传感技术学报2017，Vol.30Issue(10)：1602-1607,6.DOI:10.3969/j.issn.1004-1699.2017.10.025
基于贝叶斯网络的体域网多模态健康数据融合方法
A Multi-Modal Health Data Fusion Method in Body Sensor Networks Based on Bayesian Networks
摘要
Abstract
As an important branch of wireless sensor networks(WSNs)in biomedical field,body sensor networks ( BSNs) could remotely monitor a variety of human health data in real time. In this paper,we study a multi-modal health data fusion method based on the data collected in BSNs,in which we design a networking for BSNs including Holter sensor,blood pressure sensor and oxygen saturation sensor,and propose a method of myocardial ischemia mo-nitoring and identification based on Bayesian network model and reasoning algorithm. Single-modal Holter monitoring and multi-modal health monitoring were performed in 60 patients with confirmed heart disease,and it was proved that the proposed multi-modal health data fusion method could effectively improve the detection rate of a-symptomatic myocardial ischemia,providing a new auxiliary judgment method for clinical application.关键词
体域网/多模态/数据融合/贝叶斯网络Key words
body sensor network/multi-modal/data fusion/bayesian network分类
信息技术与安全科学引用本文复制引用
史春燕,翟羽婷,王磊..基于贝叶斯网络的体域网多模态健康数据融合方法[J].传感技术学报,2017,30(10):1602-1607,6.基金项目
江苏省政策引导类计划(产学研合作)—前瞻性联合研究项目(BY2016049-01) （产学研合作）
