An optimized ECG android system using data compression scheme for cloud storage
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ORIGINAL PAPER
An optimized ECG android system using data compression scheme for cloud storage Eduardo Giometti Bertogna 1
&
Francisco Muller Machado 2 & Miguel Antonio Sovierzoski 2
Received: 10 June 2020 / Accepted: 8 July 2020 # IUPESM and Springer-Verlag GmbH Germany, part of Springer Nature 2020
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. Keywords Electrocardiography . Data compression . Processing consumption . Cloud storage
1 Introduction Electrocardiogram (ECG) represents the electrical activity from the heart in a graphical manner. It is a result of electrical pulses due to the original impulse at the sinusoidal nodule in the heart with the activity of the heart muscles. ECG data signals can be stored from patients with heart disease for further arrhythmia detection among its signal components, or for simply monitoring the signal itself. Nevertheless, there are limitations when ECG data must be stored locally. At first, huge amounts of data may be produced depending on the
* Eduardo Giometti Bertogna [email protected] 1
Graduate Program in Technological Innovation – PPGIT, Federal University of Technology – Paraná – UTFPR, Campo Mourão, PR, Brazil
2
Academic Department of Electronics – DAELN, Federal University of Technology – Paraná – UTFPR, Curitiba, PR, Brazil
number of leads, data acquisition resolution and sample rate used while obtaining the ECG signal and some compression scheme becomes mandatory. The ECG data compression is a critical task. It
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