Evidence map›Paper›PMID 32823786›Full record

ArticleSensors (Basel, Switzerland)2020

Sensorized Assessment of Dynamic Locomotor Imagery in People with Stroke and Healthy Subjects.

Daniela De Bartolo, Valeria Belluscio, Giuseppe Vannozzi, Giovanni Morone, Gabriella Antonucci, Gianluca Giordani, Stefania Santucci, Federica Resta, Franco Marinozzi, Fabiano Bini and 2 more

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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

12 authors.

Daniela De BartoloPhD Program in Behaviour Neuroscience, Sapienza University of Rome, Via Dei Marsi 78, 00185 Rome, Italy.ORCID 0000-0001-6882-5381
Valeria BelluscioInteruniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, Department of Movement, Human and Health Sciences, University of Rome "Foro Italico", P.zza Lauro de Bosis 15, 00135 Roma, Italy.
Giuseppe VannozziInteruniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, Department of Movement, Human and Health Sciences, University of Rome "Foro Italico", P.zza Lauro de Bosis 15, 00135 Roma, Italy.ORCID 0000-0002-2359-6076
Giovanni MoroneCLEN Lab, Santa Lucia Foundation, Via Ardeatina 306, 00179 Rome, Italy.
Gabriella AntonucciDepartment of Psychology, Sapienza University of Rome, Via Dei Marsi 78, 00185 Rome, Italy.ORCID 0000-0003-0253-9029
Gianluca GiordaniCLEN Lab, Santa Lucia Foundation, Via Ardeatina 306, 00179 Rome, Italy.
Stefania SantucciDepartment of Mechanical and Aerospace Engineering, Sapienza University of Rome, Via Eudossiana 18, 00184 Rome, Italy.ORCID 0000-0002-7625-9444
Federica RestaCLEN Lab, Santa Lucia Foundation, Via Ardeatina 306, 00179 Rome, Italy.
Franco MarinozziDepartment of Mechanical and Aerospace Engineering, Sapienza University of Rome, Via Eudossiana 18, 00184 Rome, Italy.
Fabiano BiniDepartment of Mechanical and Aerospace Engineering, Sapienza University of Rome, Via Eudossiana 18, 00184 Rome, Italy.
Stefano PaolucciCLEN Lab, Santa Lucia Foundation, Via Ardeatina 306, 00179 Rome, Italy.
Marco IosaSMART Lab, Santa Lucia Foundation, Via Ardeatina 306, 00179 Rome, Italy.ORCID 0000-0003-2434-3887

Funding

Sapienza Università di Roma AR11816436CF2A11
6 · The paper itself

Abstract

Dynamic motor imagery (dMI) is a motor imagery task associated with movements partially mimicking those mentally represented. As well as conventional motor imagery, dMI has been typically assessed by mental chronometry tasks. In this paper, an instrumented approach was proposed for quantifying the correspondence between upper and lower limb oscillatory movements performed on the spot during the dMI of walking vs. during actual walking. Magneto-inertial measurement units were used to measure limb swinging in three different groups: young adults, older adults and stroke patients. Participants were tested in four experimental conditions: (i) simple limb swinging; (ii) limb swinging while imagining to walk (dMI-task); (iii) mental chronometry task, without any movement (pure MI); (iv) actual level walking at comfortable speed. Limb swinging was characterized in terms of the angular velocity, frequency of oscillations and sinusoidal waveform. The dMI was effective at reproducing upper limb oscillations more similar to those occurring during walking for all the three groups, but some exceptions occurred for lower limbs. This finding could be related to the sensory feedback, stretch reflexes and ground reaction forces occurring for lower limbs and not for upper limbs during walking. In conclusion, the instrumented approach through wearable motion devices adds significant information to the current dMI approach, further supporting their applications in neurorehabilitation for monitoring imagery training protocols in patients with stroke.

Indexed as

Monitoring, PhysiologicStrokeWalkingAgedHealthy VolunteersHumansLower ExtremityMaleMovementYoung Adultgaitinertial sensorsinstrumented movement analysismotor imageryneurorehabilitationstrokewalking

Identifiers

PMID32823786
PMCPMC7472606

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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.