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Sensors 2013, 13(5), 6141-6170; doi:10.3390/s130506141

Algorithms Based on CWT and Classifiers to Control Cardiac Alterations and Stress Using an ECG and a SCR

DeustoTech-Life Unit, DeustoTech Institute of Technology, University of Deusto, 48007 Bilbao, Spain
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Received: 12 April 2013 / Revised: 8 May 2013 / Accepted: 8 May 2013 / Published: 10 May 2013
(This article belongs to the Section Biosensors)

Abstract

This paper presents the results of using a commercial pulsimeter as an electrocardiogram (ECG) for wireless detection of cardiac alterations and stress levels for home control. For these purposes, signal processing techniques (Continuous Wavelet Transform (CWT) and J48) have been used, respectively. The designed algorithm analyses the ECG signal and is able to detect the heart rate (99.42%), arrhythmia (93.48%) and extrasystoles (99.29%). The detection of stress level is complemented with Skin Conductance Response (SCR), whose success is 94.02%. The heart rate variability does not show added value to the stress detection in this case. With this pulsimeter, it is possible to prevent and detect anomalies for a non-intrusive way associated to a telemedicine system. It is also possible to use it during physical activity due to the fact the CWT minimizes the motion artifacts.
Keywords: ECG; arrhythmia; extrasystole; heart rate; SCR; CWT; stress; cardiac alterations; signal processing; J48 ECG; arrhythmia; extrasystole; heart rate; SCR; CWT; stress; cardiac alterations; signal processing; J48
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

Villarejo, M.V.; Zapirain, B.G.; Zorrilla, A.M. Algorithms Based on CWT and Classifiers to Control Cardiac Alterations and Stress Using an ECG and a SCR. Sensors 2013, 13, 6141-6170.

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