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Authors:
Paul Fortier
Patrick DaSilva
Kristen Sethares
Keywords: Embedded ECG sensor, real-time algorithm, ECG classification
Abstract:
Current mobile monitoring solutions do not offer the ability to recognize cardiac problems without human interpretation. A combination of electrocardiogram (ECG) detection and classification software running on a mobile cardiovascular disease detection sensor is proposed to replace the need for human interpretation. The ECG is filtered using the Wavelet Transform; the ECG wave points detected using a modified version of the Pan Tompkins rule set and the cardiac rhythm is classified using an N-ary tree. The wireless mobile application is designed on a custom printed circuit board (PCB). Testing results show autonomous classifications are possible using a three lead ECG system while the patient is at rest. The proposed solution serves as a stepping stone towards a fully reliable patient disease management teaching tool with the potential to serve as an aid to the cardiovascular healthcare industry.
Pages: 1 to 6
Copyright: Copyright (c) IARIA, 2014
Publication date: November 16, 2014
Published in: conference
ISSN: 2308-4405
ISBN: 978-1-61208-374-2
Location: Lisbon, Portugal
Dates: from November 16, 2014 to November 20, 2014