基于物联网的便携式心电信号模糊诊断仪器的设计  

Design of Portable Fuzzy Diagnosis Instrument for ECG Signal Based on Internet of Things

作　　者：王凯 徐济成[2] 张钰 WANG Kai;XU Jicheng;ZHANG Yu(Department of Health Management,Bengbu Medical College,Bengbu,233030;School of Computer and Information,Anhui Agriculture University,Hefei,230027)

机构地区：[1]蚌埠医学院卫生管理学院,蚌埠市233030 [2]安徽农业大学计算机与信息学院,合肥市230027

出　　处：《中国医疗器械杂志》2019年第5期341-344,共4页Chinese Journal of Medical Instrumentation

基　　金：安徽省示范实验实训中心项目(2018sxzx58);安徽省教育厅人文社科重点项目(SK2018A1072);大规模在线开放课程示范项目(2018mooc278)

摘　　要：目的动态采集与处理心电信号,获取异常心电信号的分类信息。方法首先通过实时采集心电信号结合离散小波变换获取心电特征向量,然后计算心电信号模糊信息熵,最后利用欧氏距离获取心电信号的语义距离,得到异常信号的分类信息。结果该装置能够在基于物联网的嵌入式平台上实现异常心电信号的有效识别,提高心脏疾病的诊断精度。结论心电信号模糊诊断设备能够精确分类异常信号,输出具有高置信度区间的在线信号分类矩阵。Objective A method for dynamically collecting and processing ECG signals was designed to obtain classification information of abnormal ECG signals.Methods Firstly,the ECG eigenvectors were acquired by real-time acquisition of ECG signals combined with discrete wavelet transform,and then the ECG fuzzy information entropy was calculated.Finally,the Euclidean distance was used to obtain the semantic distance of ECG signals,and the classification information of abnormal signals was obtained.Results The device could effectively identify abnormal ECG signals on an embedded platform based on the Internet of Things,and improved the diagnosis accuracy of heart diseases.Conclusion The fuzzy diagnosis device of ECG signal could accurately classify the abnormal signal and output an online signal classification matrix with a high confidence interval.

关 键 词：ECG信号 模糊诊断 物联网 特征分类 

分 类 号：R318[医药卫生—生物医学工程]