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An Intelligent Algorithm for Home Sleep Apnoea Test Device

An Intelligent Algorithm for Home Sleep Apnoea Test Device

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Author(s): Ahsan H. Khandoker (The University of Melbourne, Australia)
Copyright: 2012
Pages: 15
Source title: Machine Learning: Concepts, Methodologies, Tools and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-60960-818-7.ch516

Keywords: Artificial Intelligence / Computational Intelligence / Computer Science & IT / Information Science Reference

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Abstract

In this chapter authors try to develop a system for Sleep apnea with the help of machine learning algorithms using ECG signals. The application of an intelligent machine learning technique (Support Vector Machines, SVM) to diagnose the patients with sleep apnea syndrome using Electrocardiogram (ECG) signal. Sleep apnea syndrome is a medical condition caused by sleep apnea which is defined as the cessation of breathing for short periods during sleep.

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