Evidence map›Paper›PMID 37765963›Full record

ArticleSensors (Basel, Switzerland)2023

Quantitative Comparison of Hand Kinematics Measured with a Markerless Commercial Head-Mounted Display and a Marker-Based Motion Capture System in Stroke Survivors.

Antonino Casile, Giulia Fregna, Vittorio Boarini, Chiara Paoluzzi, Fabio Manfredini, Nicola Lamberti, Andrea Baroni, Sofia Straudi

Open access · goldAbstract 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 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
1.7field-weighted citation impact, top 16% of its field
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

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

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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

8 authors at 2 institutions in 1 country.

Antonino CasileDepartment of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, 98122 Messina, Italy.ORCID 0000-0002-7824-9274
Giulia FregnaDoctoral Program in Translational Neurosciences and Neurotechnologies, University of Ferrara, 44121 Ferrara, Italy.
Vittorio BoariniCenter of Translational Neurophysiology of Speech and Communication (CTNSC), Istituto Italiano di Tecnologia (IIT), 44121 Ferrara, Italy.
Chiara PaoluzziDepartment of Neuroscience and Rehabilitation, University of Ferrara, 44121 Ferrara, Italy.
Fabio ManfrediniDepartment of Neuroscience and Rehabilitation, University of Ferrara, 44121 Ferrara, Italy.ORCID 0000-0001-9476-6434
Nicola LambertiDepartment of Neuroscience and Rehabilitation, University of Ferrara, 44121 Ferrara, Italy.ORCID 0000-0001-5763-3069
Andrea BaroniDepartment of Neuroscience and Rehabilitation, University of Ferrara, 44121 Ferrara, Italy.ORCID 0000-0002-8681-3090
Sofia StraudiDepartment of Neuroscience and Rehabilitation, University of Ferrara, 44121 Ferrara, Italy.ORCID 0000-0002-2061-9922
University of Ferrara · ITUniversity of Messina · IT

Funding

This work was supported by #NEXTGENERATIONEU (NGEU) and funded by the Ministry of University and Research (MUR), National Recovery and Resilience Plan (NRRP), project MNESYS (PE0000006) - A Multiscale integrated approach to the study of the nervous system project MNESYS (PE0000006)
6 · The paper itself

Abstract

Upper-limb paresis is common after stroke. An important tool to assess motor recovery is to use marker-based motion capture systems to measure the kinematic characteristics of patients' movements in ecological scenarios. These systems are, however, very expensive and not readily available for many rehabilitation units. Here, we explored whether the markerless hand motion capabilities of the cost-effective Oculus Quest head-mounted display could be used to provide clinically meaningful measures. A total of 14 stroke patients executed ecologically relevant upper-limb tasks in an immersive virtual environment. During task execution, we recorded their hand movements simultaneously by means of the Oculus Quest's and a marker-based motion capture system. Our results showed that the markerless estimates of the hand position and peak velocity provided by the Oculus Quest were in very close agreement with those provided by a marker-based commercial system with their regression line having a slope close to 1 (maximum distance: mean slope = 0.94 ± 0.1; peak velocity: mean slope = 1.06 ± 0.12). Furthermore, the Oculus Quest had virtually the same sensitivity as that of a commercial system in distinguishing healthy from pathological kinematic measures. The Oculus Quest was as accurate as a commercial marker-based system in measuring clinically meaningful upper-limb kinematic parameters in stroke patients.

Indexed as

StrokeStroke RehabilitationBiomechanical PhenomenaHandHumansMotion CaptureMovementUpper Extremityhead-mounted displaymarkerless motion capture systemmotion analysismotor recoveryOculus QuestOptitrackstroke

Identifiers

PMID37765963
PMCPMC10535006
OpenAlexW4386838406

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.