Seated balance during pitch motion with and without visual input
Bibliographic record
Abstract
The study of seated balance and postural control, specifically in relation to wheelchair propulsion, has been an area of interest for quite some time. In biomedical and rehabilitation research this has led to the potential of treatment and prevention of spinal cord and musculoskeletal injuries. To date, little study has been done which analyzes the activity of lower trunk muscles for seated balance, as opposed to upper limb and shoulder muscles. For the purpose of this study, motorized rotational movement in the forward and backward directions was simulated and the corresponding lower back and abdominal muscle activity was recorded by surface electromyography (EMG). A comparison of how muscle activity was affected by visual input was also conducted. This pilot study was performed on two healthy individuals, recording two of their abdominal muscles, and two lower back muscles. Electrodes were placed on the right and left rectus abdominis, external oblique, thoracic erector spinae, and lumbar erector spinae. Each trial consisted of twelve randomized tests that were performed twice on each subject. The results showed that the speed of rotational motion was the dominant factor in abdominal muscle activity. The results also suggested that motion of the subject with respect to the visual display had an inhibitory effect on the motion perception. Furthermore, challenges to wheelchair patients on a slightly rough terrain were highlighted. Finally, the results also suggested that visual effects during rotational motion had a small effect on the subject, which was possibly caused by placing focus on something else rather than on balance issues.
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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) | 0.003 | 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".