Machine Learning Algorithms for Processing and Classifying Unsegmented Phonocardiographic Signals: An Efficient Edge Computing Solution Suitable for Wearable …
The phonocardiogram (PCG) can be used as an affordable way to monitor heart conditions.
This study proposes the training and testing of several classifiers based on SVMs (support …
This study proposes the training and testing of several classifiers based on SVMs (support …
Deep learning based phonocardiogram signals analysis for cardiovascular abnormalities detection
Cardiovascular diseases are among the vital causes of mortality worldwide which need
early detection with the use of auscultation examination. Heart diseases could be diagnosed …
early detection with the use of auscultation examination. Heart diseases could be diagnosed …
Phonocardiogram classification using deep convolutional neural networks with majority vote strategy
Most current automated phonocardiogram (PCG) classification methods are relied on PCG
segmentation. It is universal to make use of the segmented PCG signals and then extract …
segmentation. It is universal to make use of the segmented PCG signals and then extract …
Deep autoencoder neural networks for heart sound classification
Heart sound signals, or Phonocardiogram (PCG), play a significant role in diagnosing heart
diseases, and it is a well-accepted way to detect cardiovascular diseases (CVDs). Recent …
diseases, and it is a well-accepted way to detect cardiovascular diseases (CVDs). Recent …
Automatic classification of normal–abnormal heart sounds using convolution neural network and long-short term memory
The phonocardiogram (PCG) is an important analysis method for the diagnosis of
cardiovascular disease, which is usually performed by experienced medical experts. Due to …
cardiovascular disease, which is usually performed by experienced medical experts. Due to …
Cross-wavelet assisted convolution neural network (AlexNet) approach for phonocardiogram signals classification
The exponential growth of a multitude of cardiovascular diseases, leading to life frightening
conditions, makes fast and accurate computer-aided techniques that are relevant and …
conditions, makes fast and accurate computer-aided techniques that are relevant and …
Peak spectrogram and convolutional neural network-based segmentation and classification for phonocardiogram signals
A Abid - Advances in Non-Invasive Biomedical Signal Sensing …, 2023 - Springer
Heart diseases are one of the contributing reasons for the human loss in the world. The
Phonocardiogram (PCG) provides information for the exact and timely detection of …
Phonocardiogram (PCG) provides information for the exact and timely detection of …
Automated heart sound classification system from unsegmented phonocardiogram (PCG) using deep neural network
PT Krishnan, P Balasubramanian… - Physical and Engineering …, 2020 - Springer
Given the patient to doctor ratio of 50,000: 1 in low income and middle-income countries,
there is a need for automated heart sound classification system that can screen the …
there is a need for automated heart sound classification system that can screen the …
PCG Signal Acquisition and Classification for Heart Failure Detection: Recent Advances and Implementation of Memory-Efficient Classifiers for Edge Computing …
L Spongano, R De Fazio, M De Vittorio… - … on Smart and …, 2024 - ieeexplore.ieee.org
Conventional diagnostic tools for cardiovascular diseases usually employ expensive
instrumentation and require specialized medical staff. An inexpensive and non-invasive …
instrumentation and require specialized medical staff. An inexpensive and non-invasive …
Phonocardiogram classification using deep neural networks and weighted probability comparisons
M Sotaquirá, D Alvear, M Mondragon - Journal of medical …, 2018 - Taylor & Francis
Cardiac auscultation is one of the most conventional approaches for the initial assessment
of heart disease, however the technique is highly user-dependent and with low repeatability …
of heart disease, however the technique is highly user-dependent and with low repeatability …