An Analysis Of Shoulder Muscle Activity And Spike Intensity In The Sport Of Volleyball
Bibliographic record
Abstract
INTRODUCTION: Despite being a largely popular sport, with over 500 million athletes worldwide1, little research has been done concerning the volleyball athlete's shoulder musculature. It has been found, that the lower impact speed of the serve results in lower muscle EMG throughout the vast majority of the swing, compared to the higher velocity spike swing2. Little is known about the actions of the anatomy of the shoulder, as well as the importance of certain muscles involved in this high-impact skill. PURPOSE: The purpose of this study was to measure the mean electromyographic (EMG) activity of a group of seven shoulder muscles (pectoralis major, anterior and posterior deltoids, triceps brachii, trapezius, infraspinatus, and latissimus dorsi) at varying, self-determined intensities of spiking, in order to determine the possible significance of certain muscles during the volleyball attack swing. METHODS: Shoulder EMG was collected from four healthy elite-level male CIS volleyball players with no previous shoulder pain during spiking at light, medium, and high levels of exertion. A two-way ANO VA with repeated measures was conducted to test for significant difference between mean EMG activity levels recorded over the entire overhead swing for each of the seven muscles tested. RESULTS: In two of the four subjects, a significantly higher muscle activity was seen in all seven muscles between the light and high levels of exertion, while all subjects demonstrated significantly higher muscle activity levels in the pectoralis major and anterior deltoid muscles with increasing levels of exertion. Three of the subjects demonstrated a similar trend in all muscles but the infraspinatus. Finally, an increasing activity trend was present with increasing levels of exertion for all shoulder musculature except for one subject's anterior deltoid which demonstrated a negative relationship. CONCLUSIONS: These findings are important in that they can be applied to both training and rehabilitation programs, allowing those involved to further understand the muscular effects of spiking at increased intensities.
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 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 | 0.001 | 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".