呼吸量波形的建模和分类

G. Sita, I. Murthy
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引用次数: 0

摘要

提出了一种将呼吸容积波形(RVW)分为正常和异常呼吸通路的方法。该方法利用离散余弦变换(DCT)将时间序列变换到频域,并对变换后的信号进行极点零建模。以模型极点角为特征向量的贝叶斯分类器在对深度和快速机动下记录的有限数量的RVWs进行分类时表现令人满意。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modelling and classification of respiratory volume wavefourms
A technique is proposed for classifying respiratory volume waveforms(RVW) into normal and abnormal categories of respiratory pathways. The proposed method transforms the temporal sequence into frequency domain by using an orthogonal transform, namely discrete cosine transform (DCT) and the transformed signal is pole-zero modelled. A Bayes classifier using model pole angles as the feature vector performed satisfactorily when a limited number of RVWs recorded under deep and rapid (DR) manoeuvre are classified.
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