Vertical Whole-body Vibration Exercise Increases Energy Expenditure versus the Same Exercise without Vibration
Bibliographic record
Abstract
Whole body vibration (WBV) exercise involves static and/or dynamic movements performed on a vertically oscillating platform. Previous research has suggested that WBV exercise increases oxygen consumption and muscle activity compared to the same exercise without vibration. However, there has been no evaluation of the effects of a WBV exercise session on energy expenditure during or following the exercise bout. PURPOSE: To examine the effect of an acute WBV exercise session on energy expenditure during and following (24 h) exercise compared to the same exercise session without vibration. METHODS: VO2 (n=8) was measured both during WBV exercise involving upper and lower body musculature (dynamic squats, single leg lunges, push-ups, triceps dips, and hamstring bridges; 5 sets of 15 reps in 30 sec for each exercise for a total of 15 min of exercise in a 30 min session) and for the remainder of the day (24 h collection). These 24 h data were compared to the same exercise session without vibration and to Control (no exercise). Both breakfast (29 kJ·kg-1; 72% CHO, 15% FAT, 13% PRO) and lunch (46 kJ·kg-1; 55% CHO, 27% FAT, 18%PRO) were provided. RESULTS: Energy expenditure (1311±268 vs 1054±188 kJ; mean+SD; P=0.012) and HR (139±6 vs 126±11 bpm; P=0.033) were increased during the exercise bout relative to non-vibration exercise. Further, 24h energy expenditure was increased (P<0.001) with the WBV exercise session (9363±835 kJ) vs both the non-vibration exercise (8765±210 kJ) and control (8579±766 kJ). CONCLUSION: An acute session of WBV exercise increases energy expenditure during and following the same exercise session without vibration. Consequently, performing WBV exercise chronically should lead to fat mass losses, assuming energy intake remains constant. Supported by Wave™ Manufacturing Inc., and the UWO Kinesiology Graduate Thesis Research Award Fund.
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 | 0.000 |
| 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) | 0.003 | 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".