Sleep-Apnea Detection with the Lempel-Ziv Complexity Analysis of the Electrocardiogram and Respiratory Signals
Authors/Creators
- 1. Kocaeli University, Institute of Science and Technology, Biomedical Engineering, Kocaeli, Türkiye
- 2. Kocaeli University, Faculty of Technology, Biomedical Engineering, Kocaeli, Türkiye
Description
Sleep apnea is a common and life-threatening disease. Diagnosis of the disease is as important as its treatment. A remarkable increase is observed in the number of diagnosed patients with the increase in public awareness and the increase in the rate of being noticed by physicians. Polysomnography measurements used in the diagnosis of sleep apnea disturb the patient and require more than one physiological data collection. Due to such problems, new analysis methods are being investigated. Since Lempel-Ziv is a fast and non-linear signal processing method, it is very suitable for processing physiological data. By using the Lempel-Ziv complexity method, it is aimed to diagnose the disease with less time and less data. In line with this goal, the treatment process will also be brought forward. Disease detection studies were carried out by using ECG and respiratory data from the Physionet.org database.
As a result of the analyzes, it was observed that there was a significant difference in the time intervals with apnea from the ECG, chest respiration (Resp C) and abdominal respiration (Resp A) data. With this method, sleep apnea can be diagnosed for EKG, Resp C and Resp A.