Cite

N. TOWNDEND, D. KAZAKIEWICZ, L. F. WRIGHT, A. TIMMIS, R. HUCULECI, A. TORBICA, C. P. GALE, S. ACHENBACH, F. WEIDINGER, and P. VARDAS, “Epidemiology of cardiovascular disease in europe,” Nature Reviews Cardiology, vol. 19, no. 2, pp. 133–143, 2022. Search in Google Scholar

O. KOVÁČ, J. KROMKA, J. ŠALIGA, and A. JUSKOVÁ, “Multiwavelet-based ecg compressed sensing,” Measurement, vol. 220, p. 113393, 2023. Search in Google Scholar

L. De VITO, E. PICARIELLO, F. PICARIELLO, S. RAQUANO, and I. TUDOSA, “A prototype of a wearable health device for mobile telemonitoring applications,” in 2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA). IEEE, 2022, pp. 1–6. Search in Google Scholar

M. R. MOHEBBIAN and K. A. WAHID, “Ecg compression using optimized b-spline,” Multimedia Tools and Applications, pp. 1–13, 2023. Search in Google Scholar

H. S. PAL, A. KUMAR, A. VISHWAKARMA, and L. BALYAN, “A hybrid 2d ecg compression algorithm using dct and embedded zero tree wavelet,” in 2022 IEEE 6th Conference on Information and Communication Technology (CICT). IEEE, 2022, pp. 1–5. Search in Google Scholar

L. ZHENG, Z. WANG, J. LIANG, S. LUO, and S. TIAN, “Effective compression and classification of ecg arrhythmia by singular value decomposition,” Biomedical Engineering Advances, vol. 2, p. 100013, 2021. Search in Google Scholar

J. MALIK, E. Z. SOLIMAN, and H.-T. WU, “An adaptive qrs detection algorithm for ultra-long-term ecg recordings,” Journal of Electrocardiology, vol. 60, pp. 165–171, 2020. Search in Google Scholar

S. L. BRUNTON and J. N. KUTZ, Data-driven science and engineering: Machine learning, dynamical systems, and control. Cambridge University Press, 2022. Search in Google Scholar

S. M. KHORASANI, G. A. HODTANI, and M. M. KAKHKI, “Investigation and comparison of ecg signal sparsity and features variations due to preprocessing steps,” Biomedical Signal Processing and Control, vol. 49, pp. 87–95, 2019. Search in Google Scholar

U. SATIJA, B. RAMKUMAR, and M. SABARI-MALI Manikandan, “Noise-aware dictionary-learning-based sparse representation framework for detection and removal of single and combined noises from ecg signal,” Healthcare technology letters, vol. 4, no. 1, pp. 2–12, 2017. Search in Google Scholar

Y. HUANG, G. YANG, K. WANG, H. LIU, and Y. YIN, “Learning joint and specific patterns: A unified sparse representation for off-the-person ecg bio-metric recognition,” IEEE Transactions on Information Forensics and Security, vol. 16, pp. 147–160, 2020. Search in Google Scholar

G. GROSSI, R. LANZAROTTI, and J. LIN, “High-rate compression of ecg signals by an accuracy-driven sparsity model relying on natural basis,” Digital Signal Processing, vol. 45, pp. 96–106, 2015. Search in Google Scholar

S. FOUCART and H. RAUHUT, Sparse Solutions of Underdetermined Systems. New York, NY: Springer New York, 2013, pp. 41–59. [Online]. Available: https://doi.org/10.1007/978-0-8176-4948-7_2 Search in Google Scholar

R. D. DRIVER, Cardinality. New York, NY: Springer New York, 1984, pp. 212–220. [Online]. Available: https://doi.org/10.1007/978-1-4612-1108-2_13 Search in Google Scholar

K. SAYOOD, “Data compression,” in Encyclopedia of Information Systems, H. Bidgoli, Ed. New York: Elsevier, 2003, pp. 423–444. [Online]. Available: https://www.sciencedirect.com/science/article/pii/B0122272404000290 Search in Google Scholar

E. MAHMOUDIAN, H. AMINDAVAR, and S. M. AHADI, “New sparsity measure based on energy distribution,” Displays, vol. 80, p. 102542, 2023. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0141938223001750 Search in Google Scholar

D. L. DONOHO, “Compressed sensing,” IEEE Transactions on information theory, vol. 52, no. 4, pp. 1289–1306, 2006. Search in Google Scholar

F. KEINERT, Wavelets and multiwavelets. CRC Press, 2003. Search in Google Scholar

J. LEBRUN and M. VETTERLI, “High-order balanced multiwavelets: theory, factorization, and design,” IEEE Transactions on Signal Processing, vol. 49, no. 9, pp. 1918–1930, 2001. Search in Google Scholar

C. K. CHUI and J.-A. LIAN, “A study of orthonormal multi-wavelets,” Applied Numerical Mathematics, vol. 20, no. 3, pp. 273–298, 1996. Search in Google Scholar

G. C. DONOVAN, J. S. GERONIMO, D. P. HARDIN, and P. R. MASSOPUST, “Construction of orthogonal wavelets using fractal interpolation functions,” SIAM Journal on Mathematical Analysis, vol. 27, no. 4, pp. 1158–1192, 1996. Search in Google Scholar

L. SHEN, H. H. TAN, and J. Y. THAM, “Symmetric– antisymmetric orthonormal multiwavelets and related scalar wavelets,” Applied and Computational Harmonic Analysis, vol. 8, no. 3, pp. 258–279, 2000. Search in Google Scholar

K.-W. CHEUNG and L.-M. PO, “Integer multi-wavelet transform for lossless image coding,” in Proceedings of 2001 International Symposium on Intelligent Multimedia, Video and Speech Processing. ISIMP 2001 (IEEE Cat. No. 01EX489). IEEE, 2001, pp. 117–120. Search in Google Scholar

J. KROMKA, O. Kováč, and J. ŠALIGA, “Multi-wavelet toolbox for matlab,” in 2022 32nd International Conference Radioelektronika (RADIOELEKTRONIKA), 2022, pp. 01–05. Search in Google Scholar

A. KALYAKULINA, I. YUSIPOV, V. MOSKALENKO, A. NIKOLSKIY, K. KOSONOGOV, N. ZOLOTYKH, and M. IVANCHENKO, “Lobachevsky university electrocardiography database,” Type: Dataset. Available online: https://physionet.org/content/ludb/1.0.0/ (accessed on 10 July 2021), 2020. Search in Google Scholar

A. I. KALYAKULINA, I. I. YUSIPOV, V. A. MOSKALENKO, A. V. NIKOLSKIY, K. A. KOSONOGOV, G. V. OSIPOV, N. Y. ZOLOTYKH, and M. V. IVANCHENKO, “Ludb: a new open-access validation tool for electrocardiogram delineation algorithms,” IEEE access, vol. 8, pp. 186 181–186 190, 2020. Search in Google Scholar

A. L. GOLDBERGER, L. A. AMARAL, L. GLASS, J. M. HAUSDORFF, P. C. IVANOV, R. G. MARK, J. E. MIETUS, G. B. MOODY, C.-K. PENG, and H. E. STANLEY, “Physiobank, physiotoolkit, and physionet: components of a new research resource for complex physiologic signals,” circulation, vol. 101, no. 23, pp. e215–e220, 2000. Search in Google Scholar

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