Results 21 to 30 of about 5,548 (255)

A Comprehensive Nomogram Integrating Phonocardiogram and Echocardiogram Features for the Diagnosis of Heart Failure With Preserved Ejection Fraction. [PDF]

Clin Cardiol
A total of 204 patients and 49 features were collected. After splitting the population into training and test sets according to a ratio of 7:3, the LASSO and logistic regression was used to select the final five factors for a nomogram. The AUC for the nomogram model is 0.945, while the AUC for the echocardiographic parameters combined with NT‐proBNP in
Cao L, Guo X, Liao K, Qin J, Zheng Y.
europepmc   +2 more sources

Classification of Heart Sounds Using Chaogram Transform and Deep Convolutional Neural Network Transfer Learning

Sensors, 2022
Heart sounds convey important information regarding potential heart diseases. Currently, heart sound classification attracts many researchers from the fields of telemedicine, digital signal processing, and machine learning—among others—mainly to identify
Ali Harimi, Yahya Majd, Abdorreza Alavi Gharahbagh, Vahid Hajihashemi, Zeynab Esmaileyan, José J. M. Machado, João Manuel R. S. Tavares   +6 more
doaj   +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

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

Acoustic Cardiography (ACG) for Left Ventricular Ejection Time (LVET) Monitoring in Preeclampsia Risk Prediction. [PDF]

Clin Cardiol
ACG‐derived parameters (LVET), integrated with clinical risk factors, demonstrated dynamic monitoring potential for early Preeclampsia detection, particularly in resource‐limited settings. ABSTRACT Background Preeclampsia (PE), a leading cause of maternal morbidity, lacks reliable early biomarkers.
Tang C, Zhang X, Wang M, Xiong Y, Zhu Y, Huang Q, Zhou N.   +6 more
europepmc   +2 more sources

Importance of fourth heart sound and preserved left atrial function in wild-type transthyretin amyloidosis. [PDF]

ESC Heart Fail
Abstract Aims A fourth heart sound (S4) was reported to be almost never present in patients with amyloid light‐chain cardiomyopathy. There have been no reports on S4 in patients with wild‐type transthyretin amyloid cardiomyopathy (ATTRwt‐CM). This study aimed to clarify the clinical implications of S4 in patients with ATTRwt‐CM.
Ochi Y, Yamasaki N, Kubo T, Baba Y, Miyagawa K, Noguchi T, Hirota T, Hamada T, Kitaoka H.   +8 more
europepmc   +2 more sources

Early diastolic heart sounds caused by the atrial kick. [PDF]

Ann Noninvasive Electrocardiol
Phonogram (top) demonstrates an early diastolic sound (arrows) which corresponds to the P‐wave on the EKG in a patient with second‐degree type I AV block. Abstract An 81‐year‐old male with a history of coronary artery disease, hypertension, paroxysmal atrial fibrillation and chronic kidney disease presents with asymptomatic bradycardia. Examination was
Bachour K, Mendez E, Jackson S, Lluri G, Honda HM.   +4 more
europepmc   +2 more sources

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

Cardiorespiratory system monitoring using a developed acoustic sensor

Healthcare Technology Letters, 2018
This Letter proposes a wireless acoustic sensor for monitoring heartbeat and respiration rate based on phonocardiogram (PCG). The developed sensor comprises a processor, a transceiver which operates at industrial, scientific and medical band and the ...
Reza Abbasi-Kesbi, Atefeh Valipour, Khadije Imani   +2 more
doaj   +1 more source

Signal processing of heart signals for the quantification of non-deterministic events [PDF]

, 2011
Background Heart signals represent an important way to evaluate cardiovascular function and often what is desired is to quantify the level of some signal of interest against the louder backdrop of the beating of the heart itself.
Veronique Millette, Natalie Baddour
core   +1 more source