WO2017148450A1 - 一种基于单层形态学滤除基线漂移的方法和系统 - Google Patents

一种基于单层形态学滤除基线漂移的方法和系统 Download PDF

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WO2017148450A1
WO2017148450A1 PCT/CN2017/079423 CN2017079423W WO2017148450A1 WO 2017148450 A1 WO2017148450 A1 WO 2017148450A1 CN 2017079423 W CN2017079423 W CN 2017079423W WO 2017148450 A1 WO2017148450 A1 WO 2017148450A1
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signal
qrs
structural element
baseline drift
filtering
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French (fr)
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郑慧敏
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深圳竹信科技有限公司
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7225—Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
    • G06F2218/02—Preprocessing
    • G06F2218/04—Denoising

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  • the present invention relates to the field of signal processing, and more particularly to a method and system for filtering baseline drift based on single layer morphology.
  • the ECG signals collected by biosensors contain a variety of noises, including myoelectric interference, baseline drift, and power frequency interference. These noises will accurately extract features based on sampled signals. It has a great influence, in which the baseline drift is caused by low-frequency interference such as the breathing of the measured object and the movement of the electrode. In the actual measurement, the ECG signal will deviate from the normal baseline position due to the existence of the baseline drift, and the upper and lower fluctuations will occur. The changing phenomenon causes serious interference to the detection of the low-frequency useful component in the ECG signal, the QRS complex signal, which needs to be filtered out.
  • the object of the present invention is to propose a method and system for filtering baseline drift based on single layer morphology, which has small calculation amount and good filtering effect.
  • the present invention provides a method for filtering baseline drift based on single layer morphology, comprising:
  • the QRS signal is obtained by subtracting the noise signal X3 from the original signal X1.
  • the original signal is an electrocardiographic signal that filters out myoelectric interference.
  • the structural element is: a triangular structural element k.
  • the triangular structure element k [0, 2/3, 4/3, 2, 4/3, 2/3, 0].
  • the present invention provides a system for filtering baseline drift based on single layer morphology, comprising:
  • An acquiring unit configured to obtain an original signal X1;
  • the operation unit is configured to perform the opening operation of the original signal to the signal X2 by using a structural element
  • a closed operation unit for performing a closed operation on the signal X2 to obtain a noise signal X3 that filters out the QRS signal;
  • a calculating unit configured to obtain the QRS signal by subtracting the noise signal X3 from the original signal X1.
  • the triangular structure element k [0, 2/3, 4/3, 2, 4/3, 2/3, 0].
  • the invention provides a wearable device for monitoring physiological parameters of a human body, comprising the system according to any one of claims 5 to 7.
  • the invention provides a medical device for monitoring physiological parameters of a human body, comprising the system according to any one of claims 5 to 7.
  • the present invention relates to a method and system for filtering baseline drift based on single layer morphology, comprising: acquiring an original signal X1, and using the structural element to open the original signal to a signal X2, the signal X2 performs a closed operation to obtain a noise signal X3 from which the QRS signal is filtered, and subtracts the noise signal X3 from the original signal X1 to obtain the QRS signal; the scheme uses a structural element to filter out the ECG signal through a single layer morphological filtering algorithm. Baseline drift, small amount of calculation, good filter effect.
  • FIG. 1 is a flow chart of a method of a first embodiment of a method for filtering baseline drift based on single layer morphology provided by an embodiment of the present invention.
  • FIG. 2 is a flow chart of a method for filtering a baseline drift based on single layer morphology according to a second embodiment of the present invention.
  • FIG. 3 is a block diagram showing the structure of a system based on single layer morphology filtering baseline drift provided by an embodiment of the present invention.
  • FIG. 4 is a comparison diagram of filtering effects obtained by a method for filtering baseline drift based on single layer morphology provided by a specific embodiment of the present invention.
  • FIG. 5 is a comparison diagram of filtering effects obtained by using a two-layer element to filter baseline drift based on two-layer morphology provided by a specific embodiment of the present invention.
  • FIG. 1 is a flowchart of a method for filtering a baseline drift based on a single layer morphology according to a specific embodiment of the present invention.
  • the method comprises:
  • an original signal which may be a non-stationary random signal of a signal with baseline interference.
  • the original signal is an electrocardiogram signal including baseline drift and a QRS signal that filters out electromyography, in the ECG signal, QRS signal is the most important characteristic waveform, QRS signal
  • the waveform features are relatively constant and are shaped like a triangle.
  • the morphological filtering algorithm is used to filter out the baseline interference.
  • the original structural signal needs to be selected by selecting appropriate structural elements.
  • the structural elements should be selected to match the geometry of the filtered signal.
  • the common structural elements are disc, square and diamond. Etc. For more complex signals, these simple geometric shapes can also be combined to select multiple structural elements for processing.
  • the shape is similar to a triangle.
  • the scheme adopts a triangular structure element, and the QRS signal is regarded as a noise signal, and a structural element consistent with the shape characteristic of the signal is selected.
  • Morphological processing of the ECG signal can filter out the QRS signal, and then subtract the intermediate signal of the QRS signal from the original ECG signal to obtain the QRS signal component, which provides accurate analysis for subsequent signal analysis and health diagnosis. in accordance with.
  • the original ECG signal is opened by using the above-mentioned triangular structure element, that is, the ECG signal is first etched and then expanded, the frequency is higher than the isolated point of the ECG signal, and the positive pulse of the ECG signal is suppressed; the intermediate signal X2 is performed. Closed operation, that is, the ECG signal is first expanded and then eroded, and the elimination point is lower than the isolated point of the ECG signal, and the negative pulse of the ECG signal is suppressed.
  • the ECG signal After the original ECG signal is subjected to an open operation and a closed operation, that is, after a layer of morphological filtering, since the shape feature of the selected structural element matches the shape characteristic of the QRS signal, the ECG signal can be effectively filtered out. QRS signal.
  • the useful QRS signal is obtained by subtracting the intermediate signal X3 from the original ECG signal X1.
  • a method for filtering baseline drift based on single layer morphology includes: obtaining an original signal X1, performing an opening operation on the original signal to a signal X2 by using a structural element, and performing a closed operation on the signal X2.
  • the QRS signal is obtained by subtracting the noise signal X3 from the original signal X1; the scheme uses a structural element to filter the baseline drift noise in the ECG signal by a single layer morphological filtering algorithm, and the calculation amount Small, the filter works well.
  • FIG. 2 is a flowchart of a method for filtering a baseline drift based on a single layer morphology according to a second embodiment of the present invention.
  • the method comprises:
  • the triangular structure element is selected to process the ECG signal.
  • the single layer morphological filtering algorithm is adopted in this scheme, and the QRS signal needs to be filtered out at one time.
  • the selection of the structural element size directly affects the filtering quality, and needs to be correctly selected.
  • the width and height of the triangular structure element, wherein the width is the most important parameter of the filter design size, determined by the width of the filtered signal, that is, determined by the width of the QRS signal, and the width of the filter should be slightly larger than the QRS signal.
  • this embodiment is a system for filtering baseline drift based on single layer morphology, according to QRS.
  • the shape characteristics of the signal and the baseline drift signal are selected by a triangular structure element with reasonable size to perform a morphological filtering on the ECG signal, which can effectively filter out the baseline drift noise in the ECG signal, and the calculation amount is small.
  • FIG. 3 is a structural block diagram of a system for filtering baseline drift based on single layer morphology according to an embodiment of the present invention.
  • the system comprises:
  • the obtaining unit 01 is configured to acquire the original signal X1;
  • the original signal is an ECG signal containing baseline shift and QRS signals that are filtered out of myoelectric interference.
  • the operation unit 02 is configured to perform the opening operation of the original signal to the signal X2 by using a structural element
  • the closing operation unit 03 is configured to perform a closed operation on the signal X2 to obtain a noise signal X3 that filters out the QRS signal;
  • the calculating unit 04 is configured to obtain the QRS signal by subtracting the noise signal X3 from the electrocardiographic signal X1.
  • the scheme uses a structural element to filter the original ECG signal, which is smaller than the scheme using two structural elements. At the same time, the intermediate result obtained by the two layers of filtering is subtracted in the double-layer morphological filtering.
  • the target signal, this processing method is easy to bring the top distortion of the waveform, and in this scheme, a single layer morphological filtering is used, and the intermediate signal is subtracted from the original signal to avoid the phenomenon of top distortion.
  • a structural element setting unit 05 is provided for setting the structural element.
  • the system can be applied to wearable devices that monitor human health and can also be used in medical applications. In the treatment equipment.
  • FIG. 4 is a comparison diagram of filtering effects obtained by filtering a baseline drift based on a single layer morphology according to an embodiment of the present invention
  • FIG. 5 is a double layer based manner according to an embodiment of the present invention. A comparison of the filtering effects obtained by filtering the baseline drift using two structural elements.
  • the initial signal is the ECG signal that filters out EMG
  • the denoised signal is the initial signal that filters out the baseline drift.
  • the data in Figure 5 is the ECG signal that filters out EMG, and the filtered data is the baseline drift. Data signal.
  • both methods can filter the baseline drift noise to obtain a useful QRS signal, but the QRS signal obtained by the two-layer morphological filtering algorithm of two structural elements exhibits top distortion. Obvious phenomenon, the filtering method of this method is better.
  • a system for filtering baseline drift based on single layer morphology is selected.
  • a triangular structure element with a reasonable size is selected to perform a morphological filtering on the ECG signal. Effectively filtering out the baseline drift noise, compared with the two-layer morphological filtering algorithm that selects two structural elements, the calculation amount is small, and the phenomenon of top distortion is avoided.

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Abstract

一种基于单层形态学滤除基线漂移的方法和系统，包括：获取原始信号X1（S101），采用结构元素对所述原始信号进行开运算到信号X2（S102），对信号X2进行闭运算得到滤除了QRS信号的噪声信号X3（S103），用所述原始信号X1减去噪声信号X3得到所述QRS信号（S104）；本方法采用结构元素通过单层形态学滤波算法滤除心电信号中的基线漂移，计算量小，滤波器效果好。

Description

一种基于单层形态学滤除基线漂移的方法和系统 技术领域
本发明涉及信号处理领域，尤其涉及一种基于单层形态学滤除基线漂移的方法和系统。
背景技术
在医学检测领域，通过生物传感器采集来的心电信号中包含各种各样的噪声，主要有肌电干扰、基线漂移和工频干扰等，这些噪声会对基于采样信号的特征提取的准确度造成很大的影响，其中基线漂移是有被测对象的呼吸和电极移动等低频干扰所引起的，在实际测量中，由于基线漂移的存在心电信号会偏离正常的基线位置，出现上下缓慢波动变化的现象，对心电信号中的低频有用成分——QRS波群信号的检测造成严重干扰，需要将其滤除。
传统的基线漂移去除方法主要有自适应滤波法、卡尔曼滤波法和小波变换法等。上述的方法均存在运算量较大、去除效果不佳、不能有效提高心电信号检测正确率等缺陷。
发明内容
本发明的目的在于提出一种基于单层形态学滤除基线漂移的方法和系统，计算量小，滤波效果好。
为达此目的，本发明采用以下技术方案：
第一方面，本发明提出一种基于单层形态学滤除基线漂移的方法，包括：
获取原始信号X1；
采用结构元素对所述原始信号进行开运算到信号X2；
对信号X2进行闭运算得到滤除了QRS信号的噪声信号X3；
用所述原始信号X1减去噪声信号X3得到所述QRS信号。
其中，所述原始信号为滤除了肌电干扰的心电信号。
其中，所述结构元素为：三角结构元素k。
其中，所述三角结构元素k＝[0，2/3，4/3，2，4/3，2/3，0]。
第二方面，本发明提出一种基于单层形态学滤除基线漂移的系统，包括：
获取单元，用于获取原始信号X1；
开运算单元，用于采用结构元素对所述原始信号进行开运算到信号X2；
闭运算单元，用于对信号X2进行闭运算得到滤除了QRS信号的噪声信号X3；
计算单元，用于用所述原始信号X1减去噪声信号X3得到所述QRS信号。
其中，还包括：
结构元素设置单元，用于设置所述结构元素，所述结构元素为：三角结构元素k。
其中，所述三角结构元素k＝[0，2/3，4/3，2，4/3，2/3，0]。
第三方面，本发明提出一种监测人体生理参数的可穿戴式设备，包括根据权利要求5至7任意一项所述的系统。
第四方面，本发明提出一种监测人体生理参数的医疗设备，包括根据权利要求5至7任意一项所述的系统。
本发明给出的技术方案带来的有益效果为：
本发明一种基于单层形态学滤除基线漂移的方法和系统，包括：获取原始信号X1，采用结构元素对所述原始信号进行开运算到信号X2，对信号 X2进行闭运算得到滤除了QRS信号的噪声信号X3，用所述原始信号X1减去噪声信号X3得到所述QRS信号；本方案采用结构元素通过单层形态学滤波算法滤除心电信号中的基线漂移，计算量小，滤波器效果好。
附图说明
图1是本发明具体实施方式提供的基于单层形态学滤除基线漂移的方法第一个实施例的方法流程图。
图2是本发明具体实施方式提供的基于单层形态学滤除基线漂移的方法第二个实施例的方法流程图。
图3是本发明具体实施方式提供的基于单层形态学滤除基线漂移的系统的结构方框程图。
图4是本发明具体实施方式提供的采用基于单层形态学滤除基线漂移的方法得到的滤波效果对比图。
图5是本发明具体实施方式提供的基于双层形态学采用两个结构元素滤除基线漂移的方法得到的滤波效果对比图。
具体实施方式
下面结合附图并通过附图进一步说明本发明的技术方案。
参见图1，图1是本发明具体实施方式提供的基于单层形态学滤除基线漂移的方法第一个实施例的方法流程图。
在第一实施例中，该方法包括：
S101，获取原始信号X1；
获取原始信号，该原始信号可以为存在基线干扰的信号的非平稳的随机信号，优选的，该原始信号为滤除了肌电干扰的包含基线漂移和QRS信号的心电信号，在心电信号中，QRS信号是最主要的特征波形，QRS信号的 波形特征较恒定，其形状类似三角形。
S102，采用结构元素对所述原始信号进行开运算到信号X2；
本方案采用形态学滤波算法滤除基线干扰，需选取合适的结构元素对原始信号进行处理，选择结构元素应尽量匹配被滤除信号的几何形状，常见的结构元素有圆盘形、正方形和菱形等，对于较为复杂的信号，也可通过这些简单几何形状进行组合，选取多个结构元素对其进行处理。
由于心电信号中有用信号QRS信号的波形特征比较固定，其形状类似三角形，优选的，本方案采用三角形结构元素，将该QRS信号当作噪声信号，选择与该信号的形状特征一致的结构元素对心电信号进行形态学处理，可以滤除QRS信号，然后用原始的心电信号减去滤除了QRS信号的中间信号，即可以得到QRS信号成分，为后续的信号分析，健康诊断提供准确的依据。
S103，对信号X2进行闭运算得到滤除了QRS信号的噪声信号X3；
用上述三角结构元素对原始的心电信号进行开运算，即对心电信号先腐蚀后膨胀，消除频率高于该心电信号的孤立点，抑制心电信号的正脉冲；对中间信号X2进行闭运算，即对心电信号先膨胀后腐蚀，消除频率低于该心电信号的孤立点，抑制心电信号的负脉冲。
对原始的心电信号先后经过一次开运算和一次闭运算，即进行一层形态滤波之后，由于选取的结构元素的形状特征与QRS信号的形状特征相匹配，可以有效的滤除心电信号中的QRS信号。
S104，用所述心电信号X1减去噪声信号X3得到所述QRS信号。
由于中间信号X3为滤除了QRS信号的心电信号，用原始的心电信号X1减去该中间信号X3就得到了有用的QRS信号。
综上，本实施例一种基于单层形态学滤除基线漂移的方法，包括：获取原始信号X1，采用结构元素对所述原始信号进行开运算到信号X2，对信号X2进行闭运算得到滤除了QRS信号的噪声信号X3，用所述原始信号X1减去噪声信号X3得到所述QRS信号；本方案采用结构元素通过单层形态学滤波算法滤除心电信号中的基线漂移噪声，计算量小，滤波器效果好。
实施例二
参见图2，图2是本发明具体实施方式提供的基于单层形态学滤除基线漂移的方法第二个实施例的方法流程图。
在第二实施例中，该方法包括：
S201，获取原始的心电信号X1；
S202，采用三角结构元素对所述原始信号进行开运算到信号X2；
S203，对信号X2进行闭运算得到滤除了QRS信号的噪声信号X3；
根据QRS信号的特征选择三角结构元素对上述心电信号进行处理，本方案采用单层形态学滤波算法，需要一次性将QRS信号滤除，结构元素尺寸的选取直接影响到滤波质量，需要正确选取该三角结构元素的宽度和高度，其中，宽度是滤波器设计尺寸最主要的参数，由被滤除信号的宽度所决定，即由QRS信号的宽度决定，滤波器的宽度应略大于QRS信号的宽度，若滤波器的宽度小于QRS信号的宽度，QRS信号无法滤除；若滤波器的宽度远大于QRS信号的尺寸，得到的目标信号会存在很大的误差，最终确定该三角结构元素的宽度为7，高度为2，该三角结构元素为：k＝[0，2/3，4/3，2，4/3，2/3，0]。
S204，用所述心电信号X1减去噪声信号X3得到所述QRS信号；
综上，本实施例一种基于单层形态学滤除基线漂移的系统，根据QRS 信号和基线漂移信号的形状特性，选取尺寸合理的三角形结构元素对心电信号进行一层形态学滤波，可以有效的滤除心电信号中的基线漂移噪声，计算量小。
参见图3，图3是本发明具体实施方式提供的基于单层形态学滤除基线漂移的系统的结构方框图。
在第三实施例中，该系统包括：
获取单元01，用于获取原始信号X1；
该原始信号为滤除了肌电干扰的包含基线漂移和QRS信号的心电信号。
开运算单元02，用于采用结构元素对所述原始信号进行开运算到信号X2；
闭运算单元03，用于对信号X2进行闭运算得到滤除了QRS信号的噪声信号X3；
计算单元04，用于用所述心电信号X1减去噪声信号X3得到所述QRS信号。
本方案采用一个结构元素对原始的心电信号进行滤波处理，相对于使用两个结构元素的方案计算量更小；同时，在双层形态学滤波中将两层滤波得到的中间结果相减得到目标信号，这种处理方法很容易带来波形的顶部失真，而在本方案采用单层形态学滤波，用原始信号减去中间拟合结果，把顶部失真的现象规避掉了。
结构元素设置单元05，用于设置所述结构元素。
根据QRS信号的形状特征选取三角结构元素，该三角结构元素为：k＝[0，2/3，4/3，2，4/3，2/3，0]。
该系统可以应用于监测人体健康的穿戴式设备中，同时也可以应用于医 疗设备中。
参见图4和图5，图4是本发明具体实施方式提供的采用基于单层形态学滤除基线漂移的方法得到的滤波效果对比图，图5是本发明具体实施方式提供的基于双层形态学采用两个结构元素滤除基线漂移的方法得到的滤波效果对比图。
图4中initial signal为滤除了肌电干扰的心电信号，denoised signal为滤除了基线漂移的initial signal；图5中data为滤除了肌电干扰的心电信号，filtered data为滤除了基线漂移的data信号。
由上述不同方法得到的滤波效果对比图可以看出，两个方法均可以滤除基线漂移噪声得到有用的QRS信号，但采用两个结构元素的双层形态滤波算法得到的QRS信号出现了顶部失真显现象，本方案的方法滤波效果更好。
综上，本实施例一种基于单层形态学滤除基线漂移的系统，根据QRS信号和基线漂移信号的形状特性，选取尺寸合理的三角形结构元素对心电信号进行一层形态学滤波，可以有效的滤除基线漂移噪声，相对于选取两个结构元素的双层形态学滤波算法，计算量小，且避免了顶部失真的现象。
以上结合具体实施例描述了本发明的技术原理。这些描述只是为了解释本发明的原理，而不能以任何方式解释为对本发明保护范围的限制。基于此处的解释，本领域的技术人员不需要付出创造性的劳动即可联想到本发明的其它具体实施方式，这些方式都将落入本发明的保护范围之内。

Claims (9)

  1. 一种基于单层形态学滤除基线漂移的方法，其特征在于，包括：
    获取原始信号X1；
    采用结构元素对所述原始信号进行开运算到信号X2；
    对信号X2进行闭运算得到滤除了QRS信号的噪声信号X3；
    用所述原始信号X1减去噪声信号X3得到所述QRS信号。
  2. 根据权利要求1所述的方法，其特征在于，所述原始信号为滤除了肌电干扰的心电信号。
  3. 根据权利要求1所述的方法，其特征在于，所述结构元素为：三角结构元素k。
  4. 根据权利要求3所述的方法，其特征在于，所述三角结构元素k＝[0，2/3，4/3，2，4/3，2/3，0]。
  5. 一种基于单层形态学滤除基线漂移的系统，其特征在于，包括：
    获取单元，用于获取原始信号X1；
    开运算单元，用于采用结构元素对所述原始信号进行开运算到信号X2；
    闭运算单元，用于对信号X2进行闭运算得到滤除了QRS信号的噪声信号X3；
    计算单元，用于用所述原始信号X1减去噪声信号X3得到所述QRS信号。
  6. 根据权利要求5所述的系统，其特征在于，还包括：
    结构元素设置单元，用于设置所述结构元素，所述结构元素为：三角结构元素k。
  7. 根据权利要求6所述的系统，其特征在于，所述三角结构元素k＝[0，2/3，4/3，2，4/3，2/3，0]。
  8. 一种监测人体生理参数的可穿戴式设备，其特征在于，包括根据权利要求5至7任意一项所述的系统。
  9. 一种监测人体生理参数的医疗设备，其特征在于，包括根据权利要求5至7任意一项所述的系统。
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