S1 and S2 heart sound recognition using deep neural networks

TE Chen, SI Yang, LT Ho, KH Tsai… - IEEE Transactions …, 2016 - ieeexplore.ieee.org
Objective: This study focuses on the first (S1) and second (S2) heart sound recognition
based only on acoustic characteristics; the assumptions of the individual durations of S1 and …

Classification of heart sound signal using curve fitting and fractal dimension

M Hamidi, H Ghassemian, M Imani - Biomedical Signal Processing and …, 2018 - Elsevier
Cardiovascular disease is one of the major causes of mortality worldwide. Audio signal
produced by the mechanical activity of heart provides useful information about the heart …

Detection of S1 and S2 heart sounds by high frequency signatures

D Kumar, P Carvalho, M Antunes… - … conference of the …, 2006 - ieeexplore.ieee.org
A new unsupervised and low complexity method for detection of S1 and S2 components of
heart sound without the ECG reference is described The most reliable and invariant feature …

The MyHeart project-fighting cardiovascular diseases by prevention and early diagnosis

J Habetha - 2006 international conference of the IEEE …, 2006 - ieeexplore.ieee.org
MyHeart is a so-called Integrated Project of the European Union aiming to develop
intelligent systems for the prevention and monitoring of cardiovascular diseases. The project …

Classification of phonocardiograms with convolutional neural networks

O Deperlioglu - BRAIN. Broad Research in Artificial Intelligence and …, 2018 - edusoft.ro
The diagnosis of heart diseases from heart sounds is a matter of many years. This is the
effect of having too many people with heart diseases in the world. Studies on heart sounds …

Noise detection during heart sound recording using periodicity signatures

D Kumar, P Carvalho, M Antunes… - Physiological …, 2011 - iopscience.iop.org
Heart sound is a valuable biosignal for diagnosis of a large set of cardiac diseases. Ambient
and physiological noise interference is one of the most usual and highly probable incidents …

Temporal-framing adaptive network for heart sound segmentation without prior knowledge of state duration

X Wang, C Liu, Y Li, X Cheng, J Li… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Objective: This paper presents a novel heart sound segmentation algorithm based on
Temporal-Framing Adaptive Network (TFAN), including state transition loss and dynamic …

A new algorithm for detection of S1 and S2 heart sounds

D Kumar, P Carvalho, M Antunes, P Gil… - … on Acoustics Speech …, 2006 - ieeexplore.ieee.org
This paper presents a new algorithm for segmentation and classification of S1 and S2 heart
sounds without ECG reference. The proposed approach is composed of three main stages …

Wavelet transform and simplicity based heart murmur segmentation

D Kumar, P Carvalho, M Antunes… - 2006 Computers in …, 2006 - ieeexplore.ieee.org
This paper is aimed at the identification of the boundaries of murmur present in heart sound.
Heart murmurs provide crucial diagnosis information for several heart diseases such as …

Noise/spike detection in phonocardiogram signal as a cyclic random process with non-stationary period interval

H Naseri, MR Homaeinezhad, H Pourkhajeh - Computers in biology and …, 2013 - Elsevier
The major aim of this study is to describe a unified procedure for detecting noisy segments
and spikes in transduced signals with a cyclic but non-stationary periodic nature. According …