Automatic classification of excitation location of snoring sounds | |
Sun JP(孙井鹏)1,2,3 | |
刊名 | Journal of Clinical Sleep Medicine |
2021-05-01 | |
卷号 | 17期号:5页码:1031-1038 |
关键词 | machine learning multiscale entropy snore classification obstructive sleep apnea hypopnea syndrome |
英文摘要 | Study Objectives: For surgical treatment of patients with obstructive sleep apnea-hypopnea syndrome, it is crucial to locate accurately the obstructive sites in the upper airway; however, noninvasive methods for locating the obstructive sites have not been well explored. Snoring, as the cardinal symptom of obstructive sleep apnea-hypopnea syndrome, should contain information that reflects the state of the upper airway. Through the classification of snores produced at four different locations, this study aimed to test the hypothesis that snores generated by various obstructive sites differ. |
语种 | 英语 |
内容类型 | 期刊论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/44941] |
专题 | 自动化研究所_智能制造技术与系统研究中心_多维数据分析团队 |
作者单位 | 1.Institute of Automation, Chinese Academy of Sciences, Beijing, People’s Republic of China 2.University of Chinese Academy of Sciences, Beijing, People’s Republic of China 3.Division of Interdisciplinary Medicine and Biotechnology, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts |
推荐引用方式 GB/T 7714 | Sun JP. Automatic classification of excitation location of snoring sounds[J]. Journal of Clinical Sleep Medicine,2021,17(5):1031-1038. |
APA | Sun JP.(2021).Automatic classification of excitation location of snoring sounds.Journal of Clinical Sleep Medicine,17(5),1031-1038. |
MLA | Sun JP."Automatic classification of excitation location of snoring sounds".Journal of Clinical Sleep Medicine 17.5(2021):1031-1038. |
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