Results 51 to 60 of about 7,978 (286)

A Robust Interpretable Deep Learning Classifier for Heart Anomaly Detection Without Segmentation

, 2020
Traditionally, abnormal heart sound classification is framed as a three-stage process. The first stage involves segmenting the phonocardiogram to detect fundamental heart sounds; after which features are extracted and classification is performed.
Denman, Simon, Dissanayake, Theekshana, Fernando, Tharindu, Fookes, Clinton, Ghaemmaghami, Houman, Sridharan, Sridha   +5 more
core   +1 more source

Algorithm for heart rate extraction in a novel wearable acoustic sensor. [PDF]

, 2015
Phonocardiography is a widely used method of listening to the heart sounds and indicating the presence of cardiac abnormalities. Each heart cycle consists of two major sounds - S1 and S2 - that can be used to determine the heart rate.
Aguilar-Pelaez, E, Chen, G, Imtiaz, SA, Rodriguez-Villegas, E   +3 more
core   +1 more source

Development of a Finger-Ring-Shaped Hybrid Smart Stethoscope for Automatic S1 and S2 Heart Sound Identification

Sensors, 2021
Cardiac auscultation is one of the most popular diagnosis approaches to determine cardiovascular status based on listening to heart sounds with a stethoscope.
Soomin Lee, Qun Wei, Heejoon Park, Yuri Na, Donghwa Jeong, Hongjoon Lim   +5 more
doaj   +1 more source

Deep Recurrent Learning for Heart Sounds Segmentation based on Instantaneous Frequency Features

Revista Elektrón, 2020
In this work, a novel stack of well-known technologies is presented to determine an automatic method to segment the heart sounds in a phonocardiogram (PCG).
Alvaro Joaquin Gaona, Pedro David Arini
doaj   +1 more source

A novel scoring system for heart failure screening utilizing combined electrocardiogram, phonocardiogram, and radial artery features. [PDF]

Sci Rep
Bian J, Chee KH, Liu C, Sun H, Zhang S, Chen P, Renchen D, Ting HN.   +7 more
europepmc   +2 more sources

A Low-Cost Multistage Cascaded Adaptive Filter Configuration for Noise Reduction in Phonocardiogram Signal

Journal of Healthcare Engineering, 2022
Phonocardiogram (PCG), the graphic recording of heart signals, is analyzed to determine the cardiac mechanical function. In the recording of PCG signals, the major problem encountered is the corruption by surrounding noise signals.
S. H. Pauline, S. Dhanalakshmi, R. Kumar, R. Narayanamoorthi, K. Lai   +4 more
semanticscholar   +1 more source

Spectral analysis of the fetal phonocardiogram [PDF]

European Journal of Obstetrics & Gynecology and Reproductive Biology, 1985
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openaire   +5 more sources

Determination of Morphologically Characteristic PCG Segments from Spectrogram Image [PDF]

Telfor Journal, 2010
The three-dimensional presentation of phonocardiac signal, simultaneously considering time, amplitude and frequency, allows the determination of morphological characteristic segments in phonocardiogram (PCG), both in short and long sequences.
I. S. Reljin, M. P. Paskaš, A. M. Gavrovska   +2 more
doaj  

Ensemble Transformer-Based Neural Networks Detect Heart Murmur in Phonocardiogram Recordings

2022 Computing in Cardiology (CinC), 2022
Cardiac auscultation through phonocardiogram (PCG) is still the most commonly used approach for evaluating the mechanical functionality of the heart when diagnosing congenital heart disease.
M. Alkhodari, Syafiq Kamarul Azman, L. Hadjileontiadis, A. Khandoker   +3 more
semanticscholar   +1 more source

Searching for Effective Neural Network Architectures for Heart Murmur Detection from Phonocardiogram [PDF]

2022 Computing in Cardiology (CinC), 2022
Aim: The George B. Moody PhysioNet Challenge 2022 raised problems of heart murmur detection and related abnormal cardiac function identification from phonocardiograms (PCGs).
Hao Wen, Ji-Su Kang
semanticscholar   +1 more source