Title :
An intelligent sleep apnea detection system
Author :
Hsu, Chien-chang ; Shih, Ping-ta
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Fu Jen Catholic Univ., Taipei, Taiwan
Abstract :
This paper proposes an intelligent sleep apnea detection system. The system utilizes a band-pass filter to filter out components with extreme low and high frequencies from the electroencephalogram. It only conserves sleep-related bands from 0.5 to 32Hz. Moreover, it extracts frequency elements from Hilbert spectrum by Hilbert-Huang transformation. The system computes four Hilbert spectrum frequency intensities of the alpha, beta, theta, and delta signal from the transformed spectrum. The system then detects duration of obstructive sleep apnea from the frequency variation. The experimental results show that system can detect the duration of OSA as well as preserve time information in the electroencephalogram by Hilbert-Huang transformation mechanism and find frequency variation information.
Keywords :
Hilbert transforms; band-pass filters; electroencephalography; medical signal processing; Hilbert spectrum; Hilbert-Huang transformation; electroencephalogram; frequency element extraction; frequency variation; intelligent sleep apnea detection system; preserve time information; sleep-related bands; Band pass filters; Conferences; Electroencephalography; Feature extraction; IEEE Engineering in Medicine and Biology Society; Sleep apnea; Band-pass filter; Electroencephalogram; Frequency variation; Hilbert-Huang transformation; Sleep apnea detection;
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-6526-2
DOI :
10.1109/ICMLC.2010.5580688