Evidence map›Paper›PMID 38139644›Full record

ArticleSensors (Basel, Switzerland)2023

Validity of AI-Based Gait Analysis for Simultaneous Measurement of Bilateral Lower Limb Kinematics Using a Single Video Camera.

Takumi Ino, Mina Samukawa, Tomoya Ishida, Naofumi Wada, Yuta Koshino, Satoshi Kasahara, Harukazu Tohyama

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 2 pooled it
–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

27 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

7 authors.

Takumi InoGraduate School of Health Sciences, Hokkaido University, Sapporo 0600812, Japan.ORCID 0000-0003-0980-4147
Mina SamukawaFaculty of Health Sciences, Hokkaido University, Sapporo 0600812, Japan.ORCID 0000-0002-4663-598X
Tomoya IshidaFaculty of Health Sciences, Hokkaido University, Sapporo 0600812, Japan.ORCID 0000-0003-0174-7416
Naofumi WadaDepartment of Information and Computer Science, Faculty of Engineering, Hokkaido University of Science, Sapporo 0068585, Japan.
Yuta KoshinoFaculty of Health Sciences, Hokkaido University, Sapporo 0600812, Japan.ORCID 0000-0002-1942-7798
Satoshi KasaharaFaculty of Health Sciences, Hokkaido University, Sapporo 0600812, Japan.
Harukazu TohyamaFaculty of Health Sciences, Hokkaido University, Sapporo 0600812, Japan.

Funding

JSPS KAKENHI JP20K19317
6 · The paper itself

Abstract

Accuracy validation of gait analysis using pose estimation with artificial intelligence (AI) remains inadequate, particularly in objective assessments of absolute error and similarity of waveform patterns. This study aimed to clarify objective measures for absolute error and waveform pattern similarity in gait analysis using pose estimation AI (OpenPose). Additionally, we investigated the feasibility of simultaneous measuring both lower limbs using a single camera from one side. We compared motion analysis data from pose estimation AI using video footage that was synchronized with a three-dimensional motion analysis device. The comparisons involved mean absolute error (MAE) and the coefficient of multiple correlation (CMC) to compare the waveform pattern similarity. The MAE ranged from 2.3 to 3.1° on the camera side and from 3.1 to 4.1° on the opposite side, with slightly higher accuracy on the camera side. Moreover, the CMC ranged from 0.936 to 0.994 on the camera side and from 0.890 to 0.988 on the opposite side, indicating a "very good to excellent" waveform similarity. Gait analysis using a single camera revealed that the precision on both sides was sufficiently robust for clinical evaluation, while measurement accuracy was slightly superior on the camera side.

Indexed as

Artificial IntelligenceGait AnalysisBiomechanical PhenomenaGaitLower ExtremityMotion2D motion analysisboth legshuman pose estimationjoint kinematicslower extremitymarkerlessmotion capturereliabilityViconwalking

Identifiers

PMID38139644
PMCPMC10747245

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.