Comparative effect of a 1 h session of electrical muscle stimulation and walking activity on energy expenditure and substrate oxidation in obese subjects
Bibliographic record
Abstract
It has previously been shown that low-frequency neuromuscular electrical stimulation (NMES) techniques can induce increases in energy expenditure similar to those associated with exercise. This study investigated the metabolic and cardiovascular effects of a 1 h session of lower limb NMES and compared cardiovascular response with that observed during walking in nine obese subjects (three males) (age = 43.8 ± 3.0 years; body mass index (BMI) = 41.5 ± 1.8 kg/m(2)). The NMES protocol consisted of delivering a complex pulse pattern to the thigh muscles for 1 h. The walking test consisted of five 4-min bouts starting at 2 km/h with 1 km/h increments up to 6 km/h. In both tests, an open-circuit gas analyser was used to assess O(2) consumption ([Formula: see text]O(2)), CO(2) production ([Formula: see text]CO(2)), respiratory exchange ratio (RER), and heart rate (HR). Rates of fat oxidation (RFO) and carbohydrate oxidation (CHO) were estimated by indirect calorimetry. One hour of NMES significantly increased [Formula: see text]O(2), HR, RER, and mean energy expenditure compared with resting values, reaching 8.7 ± 1.3 mL·min(-2)·kg(-1) (47% of [Formula: see text]O(2peak)), 114.8 ± 7.5 bpm, 0.95, and 318.5 ± 64.3 kcal/h, respectively. CHO, but not RFO, increased during 1 h of NMES. With NMES, CHO was greater and RFO was less than at all walking speeds except 6 km/h. Lactate also increased more with NMES, to 3.5 ± 0.7 mmol versus a maximum of 1.5 ± 0.3 mmol with the walking protocol. These results suggest that NMES can be used in an obese population to induce an effective cardiovascular exercise response. In fact, the observed increase in energy expenditure induced by 1 h of NMES is clinically important and comparable with that recommended in weight management programs.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".