Nonlinear adaptive noise compensation in electrogastrograms recorded from healthy dogs
Bibliographic record
Abstract
Adaptive noise compensation is a popular method for improving signal-to-noise ratio in a variety of biomedical applications with its major disadvantage being the requirement for a reference channel containing noise strongly correlated to the noise in the primary channel. In many biomedical applications the utilization of a channel containing such noise without any representation of the information signal is difficult if not impossible. In this study we investigated the possibility of applying adaptive compensation in nonideal noise environments containing substantial presence of information signal in the reference channel. The signal in the reference channel was subjected to nonlinear manipulations for reducing the signal-to-noise ratio, thus diminishing the representation of information signal. The methodology was tested on canine electrogastrographic (EGG) signals of four unconscious dogs which underwent laparotomy and implantation of six pairs internal stainless steel electrodes in addition to the eight-channel abdominal EGG. Fourteen-channel (six internal and eight cutaneous) were obtained from each dog for 1/2 h. The signals were digitized and processed by computer. All internal signals showed regular and coupled gastric electrical activity with frequency of repetition in the normogastric range [3-9 cycles-per-minute (cpm)]. A single pair of primary and reference channels was selected from each cutaneous recording and exponential manipulators in the reference channels were introduced. The manipulators were tuned to maximize the percent distribution of spectral components in the canine normogastric range of each frequency spectrum calculated from the signal at the output of the adaptive compensator. Significant increment in the percent distributions in the normogastric range (p < 0.01) was noted after tuning the exponential manipulator, and in many frequency spectra the recovery of the genuine dominant frequency peak of gastric electrical activity as determined by the internal recordings was noted. This study indicated that low percent distributions registered by some EGG channels are related to external nonlinear factors, the impact of which can be partially compensated.
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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 | 0.001 |
| 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".