Effects of a 12-week online Tai Chi intervention on gait and postural stability in individuals with Parkinson’s disease
Bibliographic record
Abstract
Parkinson's disease (PD) affects gait and postural stability. Tai Chi (TC) is recommended for PD for management of the condition, however biomechanical understanding to its effects on gait and postural stability is limited. This study aimed to examine the effects of an online 12-week biomechanical-based TC intervention on gait and posture in people with PD. Fifteen individuals in early-stage PD were recruited (Hoehn & Yahr stages 1–2). The TC intervention program was 60 min session, three times weekly for 12 weeks. The pre- and post-intervention test in obstacle crossing, timed-up-and-go (TUG) test, and single leg standing (SLS) with eyes open (EO) and closed (EC) were conducted. Gait speed, crossing stride length, clearance height of the heel and toe, anterior-posterior (AP) and medial-lateral (ML) displacement and velocity of the center of mass (COM) and separation of the COM-center of pressure (COP) were analyzed. The participants significantly improved their pre-vs. post-TC intervention performance on TUG test (p = 0.002). During obstacle crossing, the participants significantly increased crossing stride length of the trailing foot, increased AP COM displacement and decreased ML COM-COP separation (p < 0.05); the maximal dorsiflexion angle of the leading limb significantly increased and maximal plantarflexion angle of the trailing limb significantly decreased (p < 0.05). A 12-week biomechanical-based online TC training was effective towards improvement of gait and postural stability among people in the early-stage of PD. The TC program and online training could be applied for management of PD.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".