Abstract
Nowadays, Cardiovascular Disease (CVD) is one of the most catastrophic and life threatening common health issues. Early detection of CVD is one of the most important solutions to reduce its devastating effects on health. In this paper, an efficient detection algorithm is identified. The algorithm uses patient demographic data as inputs, along with several ECG signal features extracted automatically through signal processing techniques. Cross-validation results show a 98.29% accuracy for the algorithm. The algorithm is also integrated into a web based system that can be used at anytime by patients to check their heart health status. At one end of the system is the ECG sensor attached to the patient’s body, while at the other end is the detection algorithm. Communication between the two ends is done through an Android application.
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Alshraideh, H., Otoom, M., Al-Araida, A., Bawaneh, H., Bravo, J. (2014). A Web Based Cardiovascular Disease Detection System. In: Hervás, R., Lee, S., Nugent, C., Bravo, J. (eds) Ubiquitous Computing and Ambient Intelligence. Personalisation and User Adapted Services. UCAmI 2014. Lecture Notes in Computer Science, vol 8867. Springer, Cham. https://doi.org/10.1007/978-3-319-13102-3_40
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DOI: https://doi.org/10.1007/978-3-319-13102-3_40
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-13101-6
Online ISBN: 978-3-319-13102-3
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