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Erschienen in: Health and Technology 5/2020

11.07.2020 | Original Paper

An optimized ECG android system using data compression scheme for cloud storage

verfasst von: Eduardo Giometti Bertogna, Francisco Muller Machado, Miguel Antonio Sovierzoski

Erschienen in: Health and Technology | Ausgabe 5/2020

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Abstract

In the field of biomedical engineering, there is a lot of research being done in long term electrocardiographic (ECG) monitoring, and one of the most promising one concerns the transmission of compressed electrocardiographic signal throughout the internet, so that at the receiver side it arrives with minimum distortion, yet not demanding too much computational power from the processor to be decompressed. Other situations arrive when synchronization is a problem, and as a result may also require the storage of the signal in a cloud, for further examination by the medical staff. Another problem focuses on a reduced bandwidth for the transmission due to the huge amount of data obtained after a long term ECG monitoring of up to twelve ECG leads from the patient. In order to try solving these problems, this paper presents a ECG system using advances in Mobile Cloud Computing (MCC) focusing on its storage services, as well as concepts of ECG signal compression for an optimal processing power usage and transmission over Internet Protocol and making use of a free of charge cloud services. The task of compressing the ECG signal was made using vector quantization approach with reduced processing consumption by the mobile device. The system’s performance resulted quite suitable to be applied in patients remote ECG monitoring with very low signal distortion - maintaining its morphological information, good compression rate and reduced bandwidth for data transmission and storage. In conclusion, the system’s architecture and concepts presented here have a potential use in telemedicine systems.

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Metadaten
Titel
An optimized ECG android system using data compression scheme for cloud storage
verfasst von
Eduardo Giometti Bertogna
Francisco Muller Machado
Miguel Antonio Sovierzoski
Publikationsdatum
11.07.2020
Verlag
Springer Berlin Heidelberg
Erschienen in
Health and Technology / Ausgabe 5/2020
Print ISSN: 2190-7188
Elektronische ISSN: 2190-7196
DOI
https://doi.org/10.1007/s12553-020-00464-z

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