (n=20) and phase 2: validation of the algorithm (n=30).

Methods Participants wore a triaxial accelerometer (GeneActiv) against the skin surface on the wrist (adults) or ankle (children). Participants kept a diary to record the timings of wear and non-wear and were asked to ensure that events of wear/non-wear last for a minimum of 15 min.

Results The overall sensitivity of the proposed method was 0.94 (95% CI 0.90 to 0.98) and specificity 0.91 (95% CI 0.88 to 0.94). It performed equally well for children compared with adults, and females compared with males. Using surface skin temperature data in combination with acceleration data significantly improved the classification of wear/non-wear time when compared with methods that used acceleration data only (p<0.01).

Conclusions Using either accelerometer seismic information or temperature information alone is prone to considerable error. Combining both sources of data can give accurate estimates of non-wear periods thus giving better classification of sedentary behaviour. This method can be used in population studies of physical activity in free-living environments.

  • physical activity
  • sedentary behaviour
  • non-wear
  • accelerometer
  • PUBLIC HEALTH
  • classification

This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/

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