Analysis of continuous diaphragm electromyographic signal: Results from a patient with amyotrophic lateral sclerosis
Bibliographic record
Abstract
INTRODUCTION: Analysis of continuous diaphragm electromyography (dEMG) has not been well studied. We describe a system of analyzing continuous dEMG using implanted electrodes. METHODS: dEMG signal was acquired via two pairs of electrodes near the diaphragm motor points. Raw bursts of dEMG signal were compared to externally captured electrocardiogram (ECG) using adaptive filtering in order to remove cardiac contamination. Differential energy levels were used to identify each dEMG burst, and average amplitude and area values from both hemidiaphragms were aggregated and averaged for the duration of the recording. RESULTS: A 64-year-old patient with amyotrophic lateral sclerosis underwent three serial dEMG studies every 6 months. An average of three tracings were collected per visit, and all had excellent intertest reliability (κ > 0.8). Average dEMG area correlated with forced vital capacity and mean inspiratory pressure (r(2) > 0.9). CONCLUSIONS: The approach described represents a comprehensive method for capturing and analyzing continuous diaphragm EMG signal.
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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 | 0.001 | 0.002 |
| 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".