Movement Component Analysis of Reaching Strategies in Individuals With Stroke: Preliminary Study
Bibliographic record
Abstract
BACKGROUND: Upper limb motor paresis is a major symptom of stroke, which limits activities of daily living and compromises the quality of life. Kinematic analysis offers an in-depth and objective means to evaluate poststroke upper limb paresis, with anticipation for its effective application in clinical settings. OBJECTIVE: This study aims to compare the movement strategies of patients with hemiparesis due to stroke and healthy individuals in forward reach and hand-to-mouth reach, using a simple methodology designed to quantify the contribution of various movement components to the reaching action. METHODS: A 3D motion analysis was conducted, using a simplified marker set (placed at the mandible, the seventh cervical vertebra, acromion, lateral epicondyle of the humerus, metacarpophalangeal [MP] joint of the index finger, and greater trochanter of the femur). For the forward reach task, we measured the distance the index finger's MP joint traveled from its starting position to the forward target location on the anterior-posterior axis. For the hand-to-mouth reach task, the shortening of the vertical distance between the index finger MP joint and the position of the chin at the start of the measurement was measured. For both measurements, the contributions of relevant upper limb and trunk movements were calculated. RESULTS: A total of 20 healthy individuals and 10 patients with stroke participated in this study. In the forward reach task, the contribution of shoulder or elbow flexion was significantly smaller in participants with stroke than in healthy participants (mean 52.5%, SD 24.5% vs mean 85.2%, SD 4.5%; P<.001), whereas the contribution of trunk flexion was significantly larger in stroke participants than in healthy participants (mean 34.0%, SD 28.5% vs mean 3.0%, SD 2.8%; P<.001). In the hand-to-mouth reach task, the contribution of shoulder or elbow flexion was significantly smaller in participants with stroke than in healthy participants (mean 71.8%, SD 23.7% vs mean 90.7%, SD 11.8%; P=.009), whereas shoulder girdle elevation and shoulder abduction were significantly larger in participants with stroke than in healthy participants (mean 10.5%, SD 5.7% vs mean 6.5%, SD 3.0%; P=.02 and mean 16.5%, SD 18.7% vs mean 3.0%, SD 10.4%; P=.02, respectively). CONCLUSIONS: Compared with healthy participants, participants with stroke achieved a significantly greater distance via trunk flexion in the forward reach task and shoulder abduction and shoulder girdle elevation in the hand-to-mouth reach task, both of these differences are regarded as compensatory movements. Understanding the characteristics of individual motor strategies, such as dependence on compensatory movements, may contribute to tailored goal setting in stroke rehabilitation.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".