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On Improvement of Detection of Obstructive Sleep Apnea by Partial Least Square-based Extraction of Dynamic Features

机译:基于偏最小二乘的动态特征提取改善阻塞性睡眠呼吸暂停的检测

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摘要

This paper presents a methodology for Obstructive Sleep Apnea (OSA) detection based on the HRV analysis, where as a measure of relevance PLS is used. Besides, two different combining approaches for the selection of the best set of contours are studied. Attained results can be oriented in research focused on finding alternative methods minimizing the HRV-derived parameters used for OSA diagnosing, with a diagnostic accuracy comparable to a polysomnogram. For two classes (normal, apnea) the results for PLS are: specificity 90%, sensibility 91% and accuracy 93.56%.
机译:本文介绍了一种基于HRV分析的阻塞性睡眠呼吸暂停(OSA)检测方法,其中使用了相关性PLS量度。此外,研究了两种用于选择最佳轮廓的组合方法。获得的结果可以集中在研究上,其重点是寻找可替代的方法,以最小化HRV衍生的OSA诊断参数,其诊断准确性可与多导睡眠图相媲美。对于两类(正常,呼吸暂停),PLS的结果为:特异性90%,敏感性91%和准确性93.56%。

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