Complex study on compression of ECG signals using novel single-cycle fractal-based algorithm and SPIHT

Simple item page
dc.contributor.authorNěmcová, Andreacs
dc.contributor.authorVítek, Martincs
dc.contributor.authorNováková, Mariecs
dc.coverage.issue1cs
dc.coverage.volume10cs
dc.date.accessioned2020-10-30T11:55:20Z
dc.date.available2020-10-30T11:55:20Z
dc.date.issued2020-09-25cs
dc.description.abstractCompression of ECG signal is essential especially in the area of signal transmission in telemedicine. There exist many compression algorithms which are described in various details, tested on various datasets and their performance is expressed by different ways. There is a lack of standardization in this area. This study points out these drawbacks and presents new compression algorithm which is properly described, tested and objectively compared with other authors. This study serves as an example how the standardization should look like. Single-cycle fractal-based (SCyF) compression algorithm is introduced and tested on 4 different databases-CSE database, MIT-BIH arrhythmia database, High-frequency signal and Brno University of Technology ECG quality database (BUT QDB). SCyF algorithm is always compared with well-known algorithm based on wavelet transform and set partitioning in hierarchical trees in terms of efficiency (2 methods) and quality/distortion of the signal after compression (12 methods). Detail analysis of the results is provided. The results of SCyF compression algorithm reach up to avL=0.4460 bps and PRDN=2.8236%.en
dc.formattextcs
dc.format.extent1-15cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationScientific Reports. 2020, vol. 10, issue 1, p. 1-15.en
dc.identifier.doi10.1038/s41598-020-72656-6cs
dc.identifier.issn2045-2322cs
dc.identifier.other165412cs
dc.identifier.urihttp://hdl.handle.net/11012/195579
dc.language.isoencs
dc.publisherSpringer Naturecs
dc.relation.ispartofScientific Reportscs
dc.relation.urihttps://www.nature.com/articles/s41598-020-72656-6cs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/2045-2322/cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectcompressionen
dc.subjectECGen
dc.subjectelectrocardiogramen
dc.subjectCSE databaseen
dc.subjectMIT-BIH arrhythmia databaseen
dc.subjectSPIHTen
dc.subjectfractalsen
dc.titleComplex study on compression of ECG signals using novel single-cycle fractal-based algorithm and SPIHTen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
sync.item.dbidVAV-165412en
sync.item.dbtypeVAVen
sync.item.insts2020.10.30 12:55:20en
sync.item.modts2020.10.30 12:14:30en
thesis.grantorVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. Ústav biomedicínského inženýrstvícs
thesis.grantorVysoké učení technické v Brně. . Lékařská fakultacs
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
s41598020726566.pdf
Size:
3.62 MB
Format:
Adobe Portable Document Format
Description:
s41598020726566.pdf
Download
Collections
Ústav biomedicínského inženýrství