An Efficient Lossless Compression Algorithm for Electrocardiogram Signals. Campobello, G., Segreto, A., Zanafi, S., & Serrano, S. In 2018 26th European Signal Processing Conference (EUSIPCO), pages 777-781, Sep., 2018. Paper doi abstract bibtex This paper focuses on a novel lossless compression algorithm which can be efficiently used for compression of electrocardiogram (ECG) signals. The proposed algorithm has low memory requirements and relies on a simple and efficient encoding scheme which can be implemented with elementary counting operations. Thus it can be easily implemented even in resource constrained microcontrollers as those commonly used in several low-cost ECG monitoring systems. Despite its simplicity, simulation results carried out on real-world ECG signals show that the proposed algorithm achieves higher compression ratios as even compared to other more complex state-of-the-art solutions.
@InProceedings{8553597,
author = {G. Campobello and A. Segreto and S. Zanafi and S. Serrano},
booktitle = {2018 26th European Signal Processing Conference (EUSIPCO)},
title = {An Efficient Lossless Compression Algorithm for Electrocardiogram Signals},
year = {2018},
pages = {777-781},
abstract = {This paper focuses on a novel lossless compression algorithm which can be efficiently used for compression of electrocardiogram (ECG) signals. The proposed algorithm has low memory requirements and relies on a simple and efficient encoding scheme which can be implemented with elementary counting operations. Thus it can be easily implemented even in resource constrained microcontrollers as those commonly used in several low-cost ECG monitoring systems. Despite its simplicity, simulation results carried out on real-world ECG signals show that the proposed algorithm achieves higher compression ratios as even compared to other more complex state-of-the-art solutions.},
keywords = {data compression;electrocardiography;encoding;medical signal processing;microcontrollers;patient monitoring;compression ratios;efficient lossless compression algorithm;real-world ECG signals;low-cost ECG monitoring systems;resource constrained microcontrollers;elementary counting operations;efficient encoding scheme;simple encoding scheme;low memory requirements;electrocardiogram signals;Compression algorithms;Signal processing algorithms;Encoding;Electrocardiography;Microcontrollers;Prediction algorithms;Matrix decomposition},
doi = {10.23919/EUSIPCO.2018.8553597},
issn = {2076-1465},
month = {Sep.},
url = {https://www.eurasip.org/proceedings/eusipco/eusipco2018/papers/1570438085.pdf},
}
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