About: On the Wavelet-based Compressibility of Continuous-Time Sampled ECG Signal for e-Health Applications

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Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	On the Wavelet-based Compressibility of Continuous-Time Sampled ECG Signal for e-Health Applications
Creator	Ben-Romdhane, Manel Dallet, Dominique Maalej, Asma Rebai, Chiheb Rivet, François Tlili, Mariam
Source	Elsevier; Medline; PMC
abstract	This paper presents a compression study of electrocardiogram (ECG) signals for e-Health cardiac online diagnostic systems. The study uses 75 real electrocardiogram records sampled with continuous-time level-crossing (LC) analog-to-digital converter (ADC). This signal-dependent LC-ADC compresses signals compared to conventional ADC but further compression is needed especially for long-time monitoring applications. The orthogonal matching pursuit algorithm is simulated to evaluate ECG compression with 54 orthogonal and biorthogonal wavelets. For LC-ADC amplitude output compression, Biorthogonal3.1 (bior3.1) wavelet achieves optimal performances in terms of compression ratio (CR) while ensuring 2-% percentage root-mean-square difference (PRD). The PRD must be limited to this value to ensure a very good quality signals after decompression. For circuit implementation purposes, bior3.1 wavelet is proposed as a multiplier-free decomposition step and a noncomplex global and hard thresholding process is achieved. The average CR is 63% and PRD varies between 0.1 and 2.1% leading to a very good diagnostic quality.
has issue date	2020-05-27(xsd:dateTime)
bibo:doi	10.1016/j.measurement.2020.108031
bibo:pmid	32565605
has license	no-cc
sha1sum (hex)	18a9b518dfd30f7ad2ec739bb9f7ac1ce6a41766
schema:url	https://doi.org/10.1016/j.measurement.2020.108031
resource representing a document's title	On the Wavelet-based Compressibility of Continuous-Time Sampled ECG Signal for e-Health Applications
has PubMed Central identifier	PMC7255352
has PubMed identifier	32565605
schema:publication	Measurement (Lond)
resource representing a document's body	covid:18a9b518dfd30f7ad2ec739bb9f7ac1ce6a41766#body_text
is schema:about of	named entity 'APPLICATIONS' named entity 'PURPOSES' named entity 'ONLINE' named entity 'continuous-time' named entity 'algorithm' named entity 'PRD' named entity 'wavelets' named entity 'ADC' named entity '63%' named entity 'ADC' named entity 'ADC' named entity 'ADC' named entity 'DWT' named entity 'compression methods' named entity 'amplitude' named entity 'compression ratios' named entity 'ADC' named entity 'PRD' named entity 'block diagram' named entity 'wavelet' named entity 'ECG' named entity 'wavelet' named entity 'wavelet functions' named entity 'sampling frequency' named entity 'QRS complex' named entity 'medical diagnosis' named entity 'input signal' named entity 'OMP' named entity 'lossy compression' named entity 'database' named entity 'continuous-time' named entity 'ECG test' named entity 'wavelets' named entity 'electrocardiogram' named entity 'amplitude' named entity 'ECG' named entity 'amplitude' named entity 'algorithm' named entity 'orthogonal' named entity 'real values' named entity 'ADC' named entity 'wavelets' named entity 'CVDs' named entity 'compression ratios' named entity 'DWT' named entity 'amplitude' named entity 'ECG' named entity 'ECG' named entity 'amplitude' named entity '2, 3' named entity 'myocardial infarction' named entity 'PRD' named entity 'ADCs' named entity 'amplitude' named entity 'wavelet' named entity 'ADC' named entity 'PRD' named entity 'wavelet decomposition' named entity 'DWT' named entity 'best-fit' named entity 'machine learning algorithms' named entity 'down-sampling' named entity 'mother wavelet' named entity 'ECG' named entity 'continuous-time' named entity 'wavelet' named entity 'lossy compression' named entity 'ADC' named entity 'ECG' named entity 'wavelet decomposition' named entity 'cardinality' named entity 'wavelets' named entity 'Matlab' named entity 'QRS complex' named entity 'SoC' named entity 'time intervals'

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