Evidence map›Paper›PMID 37583419›Full record

ArticleFrontiers in neuroscience2023

The challenge of measuring physiological parameters during motor imagery engagement in patients after a stroke.

Szabina Gäumann, Efe Anil Aksöz, Frank Behrendt, Jasmin Wandel, Letizia Cappelletti, Annika Krug, Daniel Mörder, Annika Bill, Katrin Parmar, Hans Ulrich Gerth and 2 more

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PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 90% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

12 authors at 8 institutions in 2 countries.

Szabina GäumannDepartment of Research, Reha Rheinfelden, Rheinfelden, Switzerland.
Efe Anil AksözSchool of Engineering and Information Technology, Bern University of Applied Sciences, Biel, Switzerland.
Frank BehrendtDepartment of Research, Reha Rheinfelden, Rheinfelden, Switzerland.
Jasmin WandelInstitute for Optimisation and Data Analysis, Bern University of Applied Sciences, Burgdorf, Switzerland.
Letizia CappellettiDepartment of Health Professions, Bern University of Applied Science, Bern, Switzerland.
Annika KrugInstitute for Physiotherapy, School of Health Professions, Zurich University of Applied Sciences, Winterthur, Switzerland.
Daniel MörderDepartment of Sport Science, Faculty of Humanities, University of Konstanz, Konstanz, Germany.
Annika BillInstitute of Human Movement Sciences and Sport, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.
Katrin ParmarDepartment of Research, Reha Rheinfelden, Rheinfelden, Switzerland.
Hans Ulrich GerthDepartment of Research, Reha Rheinfelden, Rheinfelden, Switzerland.
Leo H BonatiDepartment of Research, Reha Rheinfelden, Rheinfelden, Switzerland.
Corina Schuster-AmftDepartment of Research, Reha Rheinfelden, Rheinfelden, Switzerland.
Bern University of Applied Sciences · CHReha Rheinfelden · CHETH Zurich · CHUniversity Hospital Münster · DEUniversity Hospital of Basel · CHUniversity of Basel · CHUniversity of Konstanz · DEZHAW Zurich University of Applied Sciences · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: It is suggested that eye movement recordings could be used as an objective evaluation method of motor imagery (MI) engagement. Our investigation aimed to evaluate MI engagement in patients after stroke (PaS) compared with physical execution (PE) of a clinically relevant unilateral upper limb movement task of the patients' affected body side. Methods: In total, 21 PaS fulfilled the MI ability evaluation [Kinaesthetic and Visual Imagery Questionnaire (KVIQ-10), body rotation task (BRT), and mental chronometry task (MC)]. During the experiment, PaS moved a cup to distinct fields while wearing smart eyeglasses (SE) with electrooculography electrodes integrated into the nose pads and electrodes for conventional electrooculography (EOG). To verify MI engagement, heart rate (HR) and oxygen saturation (SpO Results: MI and PE correlation of SE signals varied between Conclusion: The objective assessment of MI engagement in PaS remains challenging in clinical settings. However, HR was confirmed as a reliable parameter to assess MI engagement in PaS. Eye movements measured with the SE during MI did not resemble those during PE, which is presumably due to the demanding task. A re-evaluation with task adaptation is suggested.

Indexed as

electroencephalographyelectrooculographymotor imagerypulse oximetrysmart eyeglassesstroketest–retest reliabilityvalidity

Identifiers

PMID37583419
PMCPMC10423937
OpenAlexW4385428434

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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.