CN107174235A - 一种心脏起搏器病人心电图中qrs波的识别方法 - Google Patents

一种心脏起搏器病人心电图中qrs波的识别方法 Download PDF

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CN107174235A
CN107174235A CN201710455893.2A CN201710455893A CN107174235A CN 107174235 A CN107174235 A CN 107174235A CN 201710455893 A CN201710455893 A CN 201710455893A CN 107174235 A CN107174235 A CN 107174235A
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代贞勇
唐兴明
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Chongqing Kang Aftercrop Technology Development Ltd By Share Ltd
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    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/24Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316Modalities, i.e. specific diagnostic methods
    • A61B5/318Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • AHUMAN NECESSITIES
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    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/24Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316Modalities, i.e. specific diagnostic methods
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/24Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316Modalities, i.e. specific diagnostic methods
    • A61B5/318Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • A61B5/346Analysis of electrocardiograms
    • A61B5/349Detecting specific parameters of the electrocardiograph cycle
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235Details of waveform analysis
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7271Specific aspects of physiological measurement analysis
    • A61B5/7282Event detection, e.g. detecting unique waveforms indicative of a medical condition

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Abstract

本发明公开了一种心脏起搏器病人心电图中QRS波的识别方法,属于医疗诊断领域,通过发现每个波的斜率特征、最大幅值特征、出现的周期性特征及相邻波之间的联系,从中分析、识别QRS波的特征,以该特征去扑捉QRS波及出现的位置。本发明对于普通心电波、NON‑CAPTURE、AV SEQUENTIAL和ASYNC 75BPM类型的起搏心电波中能够正确识别QRS波及其位置。

Description

一种心脏起搏器病人心电图中QRS波的识别方法
技术领域
本发明属于一种心电图波形检测领域,特别涉及一种QRS波的识别方法。
背景技术
心脏病是一种常见的多发慢性疾病,由于其发病危险性高故而成为威胁人类生命的主要疾病。因此,心脏病的防治和诊断就成为当今医学界面临的主要问题。用于诊断心脏病的主要技术之一就是心电图-ECG,心电图是将心脏激动过程中所产生的体表电位差记录下来并加以解释的科学,由于心电图的方法简单,诊断可靠,对病人无损害的优点成为现在的主要诊断技术。而QRS波群检测是心电波形检测中的首要问题,可靠的QRS波群检测是诊断心律失常的最重要根据,而且只有在QRS波群确定后,才有可能进一步检测和分析心电的其它细节信息。QRS波群检测包括R波峰值点定位和QRS波群宽度检测两个方面,由于心电信号波形的复杂性和各种类型噪声的存在以及生理上的变异性,都使QRS波群的精确检测有很大困难。
现有技术中通常以安装起搏器的病人的心电图与未安装起搏器的病人的心电图相比,前者的心电图在QRS波前出现起搏信号,而起搏信号比QRS波的下降支斜率大,因而只要忽略起搏信号下降支斜率即可。下降支斜率slope_down_max只代表这一个下降支波形中某一段下降斜率,当在找slope_down_max1的位置时就会出现偏差。slope_down_max1有可能是slope_down_max所在下降支波形中的另一段下降斜率;也有可能是另一个下降支波形中某一段下降斜率,因此,其无法正确识别QRS波的位置。
在现有技术中,存在以下实际的技术问题:
(1)心电模拟仪MPS450模拟起搏器波类型为NON-CAPTURE的ECG信号,将该信号作为ECP设备中ECG输入信号,在ECP设备运行过程中,气囊无法正常冲排气。
(2)心电模拟仪MPS450模拟起搏器波类型为AV SEQUENTIAL的ECG信号,将该信号作为ECP设备中ECG输入信号,在ECP设备运行过程中,气囊无法正常冲排气。
(3)心电模拟仪MPS450模拟起搏器波类型为ASYNC 75BPM的ECG信号,将该信号作为ECP设备中ECG输入信号,在ECP设备运行过程中,气囊无法正常冲排气。
以上问题是由于起搏信号脉冲也称之为钉样标记被错误的识别为QRS波,而原有的QRS波被错误的识别为早搏。造成这种错误检测的原因是起搏信号脉冲的干扰。
发明内容
有鉴于现有技术的上述缺陷,本发明所要解决的技术问题是提供一种更加准确的QRS波识别方法。
为实现上述目的,本发明提供了一种心脏起搏器病人心电图中QRS波的识别方法,按以下步骤进行:
步骤一、获取波形中下降支斜率最大值slope_down_max和上升支斜率最大值slope_up_max;
步骤二、记录每个波的上升支斜率最大值slope_up_max、下降支斜率最大值slope_down_max、最大幅值amp、最大幅值的位置pos、该波出现的顺序号seq和该波出现的间隔时间interval;判断下降支斜率最大值的波,重复出现的依据是满足Ecg_Wave_RecordInfo[wavecounter].slope_down_max<((slope_down_max>>2)+(slope_down_max>>3))、Ecg_Wave_RecordInfo[wavecounter].slope_up_max≥
((slope_up_max>>2)+(slope_up_max>>3))且当前波峰到前一个下降支斜率最大值的波峰距离≥(ECG_SAMPLE_RATE*60/ECG_Max_Rate);
步骤三、记录一段时间待波形稳定后,对记录数据进行分析,最大斜率的波间隔时间内是否有波幅值比最大斜率波幅值大;若无,则认为该最大斜率的波为QRS波,以该波最大上升支斜率slope_up_max和下降支斜率slope_down_max搜索QRS波位置;若有,则认为该最大斜率的波为起搏信号,此最大幅值的波为QRS波,搜索该波出现的顺序号seq,按照该波出现的顺序号seq来搜索QRS波位置。
本发明的有益效果是:本发明对于普通心电波、NON-CAPTURE、AV SEQUENTIAL和ASYNC 75BPM类型的起搏心电波中能够正确识别QRS波及其位置。
具体实施方式
下面结合和实施例对本发明作进一步说明:
一种心脏起搏器病人心电图中QRS波的识别方法,按以下步骤进行:
步骤一、采样N秒钟,N>0,获取波形中下降支斜率最大值slope_down_max和上升支斜率最大值slope_up_max;
步骤二、0Ecg_Wave_RecordInfo数组记录每个波的上升支斜率最大值slope_up_max、下降支斜率最大值slope_down_max、最大幅值amp、最大幅值的位置pos、该波出现的顺序号seq和该波出现的间隔时间interval;判断下降支斜率最大值的波,重复出现的依据是满足Ecg_Wave_RecordInfo[wavecounter].slope_down_max<((slope_down_max>>2)+(slope_down_max>>3))、Ecg_Wave_RecordInfo[wavecounter].slope_up_max≥
((slope_up_max>>2)+(slope_up_max>>3))且当前波峰到前一个下降支斜率最大值的波峰距离≥(ECG_SAMPLE_RATE*60/ECG_Max_Rate);
步骤三、记录一段时间待波形稳定后,对记录数据进行分析,最大斜率的波间隔时间内是否有波幅值比最大斜率波幅值大;若无,则认为该最大斜率的波为QRS波,以该波最大上升支斜率slope_up_max和下降支斜率slope_down_max搜索QRS波位置;若有,则认为该最大斜率的波为起搏信号,此最大幅值的波为QRS波,搜索该波出现的顺序号seq,按照该波出现的顺序号seq来搜索QRS波位置。
以上详细描述了本发明的较佳具体实施例。应当理解,本领域的普通技术人员无需创造性劳动就可以根据本发明的构思作出诸多修改和变化。因此,凡本技术领域中技术人员依本发明的构思在现有技术的基础上通过逻辑分析、推理或者有限的实验可以得到的技术方案,皆应在由权利要求书所确定的保护范围内。

Claims (1)

1.一种心脏起搏器病人心电图中QRS波的识别方法,其特征在于按以下步骤进行:
步骤一、获取波形中下降支斜率最大值slope_down_max和上升支斜率最大值slope_up_max;
步骤二、记录每个波的上升支斜率最大值slope_up_max、下降支斜率最大值slope_down_max、最大幅值amp、最大幅值的位置pos、出现的顺序号seq和出现的间隔时间interval;判断下降支斜率最大值的波,判别依据是满足Ecg_Wave_RecordInfo[wavecounter].slope_down_max<((slope_down_max>>2)+(slope_down_max>>3))、Ecg_Wave_RecordInfo[wavecounter].slope_up_max≥((slope_up_max>>2)+(slope_up_max>>3))且当前波峰到前一个下降支斜率最大值的波峰距离≥(ECG_SAMPLE_RATE*60/ECG_Max_Rate);
步骤三、记录2个周期QRS波待波形稳定后,对记录数据进行分析,最大斜率的波间隔时间内是否有波幅值比最大斜率波幅值大;若无,以该波最大上升支斜率slope_up_max和下降支斜率slope_down_max搜索QRS波位置,QRS搜索采用差分法;若有,此最大幅值的波为QRS波,搜索该波出现的顺序号seq,按照该波出现的顺序号seq来搜索QRS波位置。
CN201710455893.2A 2017-06-16 2017-06-16 一种心脏起搏器病人心电图中qrs波的识别方法 Pending CN107174235A (zh)

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108324265A (zh) * 2018-02-26 2018-07-27 河南善仁医疗科技有限公司 基于心音特征定位分析心电图心音图的方法
CN108814591A (zh) * 2018-03-23 2018-11-16 南京大学 一种心电qrs波群宽度的检测方法及其心电分析方法
CN108814590A (zh) * 2018-03-23 2018-11-16 江苏华康信息技术有限公司 一种心电qrs波群的检测方法及其心电分析方法

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108324265A (zh) * 2018-02-26 2018-07-27 河南善仁医疗科技有限公司 基于心音特征定位分析心电图心音图的方法
CN108814591A (zh) * 2018-03-23 2018-11-16 南京大学 一种心电qrs波群宽度的检测方法及其心电分析方法
CN108814590A (zh) * 2018-03-23 2018-11-16 江苏华康信息技术有限公司 一种心电qrs波群的检测方法及其心电分析方法
CN108814591B (zh) * 2018-03-23 2020-12-15 南京大学 一种心电qrs波群宽度的检测方法及其心电分析方法
CN108814590B (zh) * 2018-03-23 2021-01-12 江苏华康信息技术有限公司 一种心电qrs波群的检测方法及其心电分析方法

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