Rectification is required to extract oscillatory envelope modulation from surface electromyographic signals
Bibliographic record
Abstract
Rectification of surface electromyographic (EMG) recordings prior to their correlation with other signals is a widely used form of preprocessing. Recently this practice has come into question, elevating the subject of EMG rectification to a topic of much debate. Proponents for rectifying suggest it accentuates the EMG spike timing information, whereas opponents indicate it is unnecessary and its nonlinear distortion of data is potentially destructive. Here we examine the necessity of rectification on the extraction of muscle responses, but for the first time using a known oscillatory input to the muscle in the form of electrical vestibular stimulation. Participants were exposed to sinusoidal vestibular stimuli while surface and intramuscular EMG were recorded from the left medial gastrocnemius. We compared the unrectified and rectified surface EMG to single motor units to determine which method best identified stimulus-EMG coherence and phase at the single-motor unit level. Surface EMG modulation at the stimulus frequency was obvious in the unrectified surface EMG. However, this modulation was not identified by the fast Fourier transform, and therefore stimulus coherence with the unrectified EMG signal failed to capture this covariance. Both the rectified surface EMG and single motor units displayed significant coherence over the entire stimulus bandwidth (1-20 Hz). Furthermore, the stimulus-phase relationship for the rectified EMG and motor units shared a moderate correlation (r = 0.56). These data indicate that rectification of surface EMG is a necessary step to extract EMG envelope modulation due to motor unit entrainment to a known stimulus.
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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) | 0.000 | 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".