Author

Samuel J. Frueh

University of Connecticut

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Biophysics· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Assay:electrophysiology· 1

Activity by Year

2024-2024 · peak 1/yr

1 paper

Recent·Most cited

BiophysicsbioRxivPreprintOct 18, 2024

Modeling Electrocardogram (ECG) Waveforms Using Group Theory and Symmetry Elements

Samuel J. Frueh

The paper introduces a novel method using group theory and symmetry elements to generate ECG waveforms without predefined boundary conditions, offering a new perspective on biological signal representation.

DOI 10.1101/2024.10.18.619135

electrophysiologydeep learning

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