Intra-limb Coordination and Control in Individuals with Stroke: Conceptual and Methodological Considerations
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.087 | 0.175 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.020 | 0.025 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".