Evidence map›Paper›PMID 40942744›Full record

ArticleSensors (Basel, Switzerland)2025

Validity of AI-Driven Markerless Motion Capture for Spatiotemporal Gait Analysis in Stroke Survivors.

Balsam J Alammari, Brandon Schoenwether, Zachary Ripic, Neva Kirk-Sanchez, Moataz Eltoukhy, Lauri Bishop

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 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. Review
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.

Balsam J AlammariDepartment of Physical Therapy, Miller School of Medicine, University of Miami, Coral Gables, FL 33146, USA.ORCID 0009-0004-7673-0998
Brandon SchoenwetherDepartment of Kinesiology and Sport Sciences, School of Education & Human Development, University of Miami, Coral Gables, FL 33146, USA.ORCID 0009-0002-0849-6701
Zachary RipicDepartment of Kinesiology and Sport Sciences, School of Education & Human Development, University of Miami, Coral Gables, FL 33146, USA.ORCID 0000-0002-7272-0491
Neva Kirk-SanchezDepartment of Physical Therapy, Miller School of Medicine, University of Miami, Coral Gables, FL 33146, USA.
Moataz EltoukhyDepartment of Physical Therapy, Miller School of Medicine, University of Miami, Coral Gables, FL 33146, USA.ORCID 0000-0003-3120-6944
Lauri BishopDepartment of Physical Therapy, Miller School of Medicine, University of Miami, Coral Gables, FL 33146, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gait recovery after stroke is a primary goal of rehabilitation, therefore it is imperative to develop technologies that accurately identify gait impairments after stroke. Markerless motion capture (MMC) is an emerging technology that has been validated in healthy individuals. Our study aims to evaluate the validity of MMC against an instrumented walkway system (IWS) commonly used to evaluate gait in stroke survivors. Nineteen participants performed three comfortable speed (CS) and three fastest speed (FS) walking trials simultaneously recorded with IWS and MMC system, KinaTrax (HumanVersion 8.2, KinaTrax Inc., Boca Raton, FL, USA). Pearson's correlation coefficient and intraclass correlation coefficient (ICC (3,1), 95%CI) were used to evaluate the agreement and consistency between systems. Furthermore, Bland-Altman plots were used to estimate bias and Limits of Agreement (LoA). For both CS and FS, agreements between MMC and IWS were good to excellent in all parameters except for non-paretic single-limb support time (SLS), which revealed moderate agreement during CS. Additionally, stride width and paretic SLS showed poor agreement in both conditions. Biases eliminated systematic errors, with variable LoAs in all parameters during both conditions. Findings indicated high validity of MMC in measuring spatiotemporal gait parameters in stroke survivors. Further validity work is warranted.

Indexed as

GaitGait AnalysisStrokeAdultAgedFemaleHumansMaleMiddle AgedMotion CaptureStroke RehabilitationSurvivorsWalkingartificial intelligencebiomechanicsgaitmarkerless motion capturemotion capturespatiotemporal parametersstroke

Identifiers

PMID40942744
PMCPMC12431465

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.