Discriminating apneic snorers and benign snorers based on snoring formant extracted via a noise-robust linear prediction technique
Discriminating apneic snorers and benign snorers based on snoring formant extracted via a noise-robust linear prediction technique
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基于通过抗噪声线性预测技术提取的打鼾共振峰来区分呼吸暂停打鼾者和良性打鼾者
DOI：
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发表时间：
2010
期刊：
影响因子：
--
通讯作者：
陽介 木内
中科院分区：
文献类型：
--
作者：
崇宏 榎本;U. Abeyratne;Tetsuya Kusumoto;正武 芥川;Eiji Kondo;Ikuji Kawada;Takahiro Azuma;信典 小中;陽介 木内
打鼾是阻塞性睡眠呼吸暂停（OSA）最早和最常见的症状。然而，打鼾的定量分析目前还没有用于疾病的临床诊断。几位研究人员报道了基于线性预测编码（LPC）分析的呼吸暂停和良性打鼾（SS）的共振峰频率的差异。但是扩频信号是复杂的信号，并且存在局部低信噪比.这种信号复杂性会降低共振峰估计的准确性。在本文中，我们提出了一种新的方法来诊断阻塞性睡眠呼吸暂停的基础上共振峰的SS，通过噪声鲁棒线性预测技术提取。该方法和现有的基于LPC的方法进行了比较，通过一个措施，这表明第一共振峰频率的标准偏差。所提出的方法的性能进行了评估的临床打鼾的声音记录在一家医院的睡眠诊断中心的实验室过夜的数据库。与现有的基于LPC的方法相比，我们表明，所提出的方法可以区分（敏感性：88.9%，特异性：88.9%，AUC：0.85）良性打鼾（呼吸暂停低通气指数，AHI = 6.0 ± 3.2事件/h; 6188次）和呼吸暂停打鼾（AHI = 40.7 ± 20.2事件/h; 14066次）。
Snoring is the earliest and the most common symptom of Obstructive Sleep Apnea (OSA). Quantitative analysis of snoring, however, is not used at present in the clinical diagnosis of the disease. Several researchers have reported differences in the formant frequencies of Apneic and benign snoring sounds (SS) based on linear prediction coding (LPC) analysis. However, SS is complex signal and at local low signal to noise ratio (SNR). This signal complexity should reduce the accuracy of formant estimation. In this paper, we propose a novel approach to the diagnosis of OSA based on the formants of SSs, extracted via a noise-robust linear prediction technique. The proposed method and existing LPC-based method are compared via a measure, a which indicates the standard deviation of first formant frequencies. The performance of the proposed method was evaluated on a database of clinical snoring sounds recorded overnight in the laboratory of a hospital sleep diagnostic center. Compared with existing LPC-based method, we show that the proposed method can differentiate (sensitivity: 88.9%, specificity: 88.9%, AUC: 0.85) between benign snoring (Apnea Hypopnea Index, AHI = 6.0 ± 3.2 event/h; 6188 episodes) and apneic snoring (AHI = 40.7 ± 20.2 event/h; 14066 episodes).
DOI：
10.1164/rccm.200505-702oc
发表时间：
2005-12-01
影响因子：
24.7
作者：
Arzt, M;Young, T;Bradley, TD
通讯作者：
Bradley, TD