Open Access

ARTICLE

A Mobile Cloud-Based eHealth Scheme

by Yihe Liu, Aaqif Afzaal Abbasi, Atefeh Aghaei, Almas Abbasi, Amir Mosavi, Shahaboddin Shamshirband, Mohammed A. A. Al-qaness

1 Data Recovery Key Laboratory of Sichuan Province, College of Computer Science and AI, Neijiang Normal University, Neijiang, 641100, China.
2 Department of Software Engineering, Foundation University, Islamabad, 44000, Pakistan.
3 Department of Communication, Faculty of Social Sciences, University of Tehran, Tehran, 1417466191, Iran.
4 Department of Computer Science, International Islamic University, Islamabad, 46000, Pakistan.
5 Institute of Research and Development, Duy Tan University, Da Nang, 550000, Vietnam.
6 Kalman Kando Faculty of Electrical Engineering, Obuda University, Budapest, 1034, Hungary.
7 School of the Built Environment, Oxford Brookes University, Oxford, OX3 0BP, UK.
8 Department for Management of Science and Technology Development, Ton Duc Thang University, Ho Chi Minh City, Vietnam.
9 Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam.
10 School of Computer Science, Wuhan University, Wuhan, 430072, China.

* Corresponding Author: Shahaboddin Shamshirband. Email: .

Computers, Materials & Continua 2020, 63(1), 31-39. https://doi.org/10.32604/cmc.2020.07708

Received 20 June 2019; Accepted 25 August 2019; Issue published 30 March 2020

Abstract

Mobile cloud computing is an emerging field that is gaining popularity across borders at a rapid pace. Similarly, the field of health informatics is also considered as an extremely important field. This work observes the collaboration between these two fields to solve the traditional problem of extracting Electrocardiogram signals from trace reports and then performing analysis. The developed system has two front ends, the first dedicated for the user to perform the photographing of the trace report. Once the photographing is complete, mobile computing is used to extract the signal. Once the signal is extracted, it is uploaded into the server and further analysis is performed on the signal in the cloud. Once this is done, the second interface, intended for the use of the physician, can download and view the trace from the cloud. The data is securely held using a password-based authentication method. The system presented here is one of the first attempts at delivering the total solution, and after further upgrades, it will be possible to deploy the system in a commercial setting.

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Citations