[1]谢俊松,倪飞舟,陈浩强.基于G-sensor有运动情景动态心电监护系统[J].中国医学物理学杂志,2021,38(8):996-1000.[doi:DOI:10.3969/j.issn.1005-202X.2021.08.015]
 XIE Junsong,NI Feizhou,CHEN Haoqiang.G-sensor-based dynamic electrocardiogram monitoring system with recognition of motion states[J].Chinese Journal of Medical Physics,2021,38(8):996-1000.[doi:DOI:10.3969/j.issn.1005-202X.2021.08.015]
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基于G-sensor有运动情景动态心电监护系统()
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《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
38卷
期数:
2021年第8期
页码:
996-1000
栏目:
医学信号处理与医学仪器
出版日期:
2021-08-02

文章信息/Info

Title:
G-sensor-based dynamic electrocardiogram monitoring system with recognition of motion states
文章编号:
1005-202X(2021)08-0996-05
作者:
谢俊松倪飞舟陈浩强
安徽医科大学计算机系, 安徽 合肥 230032
Author(s):
XIE Junsong NI Feizhou CHEN Haoqiang
Department of Computer Science, Anhui Medical University, Hefei 230032, China
关键词:
运动情景运动强度G-sensor心电异常Android心电监护
Keywords:
Keywords: motion states exercise intensity G-sensor abnormal electrocardiogram Android electrocardiogram monitoring
分类号:
R318;TP311.5
DOI:
DOI:10.3969/j.issn.1005-202X.2021.08.015
文献标志码:
A
摘要:
基于移动设备的心电监护设备越来越多,但大多数仅显示心电图,没有考虑到对应的用户运动情景。使用Android手机内置的G-sensor采集三轴加速度,设计一种有运动情景的动态心电监护系统。充分利用目前Android手机提供的功能,降低医疗成本,是面向家庭和社区医院的新型医疗系统,用户家属和医务人员可以通过客户端对用户进行实时监护,随时掌握其心电和运动状态信息,有利于医生做出准确的诊断,实现远程的、有运动情景的动态心电监护。
Abstract:
Abstract: There are more and more electrocardiogram (ECG) monitors based on mobile devices, but most of them can only display ECG, without taking the users motion states into account. Using the built-in G-sensor of Android mobile phone to collect 3-axis acceleration, a dynamic ECG monitoring system with the recognition of motion states is designed and implemented in the study. The system which makes full use of the functions provided by Android mobile phone and reduces the medical cost is a novel medical system for families and community hospitals. Through client terminal, users family members and medical personnel can monitor the user in real time and master their ECG and motion state information at any time, which helps the doctors to make an accuracy diagnosis. A remote dynamic ECG monitoring system with the recognition of motion states is realized in the study.

备注/Memo

备注/Memo:
【收稿日期】2021-01-26 【基金项目】安徽医科大学校基金资助项目(2019xkj027) 【作者简介】谢俊松,硕士研究生,助理实验师,研究方向:移动医疗,人工智能,E-mail: 513448336@qq.com
更新日期/Last Update: 2021-07-31