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Record W1972040301 · doi:10.1109/icassp.2010.5495604

Detection of single action potential in multi-unit postganglionic sympathetic nerve recordings in humans: A matched wavelet approach

2010· article· en· W1972040301 on OpenAlexaff
Aryan Salmanpour, Lyndon J. Brown, J. Kevin Shoemaker

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsWestern University
Fundersnot available
KeywordsMicroneurographyWaveletContinuous wavelet transformSIGNAL (programming language)ThresholdingWavelet transformPattern recognition (psychology)Computer scienceArtificial intelligenceMathematicsBlood pressureDiscrete wavelet transformMedicineHeart rateBaroreflexInternal medicine

Abstract

fetched live from OpenAlex

Sympathetic nerve activity associated with blood pressure regulation can be recorded directly using microneurography. Action potentials (APs) in the sympathetic nerve signal are dominated by colored gaussian noise. This paper proposes a novel method for detecting APs from muscle sympathetic nerve activity (MSNA) in multi-unit postganglionic recordings. The new method is based on designing a new mother wavelet matched to an actual AP template extracted from a real raw MSNA signal. To detect action potentials, the new matched wavelet was applied to the MSNA signal using a continuous wavelet transform following a thresholding procedure and detecting local maxima to estimate AP arrival times. The performance of the proposed method was evaluated using real MSNA recorded from six healthy participants and compared with two previous wavelet-based methods using a simulated MSNA signal.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.467
Threshold uncertainty score0.452

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.036
GPT teacher head0.273
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2010
Admission routes1
Has abstractyes

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