MétaCan
Menu
Back to cohort
Record W4360858916 · doi:10.46889/jcmr.2023.4107

Intra-limb Coordination and Control in Individuals with Stroke: Conceptual and Methodological Considerations

2023· article· en· W4360858916 on OpenAlexaff
Eryk Przysucha

Bibliographic record

VenueJournal of Clinical Medical Research · 2023
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsLakehead University
Fundersnot available
KeywordsPhysical medicine and rehabilitationContext (archaeology)Motor controlElbowCINAHLPsychologyStroke (engine)KinematicsRelevance (law)RehabilitationCognitive psychologyMotor coordinationMedicinePsychological interventionNeuroscienceEngineeringPolitical scienceGeography

Abstract

fetched live from OpenAlex

Background: A substantial amount of descriptive, rehabilitation and review research examined the behavioral (kinematic) nature of intra-limb organization in reaching and grasping actions in individuals who suffered a stroke. However, the majority of this work failed to explicitly address the level of movement organization affected, the conceptual relevance to existing theories of motor control, and the impact of different constraints on the emerging actions. Thus, the purpose was to examine whether the selected studies examined the issue in coordination and/or control, in the context of the existing conceptual frameworks. The second purpose was to delineate which individual and task constraints have been examined in previous work, and infer the degree to which these factors affected the nature of the emerging movement patterns. Methods: The search of four databases (PubMed, Embase, Web of Science and CINAHL), including published work between January 2019 and March 2022, yielded twenty studies. Results: Despite the fact that stroke substantially alters the emerging movement patterns majority of the studies examined issues in control, not coordination. In term of spatial and temporal control, the actions of individuals with stroke were slower and involved minimal use of the shoulder and elbow joints, as compared to their healthy counterparts. The analysis of emerging movement patterns, via inverse kinematics, showed that stroke resulted in segmented coordination between shoulder and elbow, while no studies examined the relations between distal anatomical structures (e.g., elbow and wrist). In terms of specific theories or models of motor control, most research was data-driven as only three studies made inferences to existing motor control theories (e.g., Equilibrium Point Hypothesis). In regards to the second purpose, time after stroke was the most impactful individual constraint which differentiated the nature of movement organization exhibited by those with and without stroke. The impact of variables such as gender and age, on performance of individuals with stroke, was not examined. From the methodological standpoint, lack of measures of intra-individual variability represents an important limitation in rehabilitation research reviewed. Conclusion: Collectively, the understanding of how individuals with stroke organize their actions remains equivocal. This is due to a variety of different methodological approaches used (e.g., forward vs. inverse kinematics), limited insight into critical aspects of movement organization (e.g., coordination) and the effects of key individual constraints (e.g., age/gender) on the nature of emerging movements. Also, the fact that data driven research still represents the primary impetus in this clinical field undermines the validity of the emerging inferences.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.087
metaresearch head score (Gemma)0.175
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.087
Threshold uncertainty score0.461

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0870.175
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0200.025
Science and technology studies0.0010.005
Scholarly communication0.0080.005
Open science0.0060.004
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.346
GPT teacher head0.552
Teacher spread0.206 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Clinical Medical ResearchSame topicCerebral Palsy and Movement DisordersFrench-language works237,207