Evidence map›Paper›PMID 39598953›Full record

ArticleSensors (Basel, Switzerland)2024

Monitoring Age-Related Changes in Gait Complexity in the Wild with a Smartphone Accelerometer System.

Vincenzo E Di Bacco, William H Gage

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

2 authors.

Vincenzo E Di BaccoSchool of Kinesiology and Health Science, York University, Toronto, ON M3J 1P3, Canada.ORCID 0000-0002-6223-2996
William H GageSchool of Kinesiology and Health Science, York University, Toronto, ON M3J 1P3, Canada.ORCID 0000-0003-2474-4023

Funding

Canada Foundation for Innovation 12914
6 · The paper itself

Abstract

Stride-to-stride fluctuations during walking reflect age-related changes in gait adaptability and are estimated with nonlinear measures that confine data collection to controlled settings. Smartphones, with their embedded accelerometers, may provide accessible gait analysis throughout the day. This study investigated age-related differences in linear and nonlinear gait measures estimated from a smartphone accelerometer (SPAcc) in an unconstrained, free-living environment. Thirteen young adults (YA) and 11 older adults (OA) walked within a shopping mall with a SPAcc placed in their front right pants pocket. The inter-stride interval, calculated as the time difference between ipsilateral heel contacts, was used for dependent measures calculations. One-way repeated-measures analysis of variance revealed significant (

Indexed as

AccelerometryGaitSmartphoneAdultAgedFemaleHumansMaleMonitoring, PhysiologicWalkingYoung Adultadaptabilityentropyfree-living walkingnonlinear dynamicsstatistical persistencevariabilitywearables

Identifiers

PMID39598953
PMCPMC11598579

What OpenQuestion holds

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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 OpenQuestion graph.