Low-Cost FPGA Implementation of Deep Learning-Based Heart Sound Segmentation for Real-Time CVDs Screening-Reference-Cited by-同舟云学术

Low-Cost FPGA Implementation of Deep Learning-Based Heart Sound Segmentation for Real-Time CVDs Screening

Published:2024 Issue: Volume:73 Page:1-16
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Enériz Daniel¹^ORCID,Rodriguez-Almeida Antonio J.²^ORCID,Fabelo Himar²^ORCID,Ortega Samuel²^ORCID,Balea-Fernandez Francisco J.³^ORCID,Callico Gustavo M.²^ORCID,Medrano Nicolás¹^ORCID,Calvo Belén¹^ORCID

Affiliation:

1. Aragon Institute of Engineering Research, University of Zaragoza, Zaragoza, Spain

2. Research Institute for Applied Microelectronics, Universidad de Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain

3. Research Institute for Applied Microelectronics and the Department of Psychology, Sociology and Social Work, University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain

Funder

FEDER, UE Projects

Gobierno de Aragón

Pre-Doctoral Fellowship through Agencia Canaria de Investigación, Innovación y Sociedad de la Información (ACIISI), Consejería de Economía, Conocimiento y Empleo, Gobierno de Canarias

European Social Fund

European Union NextGenerationEU/PRTR

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/19/10367905/10506694.pdf?arnumber=10506694

Reference37 articles.

1. Cardiac Auscultatory Skills of Internal Medicine and Family Practice Trainees

2. Heart Sounds Classification Based on Feature Fusion Using Lightweight Neural Networks

3. Explainable Deep Convolutional Neural Network for Valvular Heart Diseases Classification Using PCG Signals

4. Phonocardiography

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