A Novel Feature Extraction Method for Signal Quality Assessment of Arterial Blood Pressure for Monitoring Cerebral Autoregulation
文献类型：会议论文
| 作者 | Pandeng Zhang; Jia Liu; Xinyu Wu; Xiaochang Liu; Qingchun Gao |
| 出版日期 | 2010 |
| 会议名称 | 4th International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2010 |
| 英文摘要 | In this paper, we proposed a novel method of signal quality assessment of arterial blood pressure for monitoring Cerebral Autoregulation (CA). This method is based on algorithm of signal abnormality index (SAI). Two simple and effective features-end diastole slope sum (EDSS) and slow ejection slope sum (SESS), were proposed to identify abnormal beats from ABP as CA input in real-time. The methods of cumulative distribution function (CDF) and receiver operating characteristic (ROC) analysis were used to select best feature and confirm the parameter of the feature. Using the best feature with SAI model, we can directly estimate the signal quality of ABP in CA assessment. It has been tested in the data of CAassessment experiment and compared to an expert annotator, the algorithm's sensitivity is 93.95%, and specificity is 84.87% |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/2889]  |
| 专题 | 深圳先进技术研究院_集成所 |
| 作者单位 | 2010 |
| 推荐引用方式 GB/T 7714 | Pandeng Zhang,Jia Liu,Xinyu Wu,et al. A Novel Feature Extraction Method for Signal Quality Assessment of Arterial Blood Pressure for Monitoring Cerebral Autoregulation[C]. 见:4th International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2010. |
入库方式： OAI收割
来源：深圳先进技术研究院
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