Use of dynamic movement orthoses to improve gait stability and trunk control in ataxic patients
Bibliographic record
Abstract
BACKGROUND: Patients with cerebellar ataxia show increased upper body movements, which have an impact on balance and walking. AIM: In this study, we investigated the effect of using dynamic movement orthoses (DMO), designed as elastic suits, on trunk motion and gait parameters. DESIGN: Longitudinal uncontrolled study. SETTING: Outpatient rehabilitation unit. POPULATION: Eleven patients (7 men, 4 women; mean age: 49.9±9.5 years) with degenerative cerebellar ataxia were enrolled in this study. METHODS: Linear overground gait of patients was recorded by means of an optoelectronic gait analysis system before DMO use (DMO-) and during DMO use (DMO+). Time-distance parameters, lower limb joint kinematics, body sway, trunk oscillations, and gait variability (coefficient of variation [CV]) were recorded. Patient satisfaction with DMO device was measured using Quebec user evaluation of satisfaction with assistive technology. RESULTS: When using the DMO, patients showed a significant decrease in stance phase duration, double support phase duration, swing phase CV, pelvic range of motion (ROM), body sway, and trunk ROMs. A significant increase was observed in the swing phase duration and knee joint ROM. Out of 11 patients, 10 were either quite satisfied (8 points) or very satisfied (2 points) with the assistive device. CONCLUSIONS: The DMO reduce the upper body motion and in improve balance-related gait parameters. CLINICAL REHABILITATION IMPACT: We propose use of DMO as an assistive/rehabilitative device in the neurorehabilitation of cerebellar ataxia to improve the trunk control and gait stability. DMO may be considered a prototype that can be modified in terms of material characteristics, textile layers, elastic components, and diagonal and lateral seams.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".