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Automated Analysis of C. elegans Fluorescence Images using SegElegans
Published on: October 10, 2025
Ivan Gligorijević1, Johannes P van Dijk, Bogdan Mijović
1Department of Electrical Engineering, SCD-SISTA, KU Leuven, Kasteelpark Arenberg 10, 3001 Leuven, Belgium. ivan.gligorijevic@esat.kuleuven.be
This study presents a fast, data-driven method to decompose high-density surface electromyography (HD-sEMG) signals. The novel technique accurately identifies motor unit action potentials (MUAPs) and their firing patterns, matching human operator performance.
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