journal.pone.0164045.PDF (1.27 MB)
Download file

Intensity Thresholds on Raw Acceleration Data: Euclidean Norm Minus One (ENMO) and Mean Amplitude Deviation (MAD) Approaches

Download (1.27 MB)
journal contribution
posted on 24.11.2016, 14:50 by Kishan Bakrania, Thomas Yates, Alex V. Rowlands, Dale W. Esliger, Sarah Bunnewell, James Sanders, Melanie Davies, Kamlesh Khunti, Charlotte L. Edwardson
Objectives (1) To develop and internally-validate Euclidean Norm Minus One (ENMO) and Mean Amplitude Deviation (MAD) thresholds for separating sedentary behaviours from common light-intensity physical activities using raw acceleration data collected from both hip- and wrist-worn tri-axial accelerometers; and (2) to compare and evaluate the performances between the ENMO and MAD metrics. Methods Thirty-three adults [mean age (standard deviation (SD)) = 27.4 (5.9) years; mean BMI (SD) = 23.9 (3.7) kg/m2; 20 females (60.6%)] wore four accelerometers; an ActiGraph GT3X+ and a GENEActiv on the right hip; and an ActiGraph GT3X+ and a GENEActiv on the non-dominant wrist. Under laboratory-conditions, participants performed 16 different activities (11 sedentary behaviours and 5 light-intensity physical activities) for 5 minutes each. ENMO and MAD were computed from the raw acceleration data, and logistic regression and receiver-operating-characteristic (ROC) analyses were implemented to derive thresholds for activity discrimination. Areas under ROC curves (AUROC) were calculated to summarise performances and thresholds were assessed via executing leave-one-out-cross-validations. Results For both hip and wrist monitor placements, in comparison to the ActiGraph GT3X+ monitors, the ENMO and MAD values derived from the GENEActiv devices were observed to be slightly higher, particularly for the lower-intensity activities. Monitor-specific hip and wrist ENMO and MAD thresholds showed excellent ability for separating sedentary behaviours from motion-based light-intensity physical activities (in general, AUROCs >0.95), with validation indicating robustness. However, poor classification was experienced when attempting to isolate standing still from sedentary behaviours (in general, AUROCs <0.65). The ENMO and MAD metrics tended to perform similarly across activities and accelerometer brands. Conclusions Researchers can utilise these robust monitor-specific hip and wrist ENMO and MAD thresholds, in order to accurately separate sedentary behaviours from common motion-based light-intensity physical activities. However, caution should be taken if isolating sedentary behaviours from standing is of particular interest.

Funding

The research was supported by the National Institute for Health Research (NIHR) Diet, Lifestyle & Physical Activity Biomedical Research Unit (BRU) based at University Hospitals of Leicester and Loughborough University, the National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care – East Midlands (NIHR CLAHRC – EM) and the Leicester Clinical Trials Unit.

History

Citation

PLoS One, 2016 11(10): e0164045

Author affiliation

/Organisation/COLLEGE OF MEDICINE, BIOLOGICAL SCIENCES AND PSYCHOLOGY/School of Medicine/Department of Health Sciences

Version

VoR (Version of Record)

Published in

PLoS One

Publisher

Public Library of Science

issn

1932-6203

eissn

1932-6203

Acceptance date

19/09/2016

Copyright date

2016

Available date

24/11/2016

Publisher version

http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0164045

Notes

All data underlying the findings of this study are included in the following file: Supporting Information - S1 File. http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0164045#pone.0164045.s001

Language

en

Usage metrics

Categories

Keywords

Exports