slugAn Approach for Estimation of Obstructive Sleep Apnea Syndrome from EEG
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2014, Vol 2, Issue 4
Abstract
Sleep is a corporeal mechanism which achieves recuperative functions for the brain and the body. To maintain a healthy status for most living organisms sleep is an essential criteria .Being a naturally recurring state it is characterized by reduced or absent consciousness , relatively suspended sensory activity, and inactivity of nearly all voluntary muscles . After the middle age, the upper respiratory tracts of some of individuals could shrink and which leads to obstruction of the nasal passages and snoring during sleep. This situation called apnea, could affect the quality of sleep and health when it occurs frequently, and may even cause death in severe cases. Obstructive sleep apnea syndrome is a situation where repeatedly upper airway stops off while the respiratory effort continues during sleep at least for 10 s. Bispectral analysis is an advanced signal processing technique particularly used for exhibiting quadratic phase - coupling that may arise between signal components with different frequencies. In this project, a new technique for recognizing patients with OSAS was introduced using bispectral characteristics of EEG signal and an artificial neural network. The amount of quadratic phase coupling in each sub band of EEG namely; delta, theta, alpha, beta and gamma, was calculated over bispectral density of EEG. Then, the obtained quadraphase couplings are fed to the input of the designed ANN. The recommended technique could be used in the development of an automatic OSAS identification system which will improve medical service and diagnostic capability.
Authors and Affiliations
Anju N S, E. Smily Jeya Jothi
Keywords
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