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dc.contributor.author
Stutz, Jan
dc.contributor.author
Eichenberger, Philipp A.
dc.contributor.author
Stumpf, Nina
dc.contributor.author
Knobel, Samuel E.J.
dc.contributor.author
Herbert, Nicholas C.
dc.contributor.author
Hirzel, Isabel
dc.contributor.author
Huber, Sacha
dc.contributor.author
Oetiker, Chiara
dc.contributor.author
Urry, Emily
dc.contributor.author
Lambercy, Olivier
dc.contributor.author
Spengler, Christina M.
dc.date.accessioned
2024-06-18T08:36:06Z
dc.date.available
2024-06-18T06:49:38Z
dc.date.available
2024-06-18T08:36:06Z
dc.date.issued
2024
dc.identifier.issn
2673-253X
dc.identifier.other
10.3389/fdgth.2024.1400535
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/678787
dc.identifier.doi
10.3929/ethz-b-000678787
dc.description.abstract
Background: Accelerometers were traditionally worn on the hip to estimate energy expenditure (EE) during physical activity but are increasingly replaced by products worn on the wrist to enhance wear compliance, despite potential compromises in EE estimation accuracy. In the older population, where the prevalence of hearing loss is higher, a new, integrated option may arise. Thus, this study aimed to investigate the accuracy and precision of EE estimates using an accelerometer integrated into a hearing aid and compare its performance with sensors simultaneously worn on the wrist and hip. Methods: Sixty middle-aged to older adults (average age 64.0 ± 8.0 years, 48% female) participated. They performed a 20-min resting energy expenditure measurement (after overnight fast) followed by a standardized breakfast and 13 different activities of daily living, 12 of them were individually selected from a set of 35 activities, ranging from sedentary and low intensity to more dynamic and physically demanding activities. Using indirect calorimetry as a reference for the metabolic equivalent of task (MET), we compared the EE estimations made using a hearing aid integrated device (Audéo) against those of a research device worn on the hip (ZurichMove) and consumer devices positioned on the wrist (Garmin and Fitbit). Class-estimated and class-known models were used to evaluate the accuracy and precision of EE estimates via Bland-Altman analyses. Results: The findings reveal a mean bias and 95% limit of agreement for Audéo (class-estimated model) of −0.23 ± 3.33 METs, indicating a slight advantage over wrist-worn consumer devices (Garmin: −0.64 ± 3.53 METs and Fitbit: −0.67 ± 3.40 METs). Class-know models reveal a comparable performance between Audéo (−0.21 ± 2.51 METs) and ZurichMove (−0.13 ± 2.49 METs). Sub-analyses show substantial variability in accuracy for different activities and good accuracy when activities are averaged over a typical day's usage of 10 h (+61 ± 302 kcal). Discussion: This study shows the potential of hearing aid-integrated accelerometers in accurately estimating EE across a wide range of activities in the target demographic, while also highlighting the necessity for ongoing optimization efforts considering precision limitations observed across both consumer and research devices.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Frontiers Media
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.subject
metabolism
en_US
dc.subject
elderly
en_US
dc.subject
calories
en_US
dc.subject
earable
en_US
dc.subject
Fitbit
en_US
dc.subject
Garmin
en_US
dc.subject
Audéo
en_US
dc.title
Energy expenditure estimation during activities of daily living in middle-aged and older adults using an accelerometer integrated into a hearing aid
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 4.0 International
dc.date.published
2024-06-17
ethz.journal.title
Frontiers in Digital Health
ethz.journal.volume
6
en_US
ethz.journal.abbreviated
Front. Digit. Health
ethz.pages.start
1400535
en_US
ethz.size
16 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02070 - Dep. Gesundheitswiss. und Technologie / Dep. of Health Sciences and Technology::02535 - Institut für Bewegungswiss. und Sport / Institut of Human Movement Sc. and Sport::08691 - Spengler, Christina (Tit.-Prof.)
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02070 - Dep. Gesundheitswiss. und Technologie / Dep. of Health Sciences and Technology::02535 - Institut für Bewegungswiss. und Sport / Institut of Human Movement Sc. and Sport::08691 - Spengler, Christina (Tit.-Prof.)
en_US
ethz.date.deposited
2024-06-18T06:49:38Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2024-06-18T08:36:07Z
ethz.rosetta.lastUpdated
2024-06-18T08:36:07Z
ethz.rosetta.exportRequired
true
ethz.rosetta.versionExported
true
ethz.COinS
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