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International Conference on Systems and Information Sciences

ICCIS 2020: Systems and Information Sciences pp 196–207Cite as

Behavioral Signal Processing with Machine Learning Based on FPGA

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1273))

Abstract

This paper focuses on analyzing health problems derived from a sedentary lifestyle. Studies seeking to improve physical activity have shown that a good incentive to increase physical activity requires social feedback, allowing the subject to keep motivated and competitive, along with a feedback of number of steps at the end of the day. This work describes the training and implementation of a neural network as an artificial intelligence model to predict the behavior of an individual, taking advantage of the flexibility provided by Field Programmable Gate Arrays (FPGAs). We propose the design of an edge computing system, analyzing the efficiency on power, area and computational performance. The results are presented through a display, making a comparison of the predicted and expected steps.

Supported by Escuela Superior Politécnica del Litoral (ESPOL) and National Secretariat of Higher Education, Science, Technology and Innovation of Ecuador (SENESCYT).

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Author information

Authors and Affiliations

  1. Facultad de Ingeniería en Electricidad y Computación, FIEC, Escuela Superior Politécnica del Litoral, ESPOL, Campus Gustavo Galindo Km 30.5 Vía Perimetral, P.O. Box 09-01-5863, 090150, Guayaquil, Ecuador

    Víctor Asanza, Galo Sanchez, Ricardo Cajo & Enrique Peláez

  2. Research Group of Dynamical Systems and Control, Department of Electromechanical, Systems and Metal Engineering, Ghent University, 9052, Ghent, Belgium

    Ricardo Cajo

  3. EEDT—Core Lab on Decision and Control, Flanders Make Consortium, Tech Lane Science Park 131, 9052, Ghent, Belgium

    Ricardo Cajo

Authors
  1. Víctor Asanza
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  2. Galo Sanchez
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  3. Ricardo Cajo
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  4. Enrique Peláez
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Corresponding author

Correspondence to Víctor Asanza .

Editor information

Editors and Affiliations

  1. Eindhoven University of Technology, Eindhoven, Noord-Brabant, The Netherlands

    Miguel Botto-Tobar

  2. Universidad Laica Eloy Alfaro de Manabí, Manta - Manabí, Ecuador

    Willian Zamora

  3. Universidad Laica Eloy Alfaro de Manabí, Manta - Manabí, Ecuador

    Johnny Larrea Plúa

  4. Universidad Laica Eloy Alfaro de Manabí, Manta - Manabí, Ecuador

    José Bazurto Roldan

  5. Universidad Laica Eloy Alfaro de Manabí, Manta - Manabí, Ecuador

    Alex Santamaría Philco

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© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG

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Asanza, V., Sanchez, G., Cajo, R., Peláez, E. (2021). Behavioral Signal Processing with Machine Learning Based on FPGA. In: Botto-Tobar, M., Zamora, W., Larrea Plúa, J., Bazurto Roldan, J., Santamaría Philco, A. (eds) Systems and Information Sciences. ICCIS 2020. Advances in Intelligent Systems and Computing, vol 1273. Springer, Cham. https://doi.org/10.1007/978-3-030-59194-6_17

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