QQ客服 官方微博 反馈留言

	A Novel Deep Learning Based Approach for Continuous Blood Pressure Estimation
	Xueliang Liu; Fen Miao; Ye Li
	2017
会议日期	2017
会议地点	Jeju Island, Korea
英文摘要	Continuous blood pressure (BP) estimation using machine learning techniques has attracted increasing attention recently. In this study, a novel deep learning based approach is proposed to estimate BP with electrocardiogram (ECG) and photoplethysmographic (PPG) signals. Experimental results based on 73 subjects showed that the proposed approach had an excellent accuracy in BP estimation with a correlation coefficient of 0.88 and a mean error of -0.16 ± 6.72 mmHg for systolic BP, and 0.89 and −0.46± 4.37 mmHg for diastolic BP. Therefore, the proposed approach provided a potential novel insight for the continuous BP estimation.
语种	英语
内容类型	会议论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/12700]
专题	深圳先进技术研究院_数字所
作者单位	2017
推荐引用方式 GB/T 7714	Xueliang Liu,Fen Miao,Ye Li. A Novel Deep Learning Based Approach for Continuous Blood Pressure Estimation[C]. 见:. Jeju Island, Korea. 2017.

个性服务

查看访问统计

相关权益政策

暂无数据

收藏/分享

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。