Yadollahi Azadeh, Moussavi Zahra
Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, MB, Canada.
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:2563-6. doi: 10.1109/IEMBS.2009.5335292.
Formant frequencies of snore and breath sounds represent resonance in the upper airways; hence, they change with respect to the upper airway anatomy. Therefore, formant frequencies and their variations can be examined to distinguish between snore and breath sounds. In this paper, formant frequencies of snore and breath sounds are investigated and automatically grouped into 7 clusters based on K-Means clustering. First, formants clusters of breath and snore sounds of all subjects were investigated together and their union were calculated as the most probable ranges of the formants. The ranges for the first four formants which span the main frequency components of breath and snore sounds were found to be [20-400]Hz, [270-840]Hz, [500-1380]Hz and [910-1920]Hz. These ranges were then used as priori information to recalculate the formants of snore and breath sounds separately. Statistical t-test showed the 1(st) and 3(rd) formants to be the most characteristic features in distinguishing the breath and snore sounds from each other.
鼾声和呼吸声的共振峰频率代表上呼吸道的共振；因此，它们会随着上呼吸道解剖结构的变化而改变。所以，可以通过检查共振峰频率及其变化来区分鼾声和呼吸声。在本文中，对鼾声和呼吸声的共振峰频率进行了研究，并基于K均值聚类自动将其分为7类。首先，对所有受试者的呼吸声和鼾声的共振峰聚类进行了共同研究，并计算它们的并集作为共振峰最可能的范围。发现跨越呼吸声和鼾声主要频率成分的前四个共振峰的范围分别为[20 - 400]Hz、[270 - 840]Hz、[500 - 1380]Hz和[910 - 1920]Hz。然后将这些范围用作先验信息，分别重新计算鼾声和呼吸声的共振峰。统计t检验表明，第一和第三共振峰是区分呼吸声和鼾声的最具特征性的特征。
