Effect of a Passive Exoskeleton on Lower Body and Trunk Kinematics in Elderly
Bibliographic record
Abstract
Aims This study aimed to evaluate the effects of a trunk passive exoskeleton on trunk neuromuscular control and lower body kinematics in an elderly population.Methods Thirteen elderly participants, 8 men, 5 women, mean age 68.8 ± 6.7 yr, wore a passive exoskeleton to lift and drop a 5.7 kg box at 40 degrees trunk flexion. Lumbar muscle activation was recorded via electromyography and movement strategies using kinematic data from passive markers. Joint angles and electromyographic root mean square amplitude were compared using t-test between conditions (with and without exoskeleton) during both tasks.Results During the lifting task, no muscle activation and kinematic differences were observed between conditions. During the dropping task, participants with the exoskeleton showed decreased trunk flexion angle by up to 4.1°, between 31% and 60% of the task (p = 0.006). No other significant differences were observed.Discussion Passive exoskeletons can help the elderly by reducing trunk flexion without changing muscle activity.
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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".