کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
469379 698311 2007 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Inspiratory flow shape clustering: An automated method to monitor upper airway performance during sleep
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر علوم کامپیوتر (عمومی)
پیش نمایش صفحه اول مقاله
Inspiratory flow shape clustering: An automated method to monitor upper airway performance during sleep
چکیده انگلیسی

We describe an automated method for monitoring airflow dynamics in the upper airway of a sleeping subject. Its main task is to determine a set of inspiratory flow shape representatives and their relative incidence in a given respiratory airflow material. The flow shape clustering aims at reducing redundant information in the data, and thereby decreases the time needed to score overnight sleep recordings. Compared with previous computer-assisted systems, built on a pre-defined classification of prototype shapes, we require no a priori assumptions of the flow shape clusters to be discovered. The intrinsic flow shape clustering is performed with a modification of the Isodata algorithm, and the K-means clustering is used as a reference in comparison studies. The operation of the method is demonstrated on clinical sleep recordings both from patients with nocturnal breathing disorders and from non-symptomatic individuals. The feasible results obtained in the practical research design suggest that application of clustering algorithms to respiratory airflow measurements could give important insights into the subtle flow shape abnormalities underlying obstructive sleep-disordered breathing.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer Methods and Programs in Biomedicine - Volume 85, Issue 1, January 2007, Pages 8–18
نویسندگان
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