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

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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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Acknowledgments

The authors acknowledge the Federal University of Technology - Paraná for its support even though there were no funds or grants received from that institution.

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This study has not received any kind of fund or grant.

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Authors and Affiliations

  1. Graduate Program in Technological Innovation – PPGIT, Federal University of Technology – Paraná – UTFPR, Campo Mourão, PR, Brazil

    Eduardo Giometti Bertogna

  2. Academic Department of Electronics – DAELN, Federal University of Technology – Paraná – UTFPR, Curitiba, PR, Brazil

    Francisco Muller Machado & Miguel Antonio Sovierzoski

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  1. Eduardo Giometti Bertogna
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  2. Francisco Muller Machado
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  3. Miguel Antonio Sovierzoski
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Correspondence to Eduardo Giometti Bertogna.

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Bertogna, E.G., Machado, F.M. & Sovierzoski, M.A. An optimized ECG android system using data compression scheme for cloud storage. Health Technol. 10, 1163–1171 (2020). https://doi.org/10.1007/s12553-020-00464-z

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  • DOI: https://doi.org/10.1007/s12553-020-00464-z

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