Action Potential Detection Algorithm Adaptable to Individual Nerve and Recording Setup
- Resource Type
- Conference
- Authors
- Raffoul, Romain; Cerda, Javier Chavez; Reina, Elena Acedo; Smets, Hugo; Verstraeten, Maxime; Perre, Louis Vande; Taheri, Rami; Doguet, Pascal; Delbeke, Jean; Tahry, Riem El; Deviere, Jacques; Nonclercq, Antoine
- Source
- 2022 IEEE Biomedical Circuits and Systems Conference (BioCAS) Biomedical Circuits and Systems Conference (BioCAS), 2022 IEEE. :655-659 Oct, 2022
- Subject
- Bioengineering
Obesity
Neurology
Nerve fibers
Action potentials
Shape
Open Access
Rats
Action Potential detection
algorithm
vagus nerve
signal processing
template matching
clustering
- Language
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 GitHub 1 .