The acute effects of kinesio-taping on movement kinematics and muscle co-activation in rowing athletes
Bibliographic record
Abstract
BACKGROUND: Rowing-related low back disorders may occur from inconsistent technique, high trunk flexion and training volumes, overactivation of paraspinal muscles, and fatigue. OBJECTIVE: To examine if kinesiology tape (KT) affixed to the trunk dorsum affects muscular co-activation and neuromuscular control to limit dangerous rowing movements and associated injuries. METHODS: Participants (n= 18) completed two 2000 m rowing trials under BASELINE and KT conditions. KT was applied to the skin superficial to the paraspinals bilaterally with 60% pre-strain. Participants were instructed to minimize any sensation of tension. Whole body kinematics were obtained using inertial measurement units (IMUs), and surface electromyograms (EMGs) were recorded from trunk and lower extremity. Changes in joint range-of-motion (ROM) and co-activation indices (CAIs) were analyzed for shoulder, lumbar, hip, and knee. RESULTS: Responding participants (n= 5) were identified by reduced maximum lumbar flexion during the KT condition. As expected, significant differences occurred in maximum and minimum lumbar flexion/extension between responders and non-responders to KT. Additionally, there was significant reduction in mean trunk muscle co-activation in both those who did and did not respond to KT through reductions in maximum lumbar flexion. CONCLUSION: KT can be an effective at reducing mean trunk co-activation during a rowing trial in the flexed catch position. Variable responses suggest that further work is necessary to optimize the efficacy of sensory cues derived from KT during rowing movements.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| 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) | 0.000 | 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".