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Automatic electrocardioelectrode placement error detection method based on kernel function classification algorithm

A classification algorithm and ECG electrode technology, applied in the field of information science and engineering, can solve the problems of inaccurate detection results, comparable 12-lead system, wrong placement of electrodes, etc., and achieve the effect of improving sensitivity and specificity

Active Publication Date: 2015-04-01
邱磊
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  • Description
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  • Application Information

AI Technical Summary

Problems solved by technology

The other 120-plus types of leads are still not comparable to the 12-lead system
However, since 12 leads need to place 10 electrodes on the human body surface, they are left hand (LA), right hand (RA), left foot (LF) and right foot (RF) and six chest leads (V 1 -V 6 ), in medical practice, it is easy for nurses to place electrodes in the wrong position, resulting in inaccurate test results

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  • Automatic electrocardioelectrode placement error detection method based on kernel function classification algorithm
  • Automatic electrocardioelectrode placement error detection method based on kernel function classification algorithm
  • Automatic electrocardioelectrode placement error detection method based on kernel function classification algorithm

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Embodiment Construction

[0033] The present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments.

[0034] Step 1: Define the conventional 12-lead ECG waveform feature vector x=[x 1 , x 2 ,...x 12 ] T , where each component (component) x 1 , x 2 ,...x 12 : The meaning of the representative is as follows:

[0035] (1) P wave electric axis, the unit is radian, if there is no P wave, it will be calculated as zero value, and the variable x 1 express;

[0036] (2) The effective amplitude of the P wave in lead II, where the net amplitude of the P and T waves is the absolute value of the maximum positive peak amplitude minus the maximum negative peak amplitude, and the unit is mV. If there is no P wave, take zero The value is computed, taking the variable x 2 express;

[0037] (3) The effective amplitude of P wave in lead V6, the unit is millivolts, if there is no P wave, it will be calculated as zero value, and the variable x 3 express;...

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Abstract

The invention discloses an automatic electrocardioelectrode placement error detection method based on a kernel function classification algorithm and aims at realizing the intelligent detection of wrong positions of hand and foot electrodes by use of a device without extra assistance. According to the automatic electrocardioelectrode placement error detection method based on the kernel function classification algorithm, reference signals are classified into seven classes, and any given electrocardiovector is identified and classified by use of a classifier method based on a kernel function. The automatic electrocardioelectrode placement error detection method based on the kernel function classification algorithm is capable of accurately discriminating abnormal waveforms caused by heart diseases and wrong positions and greatly increasing the accuracy of electrocardiogram interpretation.

Description

technical field [0001] The invention relates to a biological signal processing method, which belongs to the field of information science and engineering. Background technique [0002] Heart disease is one of the main diseases that kills human life. Sudden cardiac death caused by it can kill the patient in just a few minutes, leaving the patient's family members with endless pain. Today's society is fast-paced and under great pressure in all aspects. Sudden cardiac death shows a trend of multi-industry and younger people, which brings irreparable losses to the country and society. [0003] The human electrocardiogram, as a comprehensive representation of the electrical activity of the heart on the body surface, contains a wealth of physiological and pathological information reflecting the heart rhythm and its electrical conduction. It has been more than 100 years since William Einthoven, a physiologist at Leiden University in the Netherlands, used a galvanometer to trace the...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/0402
CPCA61B5/24A61B5/25
Inventor 邱磊
Owner 邱磊