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

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Abstract

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.

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Funding

This work was partial funded by the CONACYT project FC2016-1961 Neurociencia Computacional: de la teoría al desarrollo de sistemas neuromórficos.

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Authors and Affiliations

  1. Laboratorio de Sistemas Bio-inspirados, Departamento de Electrónica, DICIS - Universidad de Guanajuato, Salamanca, Mexico

    Francisco Javier Iniguez-Lomeli & Horacio Rostro-Gonzalez

  2. Laboratoire de l’Intégration du Matériau au Système (IMS), University of Bordeaux, CNRS UMR 5218, Bordeaux INP, Bordeaux, France

    Yannick Bornat & Sylvie Renaud

  3. Facultad de Ingeniería y Ciencias, Universidad Autónoma de Tamaulipas, Ciudad Victoria, Mexico

    Jose Hugo Barron-Zambrano

Authors
  1. Francisco Javier Iniguez-Lomeli
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  2. Yannick Bornat
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  3. Sylvie Renaud
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  4. Jose Hugo Barron-Zambrano
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  5. Horacio Rostro-Gonzalez
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Correspondence to Jose Hugo Barron-Zambrano.

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Iniguez-Lomeli, F.J., Bornat, Y., Renaud, S. et al. A real-time FPGA-based implementation for detection and sorting of bio-signals. Neural Comput & Applic 33, 12121–12140 (2021). https://doi.org/10.1007/s00521-021-05853-7

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  • DOI: https://doi.org/10.1007/s00521-021-05853-7

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