Identifying sleep apnea syndrome using heart rate and breathing effort variation analysis based on ballistocardiography

Weichao Zhao, Hongbo Ni, Xingshe Zhou, Yalong Song, Tianben Wang

科研成果: 书/报告/会议事项章节会议稿件同行评审

22 引用 (Scopus)

摘要

Sleep apnea syndrome (SAS) is regarded as one of the most common sleep-related breathing disorders, which can severely affect sleep quality. Since SAS is usually accompanied with the cyclical heart rate variation (HRV), many studies have been conducted on heart rate (HR) to identify it at an earlier stage. While most related work mainly based on clinical devices or signals (e.g., polysomnography (PSG), electrocardiography (ECG)), in this paper we focus on the ballistocardiographic (BCG) signal which is obtained in a non-invasive way. Moreover, as the precision and reliability of BCG signal are not so good as PSG or ECG, we propose a fine-grained feature extraction and analysis approach in SAS recognition. Our analysis takes both the basic HRV features and the breathing effort variation into consideration during different sleep stages rather than the whole night. The breathing effort refers to the mechanical interaction between respiration and BCG signal when SAS events occur, which is independent from autonomous nervous system (ANS) modulations. Specifically, a novel method named STC-Min is presented to extract the breathing effort variation feature. The basic HRV features depict the ANS modulations on HR and Sample Entropy and Detrended Fluctuation Analysis are applied for the evaluations. All the extracted features along with personal factors are fed into the knowledge-based support vector machine (KSVM) classification model, and the prior knowledge is based on dataset distribution and domain knowledge. Experimental results on 42 subjects in 3 nights validate the effectiveness of the methods and features in identifying SAS (90.46% precision rate and 88.89% recall rate).

源语言英语
主期刊名2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
出版商Institute of Electrical and Electronics Engineers Inc.
4536-4539
页数4
ISBN(电子版)9781424492718
DOI
出版状态已出版 - 4 11月 2015
活动37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 - Milan, 意大利
期限: 25 8月 201529 8月 2015

出版系列

姓名Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
2015-November
ISSN(印刷版)1557-170X

会议

会议37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
国家/地区意大利
Milan
时期25/08/1529/08/15

指纹

探究 'Identifying sleep apnea syndrome using heart rate and breathing effort variation analysis based on ballistocardiography' 的科研主题。它们共同构成独一无二的指纹。

引用此