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

NĚMCOVÁ, Andrea, Martin VÍTEK and Marie NOVÁKOVÁ. Complex study on compression of ECG signals using novel single-cycle fractal-based algorithm and SPIHT. Scientific Reports. London: Nature Publishing Group, 2020, vol. 10, No 1, p. 1-15. ISSN 2045-2322. Available from: https://dx.doi.org/10.1038/s41598-020-72656-6.

Basic information

• Original name: Complex study on compression of ECG signals using novel single-cycle fractal-based algorithm and SPIHT
• Authors: NĚMCOVÁ, Andrea (203 Czech Republic, guarantor), Martin VÍTEK (203 Czech Republic) and Marie NOVÁKOVÁ (203 Czech Republic, belonging to the institution).
• Edition: Scientific Reports, London, Nature Publishing Group, 2020, 2045-2322.

Other information

• Original language: English
• Type of outcome: Article in a journal
• Field of Study: 30105 Physiology
• Country of publisher: United Kingdom of Great Britain and Northern Ireland
• Confidentiality degree: is not subject to a state or trade secret
• WWW: URL
• Impact factor: Impact factor: 4.379
• RIV identification code: RIV/00216224:14110/20:00116568
• Organization unit: Faculty of Medicine
• Doi: http://dx.doi.org/10.1038/s41598-020-72656-6
• UT WoS: 000577252400032
• Keywords in English: ECG signals; single-cycle fractal-based algorithm; SPIHT
• Tags: 14110515, rivok
• Tags: International impact, Reviewed

Abstract

Compression 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%.