FPGA-Based High-Performance Phonocardiography System for Extraction of Cardiac Sound Components Using Inverse Delayed Neuron Model

The study focuses on the extraction of cardiac sound components using a multi-channel micro-electromechanical system (MEMS) microphone-based phonocardiography system. The proposed multi-channel phonocardiography system classifies the cardiac sound components using artificial neural networks (ANNs) a...

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Autores principales: Anumukonda, Madhubabu, Lakkamraju, Prasadraju, Chowdhury, Shubhajit Roy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Medical Technology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8757846/
https://www.ncbi.nlm.nih.gov/pubmed/35047923
http://dx.doi.org/10.3389/fmedt.2021.666650
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author Anumukonda, Madhubabu
Lakkamraju, Prasadraju
Chowdhury, Shubhajit Roy
author_facet Anumukonda, Madhubabu
Lakkamraju, Prasadraju
Chowdhury, Shubhajit Roy
author_sort Anumukonda, Madhubabu
collection PubMed
description The study focuses on the extraction of cardiac sound components using a multi-channel micro-electromechanical system (MEMS) microphone-based phonocardiography system. The proposed multi-channel phonocardiography system classifies the cardiac sound components using artificial neural networks (ANNs) and synaptic weights that are calculated using the inverse delayed (ID) function model of the neuron. The proposed ANN model was simulated in MATLAB(R) and implemented in a field-programmable gate array (FPGA). The proposed system examined both abnormal and normal samples collected from 30 patients. Experimental results revealed a good sensitivity of 99.1% and an accuracy of 0.9.
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spelling pubmed-87578462022-01-18 FPGA-Based High-Performance Phonocardiography System for Extraction of Cardiac Sound Components Using Inverse Delayed Neuron Model Anumukonda, Madhubabu Lakkamraju, Prasadraju Chowdhury, Shubhajit Roy Front Med Technol Medical Technology The study focuses on the extraction of cardiac sound components using a multi-channel micro-electromechanical system (MEMS) microphone-based phonocardiography system. The proposed multi-channel phonocardiography system classifies the cardiac sound components using artificial neural networks (ANNs) and synaptic weights that are calculated using the inverse delayed (ID) function model of the neuron. The proposed ANN model was simulated in MATLAB(R) and implemented in a field-programmable gate array (FPGA). The proposed system examined both abnormal and normal samples collected from 30 patients. Experimental results revealed a good sensitivity of 99.1% and an accuracy of 0.9. Frontiers Media S.A. 2021-08-12 /pmc/articles/PMC8757846/ /pubmed/35047923 http://dx.doi.org/10.3389/fmedt.2021.666650 Text en Copyright © 2021 Anumukonda, Lakkamraju and Chowdhury. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Medical Technology
Anumukonda, Madhubabu
Lakkamraju, Prasadraju
Chowdhury, Shubhajit Roy
FPGA-Based High-Performance Phonocardiography System for Extraction of Cardiac Sound Components Using Inverse Delayed Neuron Model
title FPGA-Based High-Performance Phonocardiography System for Extraction of Cardiac Sound Components Using Inverse Delayed Neuron Model
title_full FPGA-Based High-Performance Phonocardiography System for Extraction of Cardiac Sound Components Using Inverse Delayed Neuron Model
title_fullStr FPGA-Based High-Performance Phonocardiography System for Extraction of Cardiac Sound Components Using Inverse Delayed Neuron Model
title_full_unstemmed FPGA-Based High-Performance Phonocardiography System for Extraction of Cardiac Sound Components Using Inverse Delayed Neuron Model
title_short FPGA-Based High-Performance Phonocardiography System for Extraction of Cardiac Sound Components Using Inverse Delayed Neuron Model
title_sort fpga-based high-performance phonocardiography system for extraction of cardiac sound components using inverse delayed neuron model
topic Medical Technology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8757846/
https://www.ncbi.nlm.nih.gov/pubmed/35047923
http://dx.doi.org/10.3389/fmedt.2021.666650
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