Evidence map›Paper›PMID 39390591›Full record

ArticleBMC sports science, medicine & rehabilitation2024

Classifying physical activity levels using Mean Amplitude Deviation in adults using a chest worn accelerometer: validation of the Vivalink ECG Patch.

Jim Luckhurst, Cara Hughes, Benjamin Shelley

Abstract read
In one paragraph

Article in BMC sports science, medicine & rehabilitation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Jim LuckhurstSchool of Medicine, University of Glasgow, Glasgow, UK.
Cara HughesClinical Research Fellow, Academic Unit of Anaesthesia, Critical Care and Peri-operative Medicine, University of Glasgow, Glasgow, UK.
Benjamin ShelleyPerioperative Medicine and Critical Care research Group, Department of Cardiothoracic Anaesthesia, University of Glasgow Anaesthesia, Golden Jubilee National Hospital, Glasgow, UK. 2439957l@student.gla.ac.uk.

Funding

Medical Research Scotland VAC-1874-2023
6 · The paper itself

Abstract

backgroundThe development of readily available wearable accelerometers has enabled clinicians to objectively monitor physical activity (PA) remotely in the community, a superior alternative to patient self-reporting measures. Critical to the value of these monitors is the ability to reliably detect when patients are undergoing ambulatory activity. Previous studies have highlighted the strength of using mean amplitude deviation (MAD) as a universal measure for analysing raw accelerometery data and defining cut-points between sedentary and ambulatory activities. Currently however there is little evidence surrounding the use of chest-worn accelerometers which can provide simultaneous monitoring of other physiological parameters such as heart rate (HR), RR intervals, and Respiratory Rate alongside accelerometery data. We aimed to calibrate the accelerometery function within the VivaLink ECG patch to determine the cut-point MAD value for differentiating sedentary and ambulatory activities.

methodsWe recruited healthy volunteers to undergo a randomised series of 9 activities that simulate typical free-living behaviours, while wearing a VivaLink ECG Patch (Campbell, California). MAD values were applied to a Generalised Linear Mixed Model to determine cut-points between sedentary and ambulatory activities. We constructed a Receiver Operating Characteristic (ROC) curve to analyse the sensitivity and specificity of the cut-off MAD value.

resultsEighteen healthy adults volunteered to the study and mean MAD values were collected for each activity. The optimal MAD cut-point between sedentary and ambulatory activities was 47.73mG. ROC curve analysis revealed an area under the curve of 0.99 (p < 0.001) for this value with a sensitivity and specificity of 98% and 100% respectively.

conclusionIn conclusion, the MAD cut-point determined in our study is very effective at categorising sedentary and ambulatory activities among healthy adults and may be of use in monitoring PA in the community with minimal burden. It will also be useful for future studies aiming to simultaneously monitor PA with other physiological parameters via chest worn accelerometers.

Indexed as

AccelerometerCalibrationClassificationMADMean amplitude deviationPhysical activityRaw accelerometer data

Identifiers

PMID39390591
PMCPMC11465818

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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.