Reorganized Force Control in Elbow Pain Patients During Isometric Wrist Extension
Bibliographic record
Abstract
INTRODUCTION: Reorganized force control may be an important adaptation following painful traumas. In this study, force control adaptations were assessed in elbow pain patients. Increasing the contraction demand may overcome pain interference on the motor control and as such act as an internal control. It was hypothesized that elbow pain patients compared with controls would present greater change in the direction of force when increasing the demand of the motor task. METHODS: Elbow pain patients (n=19) and asymptomatic participants (n=21) performed isometric wrist extensions at 5% to 70% of maximum voluntary contraction. Pressure pain thresholds were recorded at the lateral epicondyle and tibialis anterior muscle. Contraction force was recorded using a 3-directional force transducer. Participants performed contractions according to visual feedback of the task-related force intensity (main direction of wrist extension) and another set of contractions with feedback of the 3 force directions. Going from the simple to the detailed force feedback will increase the demand of the motor task. Force steadiness in all 3 dimensions and force directions were extracted. RESULTS: Compared with controls, elbow pain patients presented lower pressure pain thresholds at both sites (P<0.05). Force steadiness was not significantly different between groups or feedback methods. The change in force direction when providing simple visual feedback in contrast with feedback of all force components at all contraction levels was greater for patients compared with controls (P<0.05). CONCLUSION: The larger change in force direction in pain patients implies redistribution of loads across the arm as an associated effect of pain.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.004 | 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".