Results 11 to 20 of about 2,170 (177)

Heart Murmur Detection in Phonocardiogram Data Leveraging Data Augmentation and Artificial Intelligence [PDF]

Diagnostics
Background/Objectives: With a 17.9 million annual mortality rate, cardiovascular disease is the leading global cause of death. As such, early detection and disease diagnosis are critical for effective treatment and symptom management.
Melissa Valaee, Shahram Shirani
doaj   +2 more sources

Machine learning-based screening of heart failure using the integrated features of electrocardiogram and phonocardiogram: a multicenter study in China [PDF]

Frontiers in Cardiovascular Medicine
BackgroundsHeart failure (HF) is a major health concern associated with poor prognosis, and there is an urgent clinical need for an easy and accurate method for screening HF.
Junjie Bian, Junjie Bian, Kok-Han Chee, Chengyu Liu, Hongwei Sun, Shixi Zhang, Peili Chen, Hua-Nong Ting, Hua-Nong Ting   +8 more
doaj   +2 more sources

Accurate and Low-Cost Cardiac Disorder Detection from Wearable Phonocardiogram Signals Using Hybrid Feature Selection and Machine Learning [PDF]

Biosensors
Early and reliable identification of cardiac disorders from Phonocardiogram (PCG) signals acquired from wearable biosensors is critical to support clinical decision making and reduce subjectivity in auscultation-based assessments.
Ali Narin, Rukiye Uzun Arslan, Damla Kırkıl   +2 more
doaj   +2 more sources

Diagnostic value of synchronized phonocardiogram–electrocardiogram monitoring in children with ventricular septal defect [PDF]

Frontiers in Pediatrics
BackgroundVentricular septal defect (VSD) is one of the most common congenital heart diseases in children, accounting for 20%–25% of all congenital heart defects (CHDs). Current clinical diagnostic methods for VSD mainly include electrocardiography (ECG),
Yan Zhang, Yan Zhang, Jinyong Pan, Jinyong Pan, Yan Guo, Yan Guo, Hu Li, Hu Li, Fengling Zhang, Fengling Zhang, Muqing Niu, Muqing Niu, Heyun Xiong, Heyun Xiong, Yonglin Chen, Yonglin Chen   +15 more
doaj   +2 more sources

Diagnostic performance of wearable acoustic–electrocardiographic indices for screening secundum atrial septal defect in children [PDF]

Frontiers in Pediatrics
ObjectiveTo evaluate the diagnostic performance of acoustic–electrocardiographic indices derived from a wearable phonocardiogram–electrocardiogram (ECG) sensor for screening secundum atrial septal defect (ASD) in children.MethodsIn this cross-sectional ...
Jinyong Pan, Fengling Zhang, Yan Guo, Hu Li, Yonglin Chen, Muqing Niu, Yan Zhang, Heyun Xiong   +7 more
doaj   +2 more sources

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

ESC Heart Failure, Volume 11, Issue 6, Page 4000-4008, December 2024.
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.
Yuri Ochi, Naohito Yamasaki, Toru Kubo, Yuichi Baba, Kazuya Miyagawa, Tatsuya Noguchi, Takayoshi Hirota, Tomoyuki Hamada, Hiroaki Kitaoka   +8 more
wiley   +2 more sources

Balancing Energy Consumption and Detection Accuracy in Cardiovascular Disease Diagnosis: A Spiking Neural Network-Based Approach with ECG and PCG Signals [PDF]

Sensors
Electrocardiogram (ECG) and phonocardiogram (PCG) signals are widely used in the early prevention and diagnosis of cardiovascular diseases (CVDs) due to their ability to accurately reflect cardiac conditions from different physiological perspectives and ...
Guihao Ran, Yijing Wang, Han Zhang, Jiahui Cheng, Dakun Lai   +4 more
doaj   +2 more sources

Integration of PCG spectrogram texture and deep features for the diagnosis of heart failure with preserved ejection fraction using heterogeneous stacking ensemble learning [PDF]

Frontiers in Physiology
This study proposes a novel heterogeneous stacking ensemble learning model for the fusion of phonocardiogram (PCG) spectrogram texture and deep features to detect heart failure with preserved ejection fraction (HFpEF), which plays a critical role in the ...
Yineng Zheng, Yineng Zheng, Jian Qin, Fajin Lv, Fajin Lv, Xia Li, Xingming Guo   +6 more
doaj   +2 more sources

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

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