A review on computational methods for denoising and detecting ECG signals to detect cardiovascular diseases
Cardiac health of the human heart is an intriguing issue for many decades as cardiovascular
diseases (CVDs) are the leading cause of death worldwide. Electrocardiogram (ECG) signal …
diseases (CVDs) are the leading cause of death worldwide. Electrocardiogram (ECG) signal …
A systematic review on artificial intelligence-based techniques for diagnosis of cardiovascular arrhythmia diseases: challenges and opportunities
Cardiovascular health-related problem is a rapidly increasing integrated field concerning the
processing and fetching the information from cardiovascular systems for early detection and …
processing and fetching the information from cardiovascular systems for early detection and …
Optimal design of hammerstein cubic spline filter for nonlinear system modeling based on snake optimizer
This article develops a new class of Hammerstein adaptive filters that contain a memoryless
nonlinear system followed by a linear adaptive filter, where the nonlinear system comprises …
nonlinear system followed by a linear adaptive filter, where the nonlinear system comprises …
Interpretable rule mining for real-time ECG anomaly detection in IoT Edge Sensors
Electrocardiogram (ECG) analysis is widely used in the diagnosis of cardiovascular
diseases. This article proposes an explainable rule-mining strategy for prioritizing abnormal …
diseases. This article proposes an explainable rule-mining strategy for prioritizing abnormal …
A stochastic resonance electrocardiogram enhancement algorithm for robust QRS detection
This study presents a new QRS detection algorithm making use of the background noise that
is inevitably present in electrocardiogram (ECG) recordings. The algorithm suppresses …
is inevitably present in electrocardiogram (ECG) recordings. The algorithm suppresses …
An improved cardiac arrhythmia classification using stationary wavelet transform decomposed short duration QRS segment and Bi-LSTM network
Arrhythmia is a kind of cardiac conduction disorder those result in irregular heartbeats. The
electrocardiograph (ECG) signal may identify conduction system abnormalities. However, its …
electrocardiograph (ECG) signal may identify conduction system abnormalities. However, its …
Performance evaluation of various pre-processing techniques for R-peak detection in ECG signal
In recorded Electrocardiogram (ECG) signal, clinical information is masked by several
noises and distortion resulting in low signal-to-noise-ratio (SNR). In this situation, an efficient …
noises and distortion resulting in low signal-to-noise-ratio (SNR). In this situation, an efficient …
Dynamic thresholding based efficient QRS complex detection with low computational overhead
QRS-complex detection is a primitive step in the detection of cardiac disorder using
electrocardiogram (ECG). Abnormal and varying peaks, baseline wander and other noise …
electrocardiogram (ECG). Abnormal and varying peaks, baseline wander and other noise …
An energy efficient ECG ventricular ectopic beat classifier using binarized CNN for edge AI devices
Wearable Artificial Intelligence-of-Things (AIoT) requires edge devices to be resource and
energy-efficient. In this paper, we design and implement an efficient binary convolutional …
energy-efficient. In this paper, we design and implement an efficient binary convolutional …
Robust R-peak detection in an electrocardiogram with stationary wavelet transformation and separable convolution
R-peak detection is an essential step in analyzing electrocardiograms (ECGs). Previous
deep learning models reported their performance primarily in a single database, and some …
deep learning models reported their performance primarily in a single database, and some …