Apnea and Hypopnea Events Classification Using Amplitude Spectrum Trend Feature of Snores | |
Jingpeng, Sun; Xiyuan, Hu; Yingying, Zhao; Shuchen, Sun; Chen, Chen; Silong, Peng | |
2018 | |
会议名称 | 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) |
会议日期 | July 17 - July 21 |
会议地点 | Hawaii, USA |
摘要 | Research on snores for Obstructive Sleep Apnea Syndrome (OSAS) diagnosis is a new trend in recent years. In this paper, we proposed a snore-based apnea and hypopnea events classification approach. Firstly,we define the snores after the apnea event and during the hypopnea event as apnea-eventsnore (AES) and hypopnea-event-snore (HES), respectively. Then, we design a new feature from the trend of the amplitude spectrum of snores. The newly proposed feature can be viewed as an improvement of the Mel-frequency cepstral coefficient (MFCC) feature, which is well-known for speech recognition. The extracted features were fed to principle component analysis (PCA) for dimension reduction and support vector machine (SVM) for apnea and hypopnea events classification. The experimental results demonstrate the efficiency of the proposed algorithm in using snores to classify apnea and hypopneaevents. |
收录类别 | EI |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/26225 |
专题 | 智能制造技术与系统研究中心_多维数据分析(彭思龙)-技术团队 |
通讯作者 | Xiyuan, Hu |
作者单位 | 1.Institute of Automation, Chinese Academy of Sciences 2.Guanganmen Hospital, China Academy of Chinese Medical |
推荐引用方式 GB/T 7714 | Jingpeng, Sun,Xiyuan, Hu,Yingying, Zhao,et al. Apnea and Hypopnea Events Classification Using Amplitude Spectrum Trend Feature of Snores[C],2018. |
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Apnea and Hypopnea E(723KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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