Evidence map›Paper›PMID 40138688›Full record

ArticleJournal of medical Internet research2025

Toward Unsupervised Capacity Assessments for Gait in Neurorehabilitation: Validation Study.

Aileen C Naef, Guichande Duarte, Saskia Neumann, Migjen Shala, Meret Branscheidt, Chris Easthope Awai

Abstract readValidation Study
In one paragraph

Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

6 authors.

Aileen C Naef *Data Analytics & Rehabilitation Technology (DART), Lake Lucerne Institute, Vitznau, Switzerland.ORCID https://orcid.org/0000-0002-1797-9441
Guichande Duarte *Department of Neurology, University Hospital of Zurich, Zurich, Switzerland.ORCID https://orcid.org/0009-0007-1178-6765
Saskia NeumannData Analytics & Rehabilitation Technology (DART), Lake Lucerne Institute, Vitznau, Switzerland.ORCID https://orcid.org/0009-0008-6727-5638
Migjen Shalacereneo, Center for Neurology and Rehabilitation, Weggis, Switzerland.ORCID https://orcid.org/0009-0003-4860-6060
Meret Branscheidtcereneo, Center for Neurology and Rehabilitation, Weggis, Switzerland.ORCID https://orcid.org/0000-0002-4008-6916
Chris Easthope AwaiData Analytics & Rehabilitation Technology (DART), Lake Lucerne Institute, Vitznau, Switzerland.ORCID https://orcid.org/0000-0002-3602-7841

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGait impairments are common in stroke survivors, negatively impacting their overall quality of life. Therefore, gait rehabilitation is often targeted during in-clinic rehabilitation. While standardized assessments are available for inpatient evaluation, the literature often reports variable results when these assessments are conducted in a home environment. Several factors, such as the presence of an observer, the environment itself, or the technology used, may contribute to these differing results. Therefore, it is relevant to establish unsupervised capacity assessments for both in-clinic use and across the continuum of care.

objectiveThis study aimed to investigate the effect of supervision on the outcomes of a sensor-based 10-meter walk test conducted in a clinical setting, maintaining a controlled environment and setup.

methodsIn total, 21 stroke survivors (10 female, 11 male; age: mean 63.9, SD 15.5 years) were assigned alternately to one of two data collection sequences and tested over 4 consecutive days, alternating between supervised test (ST) and unsupervised test (UST) assessments. For both assessments, participants were required to walk a set distance of 10 meters as fast as possible while data were collected using a single wearable sensor (Physilog 5) attached to each shoe. After each walking assessment, the participants completed the Intrinsic Motivation Inventory. Statistical analyses were conducted to examine the mean speed, stride length, and cadence, across repeated measurements and between assessment conditions.

resultsThe intraclass correlation coefficient indicated good to excellent reliability for speed (ST: κ=0.93, P<.001; UST: κ=0.93, P<.001), stride length (ST: κ=0.92, P<.001; UST: κ=0.88, P<.001), and cadence (ST: κ=0.91, P<.001; UST: κ=0.95, P<.001) across repeated measurements for both ST and UST assessments. There was no significant effect of testing order (ie, sequence A vs B). Comparing ST and UST, there were no significant differences in speed (t

conclusionsUnsupervised gait capacity assessments offer a reliable alternative to supervised assessments in a clinical environment, showing comparable results for gait speed, stride length, and cadence, with no differences in overall motivation between the two. Future work should build upon these findings to extend unsupervised assessment of both capacity and performance in home environments. Such assessments could allow improved and more specific tracking of rehabilitation progress across the continuum of care.

Indexed as

GaitNeurological RehabilitationStroke RehabilitationAgedFemaleHumansMaleMiddle AgedWalk Test10-meter walk testcapacitygait analysisgait rehabilitationmonitoringmotivationquality of lifesensorsstrokestroke survivorssupervised assessmentsunsupervised assessmentswearables

Identifiers

PMID40138688
PMCPMC11982751

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LicenceCC BY
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Registered trials

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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.