Bibliographic record
Abstract
This study examined the maximum joint angles and moments, and electromyography (EMG) activity of the lower limbs in an experienced Tai Chi (TC) practitioner in performing four dynamic (Repulse Monkey, Wave-hand in Clouds, Brush Knee Twist Step, and Lateral Forward Step) and three static TC movements (Starting Form, Hero Touch Sky, and Push Hand Back) and compared them with the measures from walking. Integrated EMG (iEMG) and peak EMG of the rectus femoris, adductor longus, tibialis anterior, semitendinosus, erector spinae, gluteus medius, tensor fasciae latae, medial and lateral gastrocnemius muscles were analyzed. One-way analysis of variance showed that compared with walking, TC presented 1) significantly larger hip flexion (71.4° vs. 42.2°) and abduction angles (11.9° vs. 5.3°), smaller knee flexion (45.2° vs. 71.1°) and abduction angles (13.0° vs. 27.7°), larger ankle dorsiflexion (41.4° vs. 11.3°) and abduction angles (8.8° vs. 7.2°); 2) hip flexion moment and knee flexion and abduction moment were significantly larger. Ankle dorsiflexion moment were significantly smaller, whereas ankle abduction moment was significantly larger in two TC movements; and 3) the EMG activity of the muscles in TC varied from 10% to 610% of walking. The knee extensors, hip adductors and abductors had significantly higher peak EMG (430% ± 40%, 240% ± 30%, and 320% ± 90%) and iEMG values (610% ± 30%, 311% ± 30%, and 1.4% ± 20%), respectively. The findings suggested that these TC movements could be a good option for the improvement of muscle strength and range of motion of the lower limbs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 teacher head, 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".