Evidence map›Paper›PMID 41124109›Full record

ArticlePloS one2025

Accurate measurement of simulated slow and altered walking activity: Apple Watch best in class wearable devices.

Grant Rowe, David Weight, Alethea Rea, Jenny Conlon, Fiona M Wood, Dale W Edgar

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Grant RoweDiscipline of Psychology, College of Science, Health, Engineering and Education, Murdoch University, Perth, Western Australia, Australia.
David WeightSchool of Mathematics, Statistics, Chemistry and Physics, Murdoch University, Murdoch, Western Australia, Australia.
Alethea ReaSchool of Mathematics, Statistics, Chemistry and Physics, Murdoch University, Murdoch, Western Australia, Australia.ORCID https://orcid.org/0000-0003-0750-7501
Jenny ConlonFaculty of Medicine, Nursing, Midwifery and Health Sciences, School of Health Sciences, The University of Notre Dame Australia, Fremantle, Western Australia, Australia.
Fiona M WoodFiona Wood Foundation, Fiona Stanley Hospital, Murdoch, Western Australia, Australia.
Dale W EdgarFiona Wood Foundation, Fiona Stanley Hospital, Murdoch, Western Australia, Australia.ORCID https://orcid.org/0000-0001-7336-9317

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWearable activity devices, widely used to monitor physical activity in non-injured populations, have shown potential in encouraging early ambulation and enhanced recovery in hospitalised patients. This study evaluated the accuracy of wearable devices in tracking step counts under simulated hospital conditions, seeking the optimal body location placement for individuals with altered gait.

methodsThis method comparison study involved healthy adults walking on a treadmill while performing slow and shuffling walking patterns. Twelve wearable devices were placed on the arm, waist, and leg, and their recorded step counts were compared to manual counts from filmed sessions, following Consumer Technology Association guidelines.

resultsThe Apple Watch, particularly when worn on the waist, demonstrated the highest reliability and adaptability across walking patterns. Leg placement, which accounted for 10 of the top 20 device-position combinations, suggested that larger movement amplitudes improve step count accuracy, particularly during slow or altered gaits.

conclusionThis study confirmed the Apple Watch to be the most accurate wearable step count device. The study provides new understanding as to the precision of commercially available devices and their placement, when aiming to improve and, or conduct research about, patient physical activity outcomes.

Indexed as

Monitoring, AmbulatoryWalkingWearable Electronic DevicesAdultFemaleGaitHumansMaleReproducibility of ResultsYoung Adult

Identifiers

PMID41124109
PMCPMC12543184

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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 Socratic graph.