scholarly journals Towards New Multiwavelets: Associated Filters and Algorithms. Part I: Theoretical Framework and Investigation of Biomedical Signals, ECG and Coronavirus Cases

2021 ◽  
Author(s):  
Malika Jallouli ◽  
Makerem Zemni ◽  
Anouar Ben Mabrouk ◽  
Momahed Ali Mahjoub
Keyword(s):  
Wavelet Transforms ◽  
Fast Algorithms ◽  
Theoretical Framework ◽  
Ecg Signal ◽  
Biomedical Signals ◽  
Independent Components ◽  
Forward Extension

Abstract Biosignals are nowadays important subjects for scientific researches from both theory, and applications, especially, with the appearance of new pandemics threatening the humanity such as the new Coronavirus. One aim in the present work is to prove that Wavelets may be a successful machinery to understand such phenomena by applying a step forward extension of wavelets to multi-wavelets. We proposed in a first step to improve multi-wavelet notion by constructing more general families using independent components for multi-scaling, and multi-wavelet mother functions. A special multi-wavelet is then introduced, continuous, and discrete multi-wavelet transforms are associated, as well as new filters, and algorithms of decomposition, and reconstruction. The constructed multi-wavelet framework is applied for some experimentations showing fast algorithms, ECG signal, and a strain of Coronavirus processing.

scholarly journals Use of Transforms in Biomedical Signal Processing and Analysis

2021 ◽  
Author(s):  
Ette Harikrishna ◽  
Komalla Ashoka Reddy
Keyword(s):  
Wavelet Transforms ◽  
Research Work ◽  
Reference Signal ◽  
Low Frequency ◽  
Motion Artifact ◽  
Motion Artifacts ◽  
Biomedical Signal Processing ◽  
Blood Oxygen Saturation ◽  
Biomedical Signals ◽  
Electrocardiogram Ecg

Biomedical signals like electrocardiogram (ECG), photoplethysmographic (PPG) and blood pressure were very low frequency signals and need to be processed for further diagnosis and clinical monitoring. Transforms like Fourier transform (FT) and Wavelet transform (WT) were extensively used in literature for processing and analysis. In my research work, Fourier and wavelet transforms were utilized to reduce motion artifacts from PPG signals so as to produce correct blood oxygen saturation (SpO2) values. In an important contribution we utilized FT for generation of reference signal for adaptive filter based motion artifact reduction eliminating additional sensor for acquisition of reference signal. Similarly we utilized the transforms for other biomedical signals.

scholarly journals Wavelet Scalogram for Detection of R-peaks in Noisy ECG Signal

2019 ◽  
Vol 8 (10) ◽  
pp. 132-136
Keyword(s):  
Wavelet Analysis ◽  
Wavelet Transforms ◽  
Ecg Signal ◽  
Continuous Wavelet ◽  
Signal Design ◽  
Two Dimensional ◽  
Qrs Complex ◽  
Continuous Wavelet Transforms ◽  
Valuable Data ◽  
Ecg Signals

The ECG (electrocardiography) which reports heart electrical action is capable to supply with valuable data almost the sort of cardiac disarranges endured by the patient based on the fluctuations obtained from the ECG signal design. In this paper, we considered noisy ECG signals [MIT-BIH database] and their different wavelet scalograms. Wavelet analysis performed in the ECG signals with continuous wavelet transforms and it has allowed to graphically identifying scalograms energy two-dimensional characteristics of the heartbeat QRS complex.

scholarly journals A Novel Automatic Detection System for ECG Arrhythmias Using Maximum Margin Clustering with Immune Evolutionary Algorithm

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Bohui Zhu ◽  
Yongsheng Ding ◽  
Kuangrong Hao
Keyword(s):  
Wavelet Transforms ◽  
Detection System ◽  
Diagnostic System ◽  
Ecg Signal ◽  
Maximum Margin Clustering ◽  
Maximum Margin ◽  
Different Types ◽  
Automatic Detection System ◽  
Sensitivity Specificity ◽  
Electrocardiogram Ecg

This paper presents a novel maximum margin clustering method with immune evolution (IEMMC) for automatic diagnosis of electrocardiogram (ECG) arrhythmias. This diagnostic system consists of signal processing, feature extraction, and the IEMMC algorithm for clustering of ECG arrhythmias. First, raw ECG signal is processed by an adaptive ECG filter based on wavelet transforms, and waveform of the ECG signal is detected; then, features are extracted from ECG signal to cluster different types of arrhythmias by the IEMMC algorithm. Three types of performance evaluation indicators are used to assess the effect of the IEMMC method for ECG arrhythmias, such as sensitivity, specificity, and accuracy. Compared withK-means and iterSVR algorithms, the IEMMC algorithm reflects better performance not only in clustering result but also in terms of global search ability and convergence ability, which proves its effectiveness for the detection of ECG arrhythmias.

HYBRID TECHNIQUE FOR ECG SIGNAL COMPRESSION USING PARALLEL AND CASCADE METHOD

2019 ◽  
Vol 31 (01) ◽  
pp. 1950022
Author(s):  
K. S. Surekha ◽  
B. P. Patil
Keyword(s):  
Wavelet Transforms ◽  
Continuous Monitoring ◽  
Discrete Wavelet ◽  
Ecg Signal ◽  
Hybrid Technique ◽  
Compression Technique ◽  
Long Time ◽  
Cascade Method ◽  
Parallel Technique ◽  
Better Than

The recording of electrical activity of the heart by using electrodes is known as electrocardiography (ECG). In long time monitoring of ECG, a huge amount of data needs to be handled. To handle the situation, an efficient compression technique which can retain the clinically important features of ECG signal is required. The continuous monitoring of this signal requires a large amount of memory. Hence, there is a requirement of compression. The compression of ECG signal using transforms in cascade is explored to incorporate the added advantages of both the transforms. This paper presents compression of ECG signal by hybrid technique consisting of cascade and parallel combination of discrete cosine transform (DCT) and discrete wavelet transform (DWT). The simulation is carried out using MATLAB tool. Various wavelet transforms are used for the testing purpose. The performance measures used are Percent square mean Root Difference (PRD) and CR to validate the results. The methodology using cascade combination proved to be better than the parallel technique in terms of Compression Ratio (CR). The highest CR achieved is 28.2 in the method using DCT and DWT in cascade. Different DWTs are used for the testing purpose. The parallel method shows the improved PRD as compared to the cascade method.

Sign in / Sign up

Export Citation Format

Share Document