Algorithms for automatic analysis and classification of heart sounds–a systematic review
Cardiovascular diseases currently pose the highest threat to human health around the
world. Proper investigation of the abnormalities in heart sounds is known to provide vital …
world. Proper investigation of the abnormalities in heart sounds is known to provide vital …
A critical review of feature extraction techniques for ECG signal analysis
An Electrocardiogram (ECG) is a primary and most prevalent non-invasive test performed on
the subjects'(ie patients') with suspected heart problems. It helps in diagnosing important …
the subjects'(ie patients') with suspected heart problems. It helps in diagnosing important …
An open access database for the evaluation of heart sound algorithms
In the past few decades, analysis of heart sound signals (ie the phonocardiogram or PCG),
especially for automated heart sound segmentation and classification, has been widely …
especially for automated heart sound segmentation and classification, has been widely …
Phonocardiographic sensing using deep learning for abnormal heartbeat detection
Deep learning-based cardiac auscultation is of significant interest to the healthcare
community as it can help reducing the burden of manual auscultation with automated …
community as it can help reducing the burden of manual auscultation with automated …
Heart sound classification based on scaled spectrogram and tensor decomposition
W Zhang, J Han, S Deng - Expert Systems with Applications, 2017 - Elsevier
Heart sound signal analysis is an effective and convenient method for the preliminary
diagnosis of heart disease. However, automatic heart sound classification is still a …
diagnosis of heart disease. However, automatic heart sound classification is still a …
Effective heart sound segmentation and murmur classification using empirical wavelet transform and instantaneous phase for electronic stethoscope
VN Varghees, KI Ramachandran - IEEE Sensors Journal, 2017 - ieeexplore.ieee.org
Accurate measurement of heart sound and murmur parameters is of great importance in the
automated analysis of phonocardiogram (PCG) signals. In this paper, we propose a novel …
automated analysis of phonocardiogram (PCG) signals. In this paper, we propose a novel …
Time–frequency features for pattern recognition using high-resolution TFDs: A tutorial review
This paper presents a tutorial review of recent advances in the field of time–frequency (t, f)
signal processing with focus on exploiting (t, f) image feature information using pattern …
signal processing with focus on exploiting (t, f) image feature information using pattern …
Gaussian process models for mitigation of operational variability in the structural health monitoring of wind turbines
LD Avendano-Valencia, EN Chatzi… - Mechanical Systems and …, 2020 - Elsevier
The analysis presented in this work relates to the quantification of the effect of a selected set
of measured Environmental and Operational Parameters (EOPs) on the dynamic properties …
of measured Environmental and Operational Parameters (EOPs) on the dynamic properties …
Towards the classification of heart sounds based on convolutional deep neural network
Background and objective Heart sound contains various important quantities that help early
detection of heart diseases. Many methods have been proposed so far where various signal …
detection of heart diseases. Many methods have been proposed so far where various signal …
Automatic signal abnormality detection using time-frequency features and machine learning: A newborn EEG seizure case study
B Boashash, S Ouelha - Knowledge-Based Systems, 2016 - Elsevier
Time-frequency (TF) based machine learning methodologies can improve the design of
classification systems for non-stationary signals. Using selected TF distributions (TFDs), TF …
classification systems for non-stationary signals. Using selected TF distributions (TFDs), TF …