CN116236208A - Multi-lead electrocardio electrode patch positioning method based on human body surface characteristics - Google Patents

Multi-lead electrocardio electrode patch positioning method based on human body surface characteristics Download PDF

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CN116236208A
CN116236208A CN202310182755.7A CN202310182755A CN116236208A CN 116236208 A CN116236208 A CN 116236208A CN 202310182755 A CN202310182755 A CN 202310182755A CN 116236208 A CN116236208 A CN 116236208A
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electrode patch
component
human
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ordinate
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赵俭辉
邓文军
袁志勇
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Wuhan University WHU
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Wuhan University WHU
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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]
    • A61B5/321—Accessories or supplementary instruments therefor, e.g. cord hangers
    • 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
    • A61B5/25—Bioelectric electrodes therefor
    • A61B5/251—Means for maintaining electrode contact with the body
    • A61B5/257—Means for maintaining electrode contact with the body using adhesive means, e.g. adhesive pads or tapes
    • 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
    • A61B5/25—Bioelectric electrodes therefor
    • A61B5/279—Bioelectric electrodes therefor specially adapted for particular uses
    • A61B5/28—Bioelectric electrodes therefor specially adapted for particular uses for electrocardiography [ECG]
    • A61B5/282—Holders for multiple electrodes
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/684—Indicating the position of the sensor on the body
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/74—Details of notification to user or communication with user or patient ; user input means
    • A61B5/7405—Details of notification to user or communication with user or patient ; user input means using sound
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/74—Details of notification to user or communication with user or patient ; user input means
    • A61B5/742—Details of notification to user or communication with user or patient ; user input means using visual displays
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/20—Image preprocessing
    • G06V10/24—Aligning, centring, orientation detection or correction of the image
    • G06V10/245—Aligning, centring, orientation detection or correction of the image by locating a pattern; Special marks for positioning
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/764—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
    • G06V10/765—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects using rules for classification or partitioning the feature space
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/40—Scenes; Scene-specific elements in video content
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

The invention provides a multi-lead electrocardio electrode patch positioning method based on human body surface characteristics, which belongs to the technical field of medical equipment and comprises the following steps: inputting video data of the electrocardio electrode patch worn by a user into a pre-trained target positioning model to obtain the body surface characteristics of the upper body of a human body and electrocardio electrode patch characteristic state information; and calculating and obtaining characteristic operation association results of the body surface characteristics of the upper body of the human body and the electrocardio electrode patch characteristic state information, generating electrocardio electrode patch wearing state information, and determining an electrocardio electrode patch positioning guidance result according to the electrocardio electrode patch wearing state information. According to the invention, the terminal with the video function is used for collecting the body surface characteristics and the electrode patch position information of the user when wearing the electrocardio electrode patch in real time, feeding back information such as whether the user wears the electrocardio electrode patch correctly or not or an error correction method and the like to the user, assisting the user to wear the electrocardio electrode patch correctly, and effectively reducing or avoiding errors of electrocardio signal measurement caused by the fact that the user wears the electrocardio electrode patch by mistake.

Description

Multi-lead electrocardio electrode patch positioning method based on human body surface characteristics
Technical Field
The invention relates to the technical field of medical equipment, in particular to a multi-lead electrocardio electrode patch positioning method based on human body surface characteristics.
Background
In cardiovascular disease diagnosis, an electrocardiogram is one of important indexes, and is usually obtained by wearing a special electrocardiogram detection instrument on a patient, and most commonly, a multi-lead electrocardio electrode patch is worn to obtain an electrocardiogram of the patient, so that whether a person to be examined suffers from heart diseases or not is known through observation of the electrocardiogram.
With the increasing popularity of services such as remote inquiry and home health monitoring, more and more users acquire their own electrocardiographic data at any time in a home self-test mode, and most of users are not trained in wearing special electrode patches, so that great errors of the acquired electrocardiograph are possibly caused by inaccurate wearing of the electrode patches to a great extent, and the accuracy of analysis and cardiac diagnosis of electrocardiograph signals by doctors or instruments is affected.
Accordingly, there is a need to provide an effective way to assist the user in locating the ecg electrode patches and to assist the user in wearing the ecg electrode patches correctly.
Disclosure of Invention
The invention provides a multi-lead electrocardio electrode patch positioning method based on human body surface characteristics, which is used for solving the defect that a method for guiding a user to wear an electrocardio electrode patch correctly is lacking in the prior art.
The invention provides a multi-lead electrocardio electrode patch positioning method based on human body surface characteristics, which comprises the following steps:
acquiring video data of an electrocardio electrode patch worn by a user, and inputting the video data of the electrocardio electrode patch worn by the user into a pre-trained target positioning model to obtain body surface characteristics of the upper body of a human body and electrocardio electrode patch characteristic state information;
calculating and obtaining characteristic operation association results of the body surface characteristics of the upper body of the human body and the electrocardio electrode patch characteristic state information;
and generating electrocardio electrode patch wearing state information according to the characteristic operation association result, and determining an electrocardio electrode patch positioning guidance result according to the electrocardio electrode patch wearing state information.
According to the multi-lead electrocardio electrode patch positioning method based on human body surface characteristics, which is provided by the invention, the video data of the electrocardio electrode patch worn by a user is collected, the video data of the electrocardio electrode patch worn by the user is input into a pre-trained target positioning model, and the human body upper body surface characteristics and electrocardio electrode patch characteristic state information are obtained, and the method comprises the following steps:
Initializing an N-dimensional vector comprising a plurality of characteristic state information, wherein N is the total number of the body surface characteristics of the upper body of the human body plus the electrocardio electrode patches, and the plurality of characteristic state information comprises a target type, a target score value, a target center point abscissa, a target center point ordinate, a target detection frame height and a target detection frame width;
if the target type is determined to be a human nipple, performing non-ascending sorting on components corresponding to the human nipple in the plurality of characteristic state information, and taking the first two components as human nipple detection results;
if the target type is determined to be the boundary line of the upper body of the human body, non-ascending order is carried out on the components corresponding to the boundary line of the upper body of the human body in the plurality of characteristic state information, and then the first two components are taken as human body boundary detection results;
if the target type is determined to be an electrode patch, performing non-ascending order on components corresponding to the electrode patch in the plurality of characteristic state information, and taking a plurality of components as electrode patch detection results;
and constructing a two-dimensional matrix according to the human nipple detection result, the human demarcation line detection result and the electrode patch detection result, wherein the two-dimensional matrix comprises a human right nipple component, a human left nipple component, a human right borderline component, a human left borderline component, a right upper limb electrode patch component, a left upper limb electrode patch component, a first chest electrode patch component, a second chest electrode patch component, a third chest electrode patch component, a fourth chest electrode patch component, a fifth chest electrode patch component, a sixth chest electrode patch component, a right lower limb electrode patch component and a left lower limb electrode patch component.
According to the multi-lead electrocardio electrode patch positioning method based on the human body surface characteristics, the characteristic operation association result of the human body upper body surface characteristics and the electrocardio electrode patch characteristic state information is obtained through calculation, and the method comprises the following steps:
if it is determined that the abscissa of the first chest electrode patch component, the second chest electrode patch component, the third chest electrode patch component, the fourth chest electrode patch component, the fifth chest electrode patch component, and the sixth chest electrode patch component are sequentially incremented, a subsequent calculation step is performed, and otherwise, a first feature operation association result is returned.
According to the multi-lead electrocardio electrode patch positioning method based on the human body surface characteristics, the characteristic operation association result of the human body upper body surface characteristics and the electrocardio electrode patch characteristic state information is obtained through calculation, and the method further comprises the following steps:
obtaining a first ratio of the absolute value of the first chest electrode patch component ordinate minus the second chest electrode patch component ordinate to the absolute value of the first chest electrode patch component abscissa minus the second chest electrode patch component abscissa, and a second ratio of the absolute value of the human body right nipple component ordinate minus the human body left nipple component ordinate to the absolute value of the human body right nipple component abscissa minus the human body left nipple component abscissa;
If the absolute value of the difference between the first ratio and the second ratio is smaller than or equal to a first preset error value, executing a subsequent calculation step, otherwise, returning a second characteristic operation association result;
obtaining a first product obtained by subtracting the human left nipple component abscissa from the first chest electrode patch component abscissa and subtracting the human right nipple component ordinate from the human left nipple component ordinate, and a second product obtained by subtracting the human right nipple component abscissa from the human left nipple component abscissa from the first chest electrode patch component ordinate and subtracting the human left nipple component ordinate from the human left nipple component ordinate;
if the difference between the first product and the second product is smaller than or equal to the first preset error value, executing the subsequent calculation step, otherwise, returning a third characteristic operation association result;
if the Euclidean distance between the first chest electrode patch component and the human right nipple component is less than or equal to the second preset error value, and the Euclidean distance between the second chest electrode patch component and the human left nipple component is less than or equal to the second preset error value, executing the subsequent calculation step, otherwise, returning to the fourth characteristic operation association result.
According to the multi-lead electrocardio electrode patch positioning method based on the human body surface characteristics, the characteristic operation association result of the human body upper body surface characteristics and the electrocardio electrode patch characteristic state information is obtained through calculation, and the method further comprises the following steps:
obtaining a third product obtained by multiplying the difference of the fourth chest electrode patch component abscissa minus the human left nipple component abscissa by the difference of the human left nipple component abscissa minus the human right nipple component abscissa, and a fourth product obtained by multiplying the difference of the fourth chest electrode patch component ordinate minus the human left nipple component ordinate by the difference of the human left nipple component ordinate minus the human right nipple component ordinate;
if the difference between the third product and the fourth product is smaller than or equal to a first preset error value, executing a subsequent calculation step, otherwise, returning a fifth characteristic operation association result;
if the Euclidean distance between the patch component of the fourth chest electrode and the left nipple component of the human body is less than or equal to the second preset error value, executing the subsequent calculation step, otherwise, returning to the sixth characteristic operation association result.
According to the multi-lead electrocardio electrode patch positioning method based on the human body surface characteristics, the characteristic operation association result of the human body upper body surface characteristics and the electrocardio electrode patch characteristic state information is obtained through calculation, and the method further comprises the following steps:
Acquiring a first linear distance from a third front electrode patch center point to a connecting line of a second front electrode patch center point and a fourth front electrode patch center point, a second linear distance from the third front electrode patch center point to the second front electrode patch center point, and a third linear distance from the third front electrode patch center point to the fourth front electrode patch center point;
if the difference between the first linear distance and the second preset error value is less than or equal to 0, executing the subsequent calculation step, otherwise, returning to a seventh characteristic operation association result;
and if the absolute value of the difference between the second linear distance and the third linear distance is smaller than or equal to the second preset error value, executing the subsequent calculation step, otherwise, returning to the eighth characteristic operation association result.
According to the multi-lead electrocardio electrode patch positioning method based on the human body surface characteristics, the characteristic operation association result of the human body upper body surface characteristics and the electrocardio electrode patch characteristic state information is obtained through calculation, and the method further comprises the following steps:
obtaining a fifth product obtained by subtracting the human left boundary component abscissa from the sixth chest electrode patch component abscissa, multiplying the difference of the human left nipple component abscissa and the human right nipple component abscissa from the sixth chest electrode patch component ordinate and multiplying the difference of the human left boundary component ordinate from the sixth chest electrode patch component ordinate and the human right nipple component ordinate from the human left nipple component ordinate;
If the difference between the fifth product and the sixth product is smaller than or equal to a first preset error value, executing a subsequent calculation step, otherwise, returning a ninth characteristic operation association result;
obtaining a seventh product obtained by subtracting the fourth chest electrode patch component abscissa from the sixth chest electrode patch component abscissa and subtracting the human right nipple component ordinate from the human left nipple component ordinate, and an eighth product obtained by subtracting the human right nipple component abscissa from the human left nipple component abscissa from the sixth chest electrode patch component ordinate and subtracting the fourth chest electrode patch component ordinate from the sixth chest electrode patch component ordinate;
and if the difference between the seventh product and the eighth product is less than or equal to the first preset error value, executing the subsequent calculation step, otherwise, returning a tenth characteristic operation association result.
According to the multi-lead electrocardio electrode patch positioning method based on the human body surface characteristics, the characteristic operation association result of the human body upper body surface characteristics and the electrocardio electrode patch characteristic state information is obtained through calculation, and the method further comprises the following steps:
obtaining a ninth product obtained by subtracting the fourth chest electrode patch component abscissa from the fifth chest electrode patch component abscissa, multiplying the difference of the human left nipple component ordinate and the human right nipple component abscissa from the fifth chest electrode patch component ordinate and a tenth product obtained by subtracting the fourth chest electrode patch component ordinate from the fifth chest electrode patch component ordinate and multiplying the difference of the human left nipple component abscissa and the human right nipple component abscissa from the human left nipple component abscissa;
And if the difference between the ninth product and the tenth product is smaller than the first preset error value, executing the subsequent calculation step, otherwise, returning to the eleventh characteristic operation association result.
According to the multi-lead electrocardio electrode patch positioning method based on the human body surface characteristics, the second preset error value is obtained by multiplying the average frame length of the sum of the target frame lengths and the target frame widths of 10 electrode patches in the two-dimensional matrix by the preset proportion.
According to the multi-lead electrocardio electrode patch positioning method based on the human body surface characteristics, the electrocardio electrode patch wearing state information is generated according to the characteristic operation association result, and the electrocardio electrode patch positioning guidance result is determined according to the electrocardio electrode patch wearing state information, and the method comprises the following steps:
if the characteristic operation association result is determined to be wearing error information, feeding back a wearing error electrode patch number and an electrode patch adjusting method to a user by adopting voice or characters;
if the characteristic operation association result is determined to be the wearing correct information, the wearing success prompt information is fed back to the user by voice or characters.
According to the multi-lead electrocardio electrode patch positioning method based on the human body surface characteristics, the terminal with the video function is used for collecting the surface characteristics and the electrode patch position information of a user when wearing the electrocardio electrode patch in real time, feeding back information such as whether wearing is correct or not or an error correction method and the like to the user, assisting the user in wearing the electrocardio electrode patch correctly, and effectively reducing or avoiding errors of electrocardio signal measurement caused by the fact that the user wears the electrocardio electrode patch by mistake.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the invention, and other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a multi-lead electrocardio electrode patch positioning method based on the characteristics of the body surface;
FIG. 2 is a second flow chart of a multi-lead ECG electrode patch positioning method based on body surface features of a human body provided by the invention;
FIG. 3 is a schematic diagram of the results of the electrocardio electrode patch and the human body surface features provided by the invention;
FIG. 4 is a schematic diagram of the result of object numbering provided by the present invention;
fig. 5 is a schematic diagram of the result of electrode patch auxiliary wearing provided by the invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Along with the popularization of network remote inquiry and home health monitoring, the use demands of users on medical equipment are increasing, wherein in the aspect of monitoring vascular diseases, the users wear multi-lead electrocardio electrode patches to acquire electrocardio data, and electrocardio data are provided for specialized doctors to realize cardiovascular health monitoring and diagnosis.
Fig. 1 is a schematic flow chart of a multi-lead electrocardiograph electrode patch positioning method based on body surface features according to an embodiment of the present invention, as shown in fig. 1, including:
step 100: acquiring video data of an electrocardio electrode patch worn by a user, and inputting the video data of the electrocardio electrode patch worn by the user into a pre-trained target positioning model to obtain body surface characteristics of the upper body of a human body and electrocardio electrode patch characteristic state information;
Step 200: calculating and obtaining characteristic operation association results of the body surface characteristics of the upper body of the human body and the electrocardio electrode patch characteristic state information;
step 300: and generating electrocardio electrode patch wearing state information according to the characteristic operation association result, and determining an electrocardio electrode patch positioning guidance result according to the electrocardio electrode patch wearing state information.
The embodiment of the invention firstly collects video data of the electrocardio electrode patch worn by a user, utilizes a pre-trained automatic target positioning model to process images or video streams in the video data of the electrocardio electrode patch worn by the user, carries out detection positioning, outputs the characteristic state information of the body surface of the upper body and the electrocardio electrode patch of the human body by the target positioning model, then calculates the characteristic operation association result of the characteristic state information of the electrocardio electrode patch and the body surface of the upper body, judges whether the electrocardio electrode patch worn by the user is successfully worn according to the characteristic operation association result, informs the user of the successful wearing result in the form of voice or characters if the user is successful, and informs the user of how to adjust the electrocardio electrode patch which is worn incorrectly in the form of voice or characters.
Specifically, as shown in fig. 2, after the user wears the electrocardiograph electrode patch, based on target detection of video stream or image, training the input video stream or image by using a pre-trained target positioning model to obtain body surface feature reference points and the positions of the electrocardiograph electrode patch, judging the wearing result of the electrocardiograph electrode patch according to an auxiliary wearing algorithm, if the wearing is successful, directly informing the user of the wearing success result, if the wearing is wrong, feeding back error information to the user in real time through voice or characters, and guiding the user to adjust the positions of the electrocardiograph electrode patch.
According to the invention, the terminal with the video function is used for collecting the body surface characteristics and the electrode patch position information of the user when wearing the electrocardio electrode patch in real time, feeding back information such as whether the user wears the electrocardio electrode patch correctly or not or an error correction method and the like to the user, assisting the user to wear the electrocardio electrode patch correctly, and effectively reducing or avoiding errors of electrocardio signal measurement caused by the fact that the user wears the electrocardio electrode patch by mistake.
Based on the above embodiment, step 100 includes:
initializing an N-dimensional vector comprising a plurality of characteristic state information, wherein N is the total number of the body surface characteristics of the upper body of the human body plus the electrocardio electrode patches, and the plurality of characteristic state information comprises a target type, a target score value, a target center point abscissa, a target center point ordinate, a target detection frame height and a target detection frame width;
if the target type is determined to be a human nipple, performing non-ascending sorting on components corresponding to the human nipple in the plurality of characteristic state information, and taking the first two components as human nipple detection results;
if the target type is determined to be the boundary line of the upper body of the human body, non-ascending order is carried out on the components corresponding to the boundary line of the upper body of the human body in the plurality of characteristic state information, and then the first two components are taken as human body boundary detection results;
If the target type is determined to be an electrode patch, performing non-ascending order on components corresponding to the electrode patch in the plurality of characteristic state information, and taking a plurality of components as electrode patch detection results;
and constructing a two-dimensional matrix according to the human nipple detection result, the human demarcation line detection result and the electrode patch detection result, wherein the two-dimensional matrix comprises a human right nipple component, a human left nipple component, a human right borderline component, a human left borderline component, a right upper limb electrode patch component, a left upper limb electrode patch component, a first chest electrode patch component, a second chest electrode patch component, a third chest electrode patch component, a fourth chest electrode patch component, a fifth chest electrode patch component, a sixth chest electrode patch component, a right lower limb electrode patch component and a left lower limb electrode patch component.
According to the embodiment of the invention, a pre-trained automatic target positioning model is used for automatically positioning targets of an image or video stream input by equipment, and the human body surface characteristics and the characteristic state information of a plurality of electrode patches in the image or video stream are obtained.
Specifically, images of a plurality of bare human bodies and electrode patches worn on the upper half bodies of the human bodies are shot in various background environments, targets (human body papillae, left and right boundary lines of the upper half bodies of the human bodies and electrode patches) appearing in all the images are marked, a dataset of an automatic target positioning model is obtained, an automatic target positioning model for detecting the characteristics of the electrode patches and the body surfaces of the human bodies is constructed, and training is carried out by using the obtained dataset; during training, setting the number of target categories in the automatic target positioning model to be 3; the results of obtaining a trained automatic target positioning model, an electrocardio electrode patch and human body surface characteristics are shown in figure 3.
Initializing an N-dimensional vector object with a data type as feature state information, and storing all feature state information of the detected object in the N-dimensional vector object; the rank of the object vector is N, which is the number of electrode patches and the human body surface features detected by the automatic target positioning model in the image or video stream; the structure of the characteristic state information comprises a target type, a target score value, a target center point abscissa, a target center point ordinate, a target detection frame height and a target detection frame width of the target; any component of the N-dimensional vector can be divided into three target types, here, it is assumed that the target type 1 is a human nipple, the target type 2 is a boundary line of the upper body of the human body, and the target type 3 is an electrode patch; non-ascending sorting is carried out on components belonging to the same target type in the N-dimensional vector according to the target score values of the components:
(1) For the target type 1, taking the first two components of the N-dimensional vector sequence as the final detection result of the human nipple;
(2) For the target type 2, taking the first two components of the N-dimensional vector sequence as the final detection result of the human body boundary line;
(3) For target type 3, the first multiple components of the N-dimensional vector sequence are taken as the final electrode patch detection result, note that the number here should be uniform with the number of electrode patches worn.
And numbering each detected object according to the position relation of the components belonging to the same object type in the N-dimensional vector object, initializing a two-dimensional matrix, and storing the number of each object and the characteristic state information in each column of each row of the two-dimensional matrix correspondingly. The number of lines of the two-dimensional matrix is the number of targets, namely, the subscript number of each line corresponds to the number of the targets, and the number of columns of the two-dimensional matrix is the same as the characteristic state number of the targets, namely, each column corresponds to the type of the targets, the target score value, the x coordinate of the target center point, the y coordinate of the target center point, the height of the target detection frame and the length of the target detection frame from small to large.
Firstly numbering target elements of a human nipple, and comparing the sizes of target center point abscissa coordinates of the human nipple with component target types in N-dimensional vectors; the number of the component with smaller abscissa is marked as RN, namely right nipple and is stored in the two-dimensional matrix, and the number of the component with larger abscissa is marked as LN, namely left nipple and is stored in the two-dimensional matrix; then numbering the target elements of the human body boundary line, and comparing the sizes of the target central point abscissa coordinates of which the component target types in the N-dimensional vector are the human body boundary line; the number of the component with smaller abscissa is marked as RB, namely a right boundary line and is stored in a two-dimensional matrix, and the number of the component with larger abscissa is marked as LB, namely a left boundary line and is stored in the two-dimensional matrix; finally, the target elements of the electrode patches are numbered, wherein the number is related to the number of the electrode patches. The components are sorted in a non-descending order according to the abscissa of the target center point, the type of the component target of which is the boundary line of the human body, in the N-dimensional vector, and 12 leads are taken as an example here, and the components are sequentially "RA", "LA", "V1", "V2", "V3", "V4", "V5", "V6", "RL", "LL" according to the serial numbers of the sequential components, and are respectively stored in the two-dimensional matrix. The results of each target are shown in fig. 4.
The invention performs auxiliary inspection based on the body surface characteristics of the user as the reference point, so that the invention is applicable to various complex background environments, and has high auxiliary wearing accuracy and environment fault tolerance.
Based on the above embodiment, step 200 includes:
according to the body surface characteristics of the human body in the two-dimensional matrix and the position information of the electrode patches in the image or video stream, analyzing whether the relative position relation among the electrode patches and the position relation of the relative body surface characteristics accord with the medical electrode patch wearing specification or not, and returning a result response code result code, wherein the specific classification is shown in table 1:
TABLE 1
Figure BDA0004102770640000101
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Figure BDA0004102770640000111
The first case is to analyze and check whether the relative positions of the V1 to V6 electrode patches satisfy a relationship in which the abscissa sequentially increases; if the relation is satisfied, a result response code= "correct" is returned; otherwise, continuing to execute the subsequent steps; if not, a result response code= "error_1-6" is returned, and the judgment process of whether the relative position relationship between the V1 and V6 electrode patches meets the requirements is as follows:
Figure BDA0004102770640000112
wherein matrix [ n ] [2] represents the abscissa in the image or video stream of the center point of the electrode patch with the number Vn.
The second condition is to analyze and check whether the connecting line of the central points of the V1 and V2 electrode patches meets the position relation parallel to the connecting line of the RN and LN central points in the error range; if the relation is satisfied, executing the subsequent steps; otherwise, returning a result response code= "error_1-2_1";
the judging process of whether the connecting line of the central points of the V1 and V2 electrode patches and the connecting line of the central points of the RN and LN meet the requirements is as follows:
Figure BDA0004102770640000121
wherein matrix [ n ] [3] represents the ordinate of the center point of the electrode patch with the number Vn in the image or video stream. matrix [6] [3], matrix [7] [3], matrix [0] [3], matrix [1] [3] represent the vertical coordinates in the image or video of the electrode patch center points numbered V1 and V2 and the human nipple center points numbered RN and LN, respectively, matrix [6] [2], matrix [7] [2], matrix [0] [2], matrix [1] [2] represent the horizontal coordinates in the image or video of the electrode patch center points numbered V1 and V2 and the human nipple center points numbered RN and LN, respectively, and alpha is the maximum allowable error value, i.e., the first preset error value.
Further analyzing and checking whether the connecting line of the center points of the V1 and V2 electrode patches meets the position relation on the same straight line with the connecting line of the center points of the RN and the LN and whether the distances between the V1 and the RN and the distances between the V2 and the LN respectively meet the position relation within the error allowable range; if the relation is satisfied, executing the subsequent steps; otherwise, returning a result response code= "error_1-2_2";
The judging process of whether the connecting line of the central points of the V1 and V2 electrode patches meets the requirements with the connecting line of the central points of the RN and the LN is as follows:
(matrix[6][2]-matrix[1][2])×(matrix[1][3]-matrix[0][3])-(matrix[6][3]-matrix[1][3])×(matrix[1][2]-matrix[0][2])≤α；
the judging process of whether the straight line distance between the V1 and V2 electrode patches and RN and LN respectively meets the requirements is shown in the following Euclidean distance formula:
Figure BDA0004102770640000122
and
Figure BDA0004102770640000123
wherein matrix [6] [2], matrix [0] [2], matrix [7] [2], matrix [1] [2] represent the horizontal coordinates of the electrode patch center points numbered V1 and V2 and the human nipple center points numbered RN and LN in the image or video stream, respectively, matrix [6] [3], matrix [0] [3], matrix [7] [3], matrix [1] [3] represent the vertical coordinates of the electrode patch center points numbered V1 and V2 and the human nipple center points numbered RN and LN in the image or video stream, respectively, and beta is the maximum allowable error value, i.e., the second preset error value.
The third case is to analyze and check whether the V4 electrode patch satisfies a positional relationship with respect to the human body directly below LN and whether the distance between the two satisfies a relationship within an error-allowable range; if both satisfy the relation, executing the subsequent steps; otherwise, if the former does not meet the relation, returning a result response code result= "error_4_1"; if the former satisfies the relationship but the latter does not, a result response code result= "error_4_2" is returned;
The judging process of whether the V4 electrode patch and LN meet the requirements is as follows:
(matrix[9][2]-matrix[1][2])×(matrix[1][2]-matrix[0][2])+(matrix[9][3]-matrix[1][3])×(matrix[1][3]-matrix[0][3])≤α；
the judging process of whether the distance between the V4 electrode patch and the LN meets the requirements is as follows:
Figure BDA0004102770640000131
wherein matrix [9] [2], matrix [1] [2], matrix [0] [2] represent the abscissa of the electrode patch center point numbered V4 and the human nipple center points numbered LN and RN in the image or video stream, respectively, matrix [9] [3], matrix [1] [3], matrix [0] [3] represent the ordinate of the electrode patch center point numbered V4 and the human nipple center points numbered LN and RN in the image or video stream, respectively, and alpha and beta are maximum allowable error values.
The fourth condition is to calculate the distance range from the center point of the V3 electrode patch to the straight line where the center points of the V2 and V4 electrode patches are located (v3,v2v4) And the distances from the center point of the V3 electrode patch to the center points of the V2 electrode patch and the V4 electrode patch are range respectively (v3,v2) And range (v3,v4) And judge range (v3,v2v4) Whether or not the relationship of 0 within the error allowable range is satisfied (v3,v2) And range (v3,v4) Whether the relationship equal in the error range is satisfied; if both the two are in accordance with the relationship, executing the subsequent steps; if the former is not fullSufficient relation, then return the result response code result= "error_3_1"; if the former satisfies the relationship but the latter does not, a result response code result= "error_3_2" is returned;
range (v3,v2v4) The determination process of whether the requirement of 0 within the error allowable range is satisfied is as follows:
range (v3,v2v4) -β≤0；
range (v3,v2) and range (v2,v4) The determination of whether the requirements for equality within the error allowable range are satisfied is as follows:
|range (v3,v2) -range (v2,v4) |≤β；
where β is the maximum error tolerance value.
The fifth condition is that whether the center point of the V6 electrode patch meets the position relation on the left boundary line of the human body and whether the connecting line of the V6 electrode patch and the center point of the V4 electrode patch meets the position relation with the level of the two human nipples are analyzed and checked, and if the two meet the relation, the subsequent steps are executed; otherwise, if the former does not meet the relation, a result response code is returned, wherein the result response code is = "error_6_1"; if the former satisfies the relationship but the latter does not, a result response code result= "error_6_2" is returned;
the determination of whether the V6 electrode patch center point meets the requirements on the boundary of the left side of the human body is as follows:
(matrix[11][2]-matrix[1][2])×(matrix[1][2]-matrix[0][2])+(matrix[11][3]-matrix[3][3])×(matrix[2][3]-matrix[0][3])≤α；
the judging process of whether the connection line between the V6 electrode patch and the center point of the V4 electrode patch meets the requirements of the level of the nipples of two human bodies is as follows:
(matrix[9][2]-matrix[9][2])×(matrix[1][3]-matrix[0][3])-(matrix[11][3]-matrix[9][3])×(matrix[1][2]-matrix[0][2])≤α；
wherein matrix [9] [2], matrix [11] [2], matrix [1] [2], matrix [0] [2], matrix [3] [2] represent the electrode patch center points numbered V4 and V6 and the abscissa of the human nipple center points numbered LN and RN and the human left boundary line center point numbered LB in the image or video stream, respectively, matrix [9] [3], matrix [11] [3], matrix [1] [3], matrix [0] [3], matrix [3] [3] represent the electrode patch center points numbered V4 and V6 and the ordinate of the human nipple center points numbered LN and RN and the human left boundary line center point numbered LB in the image or video stream, respectively, and α is the maximum allowable error value.
The sixth case is to analyze and check whether the V4, V5, V6 electrode patches satisfy a positional relationship of whether or not they are horizontal with respect to the human body within the range of error; if the relation is satisfied, a result response code= "correct" is returned; otherwise, returning a result response code= "error_5";
the judgment process of whether the V4, V5 and V6 electrode patches meet the positional relationship relative to the human body level within the error allowable range is as follows:
(matrix[10][2]-matrix[9][2])×(matrix[1][3]-matrix[0][3])-(matrix[10][3]-matrix[9][3])×(matrix[1][2]-matrix[0][2])≤α；
wherein matrix [9] [2], matrix [10] [2], matrix [1] [2], matrix [0] [2] represent the horizontal coordinates in the image or video stream of the electrode patch center points numbered V4 and V5 and the human nipple center points numbered LN and RN, respectively, matrix [9] [3], matrix [10] [3], matrix [1] [3], matrix [0] [3] represent the vertical coordinates in the image or video stream of the electrode patch center points numbered V4 and V5 and the human nipple center points numbered LN and RN, respectively, and α is the maximum allowable error value.
It should be noted that, the maximum allowable error α in the embodiment of the present invention is an allowable error for determining that a straight line is vertically set; the maximum allowable error β is set here to be two-thirds of the average frame length of the sum of the lengths and widths of 10 electrode patches in the obtained target image:
Figure BDA0004102770640000151
Wherein matrix [ i+4] [4] and matrix [ i+4] [5] respectively represent the width and the height of the obtained ith electrode patch target frame.
It can be understood that if the calculation result is not the above cases, the result response code is returned = "correct".
Based on the above embodiment, step 300 includes:
if the characteristic operation association result is determined to be wearing error information, feeding back a wearing error electrode patch number and an electrode patch adjusting method to a user by adopting voice or characters;
if the characteristic operation association result is determined to be the wearing correct information, the wearing success prompt information is fed back to the user by voice or characters.
Specifically, according to the different result response codes obtained in the foregoing embodiment, the electrode patch number designed by the result response code and the corresponding prompt information are obtained from table 1, and are fed back to the client in a voice or text mode, as shown in fig. 5, which is an example schematic diagram of feeding back the electrode patch wearing auxiliary inspection result in a voice or text mode, in fig. 5, the electrode patch wearing the problem is framed, and the corresponding voice and text prompt information is given, that is, the prompt "the V4 electrode patch is not located under the left nipple of the human body, and the adjustment is requested.
The method provided by the invention can be applied to mobile terminal or PC terminal application or webpage and other edge equipment, and a user needs to finish wearing the multi-lead electrocardio electrode patch by himself under the condition of home health monitoring or online network consultation.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims (10)

1. A method for positioning a multi-lead electrocardio electrode patch, which is characterized by comprising the following steps:
acquiring video data of an electrocardio electrode patch worn by a user, and inputting the video data of the electrocardio electrode patch worn by the user into a pre-trained target positioning model to obtain body surface characteristics of the upper body of a human body and electrocardio electrode patch characteristic state information;
calculating and obtaining characteristic operation association results of the body surface characteristics of the upper body of the human body and the electrocardio electrode patch characteristic state information;
and generating electrocardio electrode patch wearing state information according to the characteristic operation association result, and determining an electrocardio electrode patch positioning guidance result according to the electrocardio electrode patch wearing state information.
2. The multi-lead electrocardio electrode patch positioning method of claim 1, wherein the acquiring the video data of the electrocardio electrode patch worn by the user, inputting the video data of the electrocardio electrode patch worn by the user into a pre-trained target positioning model to obtain the body surface characteristics of the upper body of the human body and the electrocardio electrode patch characteristic state information comprises the following steps:
initializing an N-dimensional vector comprising a plurality of characteristic state information, wherein N is the total number of the body surface characteristics of the upper body of the human body plus the electrocardio electrode patches, and the plurality of characteristic state information comprises a target type, a target score value, a target center point abscissa, a target center point ordinate, a target detection frame height and a target detection frame width;
if the target type is determined to be a human nipple, performing non-ascending sorting on components corresponding to the human nipple in the plurality of characteristic state information, and taking the first two components as human nipple detection results;
if the target type is determined to be the boundary line of the upper body of the human body, non-ascending order is carried out on the components corresponding to the boundary line of the upper body of the human body in the plurality of characteristic state information, and then the first two components are taken as human body boundary detection results;
If the target type is determined to be an electrode patch, performing non-ascending order on components corresponding to the electrode patch in the plurality of characteristic state information, and taking a plurality of components as electrode patch detection results;
and constructing a two-dimensional matrix according to the human nipple detection result, the human demarcation line detection result and the electrode patch detection result, wherein the two-dimensional matrix comprises a human right nipple component, a human left nipple component, a human right borderline component, a human left borderline component, a right upper limb electrode patch component, a left upper limb electrode patch component, a first chest electrode patch component, a second chest electrode patch component, a third chest electrode patch component, a fourth chest electrode patch component, a fifth chest electrode patch component, a sixth chest electrode patch component, a right lower limb electrode patch component and a left lower limb electrode patch component.
3. The multi-lead ecg electrode patch positioning method of claim 1, wherein the calculating to obtain the feature operation correlation result of the human upper body surface feature and the ecg electrode patch feature status information comprises:
if it is determined that the abscissa of the first chest electrode patch component, the second chest electrode patch component, the third chest electrode patch component, the fourth chest electrode patch component, the fifth chest electrode patch component, and the sixth chest electrode patch component are sequentially incremented, a subsequent calculation step is performed, and otherwise, a first feature operation association result is returned.
4. The multi-lead ecg electrode patch positioning method of claim 1, wherein the calculating obtains a feature operation correlation result of the human upper body surface feature and the ecg electrode patch feature status information, further comprising:
obtaining a first ratio of the absolute value of the first chest electrode patch component ordinate minus the second chest electrode patch component ordinate to the absolute value of the first chest electrode patch component abscissa minus the second chest electrode patch component abscissa, and a second ratio of the absolute value of the human body right nipple component ordinate minus the human body left nipple component ordinate to the absolute value of the human body right nipple component abscissa minus the human body left nipple component abscissa;
if the absolute value of the difference between the first ratio and the second ratio is smaller than or equal to a first preset error value, executing a subsequent calculation step, otherwise, returning a second characteristic operation association result;
obtaining a first product obtained by subtracting the human left nipple component abscissa from the first chest electrode patch component abscissa and subtracting the human right nipple component ordinate from the human left nipple component ordinate, and a second product obtained by subtracting the human right nipple component abscissa from the human left nipple component abscissa from the first chest electrode patch component ordinate and subtracting the human left nipple component ordinate from the human left nipple component ordinate;
If the difference between the first product and the second product is smaller than or equal to the first preset error value, executing the subsequent calculation step, otherwise, returning a third characteristic operation association result;
if the Euclidean distance between the first chest electrode patch component and the human right nipple component is less than or equal to the second preset error value, and the Euclidean distance between the second chest electrode patch component and the human left nipple component is less than or equal to the second preset error value, executing the subsequent calculation step, otherwise, returning to the fourth characteristic operation association result.
5. The multi-lead ecg electrode patch positioning method of claim 1, wherein the calculating obtains a feature operation correlation result of the human upper body surface feature and the ecg electrode patch feature status information, further comprising:
obtaining a third product obtained by multiplying the difference of the fourth chest electrode patch component abscissa minus the human left nipple component abscissa by the difference of the human left nipple component abscissa minus the human right nipple component abscissa, and a fourth product obtained by multiplying the difference of the fourth chest electrode patch component ordinate minus the human left nipple component ordinate by the difference of the human left nipple component ordinate minus the human right nipple component ordinate;
If the difference between the third product and the fourth product is smaller than or equal to a first preset error value, executing a subsequent calculation step, otherwise, returning a fifth characteristic operation association result;
if the Euclidean distance between the patch component of the fourth chest electrode and the left nipple component of the human body is less than or equal to the second preset error value, executing the subsequent calculation step, otherwise, returning to the sixth characteristic operation association result.
6. The multi-lead ecg electrode patch positioning method of claim 1, wherein the calculating obtains a feature operation correlation result of the human upper body surface feature and the ecg electrode patch feature status information, further comprising:
acquiring a first linear distance from a third front electrode patch center point to a connecting line of a second front electrode patch center point and a fourth front electrode patch center point, a second linear distance from the third front electrode patch center point to the second front electrode patch center point, and a third linear distance from the third front electrode patch center point to the fourth front electrode patch center point;
if the difference between the first linear distance and the second preset error value is less than or equal to 0, executing the subsequent calculation step, otherwise, returning to a seventh characteristic operation association result;
And if the absolute value of the difference between the second linear distance and the third linear distance is smaller than or equal to the second preset error value, executing the subsequent calculation step, otherwise, returning to the eighth characteristic operation association result.
7. The multi-lead ecg electrode patch positioning method of claim 1, wherein the calculating obtains a feature operation correlation result of the human upper body surface feature and the ecg electrode patch feature status information, further comprising:
obtaining a fifth product obtained by subtracting the human left boundary component abscissa from the sixth chest electrode patch component abscissa, multiplying the difference of the human left nipple component abscissa and the human right nipple component abscissa from the sixth chest electrode patch component ordinate and multiplying the difference of the human left boundary component ordinate from the sixth chest electrode patch component ordinate and the human right nipple component ordinate from the human left nipple component ordinate;
if the difference between the fifth product and the sixth product is smaller than or equal to a first preset error value, executing a subsequent calculation step, otherwise, returning a ninth characteristic operation association result;
obtaining a seventh product obtained by subtracting the fourth chest electrode patch component abscissa from the sixth chest electrode patch component abscissa and subtracting the human right nipple component ordinate from the human left nipple component ordinate, and an eighth product obtained by subtracting the human right nipple component abscissa from the human left nipple component abscissa from the sixth chest electrode patch component ordinate and subtracting the fourth chest electrode patch component ordinate from the sixth chest electrode patch component ordinate;
And if the difference between the seventh product and the eighth product is less than or equal to the first preset error value, executing the subsequent calculation step, otherwise, returning a tenth characteristic operation association result.
8. The multi-lead ecg electrode patch positioning method of claim 1, wherein the calculating obtains a feature operation correlation result of the human upper body surface feature and the ecg electrode patch feature status information, further comprising:
obtaining a ninth product obtained by subtracting the fourth chest electrode patch component abscissa from the fifth chest electrode patch component abscissa, multiplying the difference of the human left nipple component ordinate and the human right nipple component abscissa from the fifth chest electrode patch component ordinate and a tenth product obtained by subtracting the fourth chest electrode patch component ordinate from the fifth chest electrode patch component ordinate and multiplying the difference of the human left nipple component abscissa and the human right nipple component abscissa from the human left nipple component abscissa;
and if the difference between the ninth product and the tenth product is smaller than the first preset error value, executing the subsequent calculation step, otherwise, returning to the eleventh characteristic operation association result.
9. The method of any one of claims 4 to 6, wherein the second predetermined error value is obtained by multiplying a predetermined ratio by an average frame length of a sum of target frame lengths and target frame widths of 10 electrode patches in a two-dimensional matrix.
10. The multi-lead ecg electrode patch positioning method of claim 1, wherein the generating ecg electrode patch wearing state information from the characteristic operation association result, determining an ecg electrode patch positioning guidance result from the ecg electrode patch wearing state information, comprises:
if the characteristic operation association result is determined to be wearing error information, feeding back a wearing error electrode patch number and an electrode patch adjusting method to a user by adopting voice or characters;
if the characteristic operation association result is determined to be the wearing correct information, the wearing success prompt information is fed back to the user by voice or characters.
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Publication number Priority date Publication date Assignee Title
CN117281484A (en) * 2023-11-24 2023-12-26 深圳启脉科技有限公司 Identification method for wearing position of mobile monitoring equipment

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117281484A (en) * 2023-11-24 2023-12-26 深圳启脉科技有限公司 Identification method for wearing position of mobile monitoring equipment
CN117281484B (en) * 2023-11-24 2024-03-01 深圳启脉科技有限公司 Wearing position identification method of monitoring device

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