基于小波信息熵谱的阻塞性睡眠呼吸暂停自动准确检测

Fugui Qi, Jianqi Wang, A. Fathy
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引用次数: 2

摘要

一种精确的非接触检测阻塞性睡眠呼吸暂停(OSA)的新方法已经开发并将在这里介绍。通常,非接触式测量优先用于婴儿、严重烧伤患者和呼吸道传染病患者等。该方法基于小波信息熵的概念,根据患者呼吸信号的强烈异常、复杂结构和紊乱对呼吸暂停进行清晰的分类。该方法的准确性已经过实验验证,并在生物雷达上证明了超过93%的准确性。
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Automatic and Accurate Non-contact Obstructive Sleep Apnea Detection using Wavelet Information Entropy Spectrum
An accurate non-contact novel detection method for obstructive sleep apnea (OSA) has been developed and will be presented here. Typically, non-contact measurement is preferred for babies, brutally burnt patients, and patients with respiratory contagious diseases, etc. The developed method is based on wavelet information entropy concepts that would clearly classify apnea by the strong abnormality, complex structure and disorder of the patient’s respiratory signal. The accuracy of this method has been experimentally validated, and demonstrated over 93% accuracy using a bio-radar.
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