新生儿呼吸信号干扰呼吸检测算法的比较研究

M. Schmidt , B. Foitzik , R.R. Wauer , F. Winkler , G. Schmalisch
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引用次数: 40

摘要

正确检测呼吸信号中的吸气起始和呼气起始是准确进行新生儿肺功能检测的必要前提。研究了五种使用气相摄影测量的流量和体积信号进行呼吸检测的算法的错误率。为了比较和评估这些算法的可靠性,我们使用了来自自主呼吸新生儿的12个最小干扰和12个严重干扰的流量和体积信号。除了基于沃尔什变换信号的算法外,如果干扰最小,所有算法都可靠地工作(错误率<1.1%)。在严重干扰的信号中,算法之间存在很大的差异。经过测试的最稳健的算法(触发流量信号并对识别的呼吸进行额外的合理性检查)导致错误率为3.4%。并非所有被测试的算法都适合实时应用,因为它们在呼吸检测的延迟时间上差别很大。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparative Investigations of Algorithms for the Detection of Breaths in Newborns with Disturbed Respiratory Signals

The correct detection of the beginning of inspiration and expiration in the respiratory signals is an essential prerequisite for accurate lung function testing in newborns. Five algorithms for breath detection using pneumotachographically measured flow and volume signals were investigated with regard to the error rate. To compare and to evaluate the reliability of these algorithms 12 minimally and 12 severely disturbed flow and volume signals from spontaneously breathing newborns were used. With the exception of an algorithm based on Walsh-transformed signals, all algorithms work reliably (error rate <1.1%) if disturbances are minimal. In severely disturbed signals there is a great difference between the algorithms. The most robust algorithm tested (trigger of the flow signal with an additional plausibility check of the recognized breath) resulted in an error rate of <3.4%. Not all algorithms tested are suitable for real-time applications because they differ considerably in delay time for breath detection.

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