A real-time FPGA-based implementation for detection and sorting of bio-signals

Francisco Javier Iniguez-Lomeli, Yannick Bornat, Sylvie Renaud, Jose Hugo Barron-Zambrano, Horacio Rostro-Gonzalez

Producció científica: Article en revista indexadaArticleAvaluat per experts

4 Cites (Scopus)


Extracting and analyzing relevant information from bio-signal recordings are complex tasks in which action potential detection and sorting processes take place, moreover if these are performed in real time. In this regard, the present paper introduces real-time FPGA-based architectures for detection and sorting of bio-signals, in particular macaque and human pancreatic signals. Action potential detection is performed by using an adaptive threshold. Also, during this process we have identified six different action potential shapes from the signals, which have been used to classify the action potentials. Our implementation runs at a frequency of 100 MHz with a low resource consumption for both architectures, and action potentials can be also observed in real time during a simulation in an OLED display.

Idioma originalAnglès
Pàgines (de-a)12121-12140
Nombre de pàgines20
RevistaNeural Computing and Applications
Estat de la publicacióPublicada - de set. 2021
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