Feature Extraction of Upper Airway Dynamics during Sleep Apnea using Electrical Impedance Tomography

Abstract

characterizing upper airway occlusion during natural sleep could be instrumental for studying the dynamics of sleep apnea and designing an individualized treatment plan. in recent years, obstructive sleep apnea (oSA) phenotyping has gained attention to classify oSA patients into relevant therapeutic categories. electrical impedance tomography (eit) has been lately suggested as a technique for noninvasive continuous monitoring of the upper airway during natural sleep. in this paper, we developed the automatic data processing and feature extract methods to handle acquired eit data for several hours. Removing ventilation and blood flow artifacts, EIT images were reconstructed to visualize how the upper airway collapsed and reopened during the respiratory event. from the time series of reconstructed eit images, we extracted the upper airway closure signal providing quantitative information about how much the upper airway was closed during collapse and reopening. features of the upper airway dynamics were defined from the extracted upper airway closure signal and statistical analyses of ten oSA patients' data were conducted. the results showed the feasibility of the new method to describe the upper airway dynamics during sleep apnea, which could be a new step towards oSA phenotyping and treatment planning.

A Comprehensive Review: Computational Models for Obstructive Sleep Apnea Detection in Biomedical Applications

“…Most of the frequency domain features are extracted using WT, as WT uses a multiscale basis, and it is advantageous over Fourier transforms. The varying window size is taken for nonstationary signals, hence providing a better extraction of features [ 87 , 88 ]. Statistical feature analysis is implemented to identify errors that are not identified during the initial stages of signal processing.…”

“…The upper airway closure signal is extracted as a feature along with statistical analysis. The features are analyzed by one-way analysis of variance (ANOVA) test, where the patients' features are displayed as a box and whisker plots and heat map clusters [ 87 ]. Mostafa et al [ 47 ] extracted seven features from SpO 2 signal using genetic algorithm.…”

Evaluation of Ecological Water Consumption in Yanhe River Basin Based on Big Data

“…On the basis of feature extraction [ 11 ], feature data preprocessing first deals with missing values to meet the modeling requirements. Then, based on complex nonlinear feature decomposition and image data dimension reduction, lumped transformation is carried out to obtain lumped feature factor information of the whole basin.…”

A narrative review of electrical impedance tomography in lung diseases with flow limitation and hyperinflation: methodologies and applications

“…Global tidal variation, expiratory time constants Breath-by-breath regional expiratory time constants is feasible, which could be used to adjust mechanical ventilation according to regional airflow obstruction were placed around the chest at the 4 th to 6 th intercostal spaces in most cases, except in three studies of patients with obstructive sleep apnea (OSA), where the electrodes were placed around the lower head above the neck to measure the airway occlusion (18,20,43). As the impedance-volume ratio may be significantly influenced by the position of the electrode plane and volume excursion (57,58), we strongly advise against the placement of electrodes lower than the 5 th intercostal space during spirometry testing.…”

“…EIT around the chest wall shows that lung volume changes differ between those with versus without OSA (51). Furthermore, new electrode placement designs and reconstruction algorithms enable the detection of upper airway collapse (18,20,43).…”