Title :
A noninvasive technique for detecting obstructive and central sleep apnea
Author :
Yen, Fu-Chung ; Behbehani, Khosrow ; Lucas, Edgar A. ; Burk, John R. ; Axe, John R.
Author_Institution :
Dept. of Biomed. Eng., Texas Univ., Arlington, TX, USA
Abstract :
A new noninvasive method to detect obstructive and central sleep apnea [(OSA) and (CSA)] events is described. Data were collected from ten volunteer subjects with a previous diagnosis of OSA while they were titrated for continuous positive airway pressure (CPAP) therapy. Apneic events were identify by analyzing of estimated airway impedance determined from pressure and airflow signals delivered from CPAP. To enhance performance of this technique, a single-frequency (5 Hz with 0.5 cmH 2O peak-to-peak amplitude) probing signal was superimposed on the applied CPAP pressure. The results indicated that estimated airway impedance during OSA (mean: 17.9, SD: 3.4, N=50) was significantly higher then during CSA (mean: 4.1, SD: 1.7, N=50). When the estimated impedance of OSA and CSA events were compared to a fixed threshold, 100% of all events can be correctly categorized. These results indicate that it may be possible to diagnose OSA and CSA noninvasively based upon this technique. The instrument and the algorithm required are relatively simple and can be incorporated in a home-based device. If this method was used for prescreening apnea patients, it could reduce cost, waiting time, and discomfort associated with traditional diagnostic procedures.
Keywords :
medical signal processing; pneumodynamics; pressure measurement; signal detection; airflow signals; algorithm; apneic events; central sleep apnea; discomfort reduction; estimated airway impedance; home-based device; instrument; noninvasive technique; obstructive apnea; volunteer subjects; Biomedical engineering; Biomedical measurements; Electromyography; Esophagus; Event detection; Impedance; Medical treatment; Signal analysis; Sleep apnea; Surgery; Airway Resistance; Algorithms; Female; Humans; Male; Middle Aged; Models, Biological; Nose; Polysomnography; Positive-Pressure Respiration; Random Allocation; Respiratory System; Sleep Apnea Syndromes;
Journal_Title :
Biomedical Engineering, IEEE Transactions on