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Sensors 2014, 14(6), 11031-11044; doi:10.3390/s140611031

A Mobile Device System for Early Warning of ECG Anomalies

AGH University of Science and Technology, Faculty of Physics and Applied Computer Science, 30 Mickiewicza Av., PL-30059, Krakow 004812, Poland
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Received: 13 March 2014 / Revised: 5 June 2014 / Accepted: 10 June 2014 / Published: 20 June 2014
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Abstract

With the rapid increase in computational power of mobile devices the amount of ambient intelligence-based smart environment systems has increased greatly in recent years. A proposition of such a solution is described in this paper, namely real time monitoring of an electrocardiogram (ECG) signal during everyday activities for identification of life threatening situations. The paper, being both research and review, describes previous work of the authors, current state of the art in the context of the authors’ work and the proposed aforementioned system. Although parts of the solution were described in earlier publications of the authors, the whole concept is presented completely for the first time along with the prototype implementation on mobile device—a Windows 8 tablet with Modern UI. The system has three main purposes. The first goal is the detection of sudden rapid cardiac malfunctions and informing the people in the patient’s surroundings, family and friends and the nearest emergency station about the deteriorating health of the monitored person. The second goal is a monitoring of ECG signals under non-clinical conditions to detect anomalies that are typically not found during diagnostic tests. The third goal is to register and analyze repeatable, long-term disturbances in the regular signal and finding their patterns. View Full-Text
Keywords: ambient intelligence; ECG anomalies; heart anomaly alert; ECG monitoring for mobile devices ambient intelligence; ECG anomalies; heart anomaly alert; ECG monitoring for mobile devices
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Szczepański, A.; Saeed, K. A Mobile Device System for Early Warning of ECG Anomalies. Sensors 2014, 14, 11031-11044.

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