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Action Potential Detection Algorithm Adaptable to Individual Nerve and Recording Setup

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Raffoul, R Chavez-Cerda, Javier [UCL] Acedo Reina, Elena [UCL] Smets, Hugo [UCL] Verstraeten, Maxime [UCL] Vande Perre, Louis [UCL] Delbeke, Jean [UCL] El Tahry, Riëm [UCL] Nonclercq, Antoine [UCL]

This work presents an automated analysis algorithm to detect action potentials (APs) in a nerve and quantify its activity. The algorithm is based on template matching. The templates are automatically adapted to individual AP shapes that vary depending on the nerve fibers from which the AP originates, and the recording setup used. The algorithm was validated by quantifying vagus nerve activity recorded during in vivo experiments in a rat model. The MATLAB version of the code is available in open access on GitHub1

Document type Article de périodique (Journal article) – Article de recherche
Access type Accès libre
Publication date 2022
Language Anglais
Journal information "IEEE Biomedical Circuits and Systems Conference (BioCAS)" - p. 655-659
Publisher IEEE
issn 2163-4025
Publication status Publié
Affiliation UCL - SSS/IONS/NEUR - Clinical Neuroscience
Links
Bibliographic reference Raffoul, R ; Chavez-Cerda, Javier ; Acedo Reina, Elena ; Smets, Hugo ; Verstraeten, Maxime ; et. al. Action Potential Detection Algorithm Adaptable to Individual Nerve and Recording Setup. In: IEEE Biomedical Circuits and Systems Conference (BioCAS), p. 655-659
Permanent URL http://hdl.handle.net/2078.1/265716