Sleep Apnea Detection From Heart Rate Variability Data Using A DWPT Based Technique

被引：0
|
作者：
Ali, Syeda Quratulain [1 ]
Jeoti, Varun [1 ]
Khalid, Sohail [1 ]
机构：
[1] Univ Teknol PETRONAS, Dept Elect & Elect Engn, Bandar Seri Iskandar 31750, Tronoh, Malaysia
来源：
2012 4TH INTERNATIONAL CONFERENCE ON INTELLIGENT AND ADVANCED SYSTEMS (ICIAS), VOLS 1-2 | 2012年
关键词：
ELECTROCARDIOGRAM; CLASSIFICATION;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Sleep Apnea is a clinical condition related to problematic breathing during the course of sleep. Nocturnal polysomnography (NPSG) is the traditional method to detect sleep apnea but it is costly and inconvenient. Research directions are turning towards signal processing based sleep apnea detection. This study focuses on a simple, fast and memory efficient method for detection of sleep apnea using Electrocardiogram (ECG) data from MIT online database. Discrete wavelet packet transform (DWPT) has been employed on RRI intervals (RRI), in band of interest (FOI) to highlight the frequency pattern differences in normal and abnormal cases. Cases based classification is 100% accurate.
引用
收藏
页码：622 / 626
页数：5
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