CN118303893A - Artificial intelligence assisted electrocardio and wearable ultrasonic monitoring system and method - Google Patents

Abstract

The invention relates to the technical field of electrocardiograph monitoring, in particular to an artificial intelligence-assisted electrocardiograph and wearable ultrasonic monitoring system and method. The system comprises an electrode plate, a detection unit and a control unit, wherein the electrode plate is attached to a tested object and is used for collecting electrocardiosignals of the tested object; the wearable ultrasonic equipment is arranged on the body surface of the tested object, and can controllably transmit and receive ultrasonic waves based on a wake-up signal to generate heart monitoring data of the tested object; the electrocardiograph monitoring device is connected with the electrode plate to receive electrocardiograph signals; the electrocardio analysis module is connected with the electrocardio monitoring equipment and used for analyzing electrocardio signals in real time; the ultrasonic triggering module is connected with the electrocardio analysis module and is used for outputting a wake-up signal after the electrocardio analysis module detects the abnormality. According to the invention, by combining the electrocardio monitoring equipment with the wearable ultrasonic equipment, continuous monitoring of the heart structure and function is realized, and more comprehensive and accurate heart monitoring data is provided.

Description

Artificial intelligence assisted electrocardio and wearable ultrasonic monitoring system and method

Technical Field

The invention relates to the technical field of electrocardiograph monitoring, in particular to an electrocardiograph and wearable ultrasonic monitoring system and method.

Background

A 24-hour electrocardiogram (Holter monitoring) is a kind of examination in which an electrocardiogram is continuously recorded, and the electrical activity of the heart is evaluated by continuously recording the electrocardiogram for 24 hours, for monitoring arrhythmia, evaluating the effect of medication, and finding the cause. However, conventional Holter monitoring has a limitation on direct observation of the heart structure while capturing the electrocardiographic abnormality, and compared with other electrocardiographic examinations, holter monitoring has a limitation on observation of the heart structure, and direct observation of the heart structure is not possible. For example, structural images of the heart and blood flow data cannot be determined.

Disclosure of Invention

The invention aims to provide an artificial intelligence auxiliary electrocardio and wearable ultrasonic monitoring system, which solves the technical problems;

the invention also aims to provide an artificial intelligence assisted electrocardio and wearable ultrasonic monitoring method, which solves the technical problems.

The technical problems solved by the invention can be realized by adopting the following technical scheme:

an artificial intelligence aided electrocardio and wearable ultrasonic monitoring system comprises,

The electrode plate is attached to the measured object and is used for collecting electrocardiosignals of the measured object;

The wearable ultrasonic equipment is arranged on the body surface of the tested object, and can controllably transmit and receive ultrasonic waves based on a wake-up signal to generate heart monitoring data of the tested object;

The electrocardiograph monitoring equipment is connected with the electrode plate to receive the electrocardiograph signals;

The electrocardio analysis module is connected with the electrocardio monitoring equipment and is used for analyzing the electrocardio signals in real time, detecting the abnormal state of the current waveform and predicting the abnormal condition of the next cardiac cycle;

The ultrasonic triggering module is connected with the electrocardio analysis module and is used for outputting the wake-up signal after the electrocardio analysis module detects the abnormality.

Preferably, the heart color ultrasound scanning device further comprises a heart color ultrasound pre-scanning module for pre-scanning the heart part of the detected object to obtain pre-scanning data, and the wearing position of the ultrasonic device is determined based on the pre-scanning data.

Preferably, the ultrasound device comprises,

A transducer for transmitting and receiving ultrasound waves, producing the cardiac monitoring data;

The solid coupling agent is arranged between the measured object and the transducer and used for transmitting ultrasonic waves;

And the mounting belt is used for binding the transducer and the solid coupling agent on the outer side of the body surface of the tested object.

Preferably, the electrocardiographic analysis module is a trained long-short-period memory network model, and is used for identifying characteristic waveforms of arrhythmia and predicting abnormality of the next cardiac cycle.

Preferably, the cardiac monitoring data includes two-dimensional imaging data and blood flow velocity data.

Preferably, the ultrasound device is further connected to an external medical image system for deriving the cardiac monitoring data to the medical image system.

An artificial intelligence aided electrocardio and wearable ultrasonic monitoring method is applied to the artificial intelligence aided electrocardio and wearable ultrasonic monitoring system, comprising,

Step S1, attaching the electrode plate to a measured object, connecting the electrode plate to the electrocardiograph monitoring equipment, and wearing the ultrasonic equipment on the body surface of the measured object according to a wearing position;

Step S2, starting the electrocardiograph monitoring equipment and the ultrasonic equipment, setting parameters of the ultrasonic equipment, and acquiring the electrocardiograph signals in real time by the electrocardiograph monitoring equipment through the electrode plates;

Step S3, the electrocardio signal is analyzed in real time by the electrocardio analysis module, and the abnormal state of the current waveform is detected and the abnormal condition of the next cardiac cycle is predicted;

step S4, the ultrasonic triggering module judges whether the triggering condition of the ultrasonic equipment is met, if yes, the wake-up signal is sent out, the ultrasonic equipment transmits and receives ultrasonic waves, and heart monitoring data are generated; otherwise, the step S3 is executed back.

Preferably, the method further comprises the steps of,

Step S0, a heart color ultrasound pre-scanning module performs pre-scanning on a heart part of a measured object to obtain pre-scanning data, and the wearing position is determined based on the pre-scanning data.

Preferably, the setting parameters of the ultrasound device in step S2 includes a trigger condition of the ultrasound device, a gain of ultrasound, a blood flow region interest box, and a sampling line.

Preferably, the method further comprises the steps of,

And S5, the ultrasonic equipment records the heart monitoring data in a period of time until the heart beat of the tested object is recovered to be normal, the ultrasonic equipment stops working and enters a sleep state after the heart beat of the tested object is recovered to be normal, and the heart monitoring data is imported into an external medical image system.

The invention has the beneficial effects that: by adopting the technical scheme, the invention realizes continuous monitoring of the structure and the function of the heart by combining the electrocardio monitoring equipment with the wearable ultrasonic equipment, and provides more comprehensive and accurate heart monitoring data.

Drawings

FIG. 1 is a schematic diagram of an artificial intelligence assisted electrocardiograph and wearable ultrasound monitoring system in an embodiment of the present invention;

FIG. 2 is a schematic diagram of an ultrasonic apparatus according to an embodiment of the present invention;

fig. 3 is a step diagram of an artificial intelligence aided electrocardiograph and wearable ultrasound monitoring method in an embodiment of the present invention.

In the accompanying drawings: 1. an electrode sheet; 2. an ultrasonic device; 21. a transducer; 22. a solid coupling agent; 23. a mounting belt; 3. an electrocardiographic monitoring device; 4. an electrocardiograph analysis module; 5. and an ultrasonic triggering module.

Detailed Description

The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but 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.

It should be noted that, without conflict, the embodiments of the present invention and features of the embodiments may be combined with each other.

The invention is further described below with reference to the drawings and specific examples, which are not intended to be limiting.

An artificial intelligence assisted electrocardiograph and wearable ultrasound monitoring system, as shown in fig. 1 and 2, comprises,

The electrode plate 1 is attached to the measured object and is used for collecting electrocardiosignals of the measured object;

The wearable ultrasonic equipment 2 is arranged on the body surface of the tested object, and can controllably transmit and receive ultrasonic waves based on a wake-up signal to generate heart monitoring data of the tested object;

The electrocardiograph monitoring device 3 is connected with the electrode plate 1 to receive electrocardiograph signals;

the electrocardio analysis module 4 is connected with the electrocardio monitoring equipment 3 and is used for analyzing electrocardio signals in real time, detecting the abnormal state of the current waveform and predicting the abnormal condition of the next cardiac cycle;

the ultrasonic triggering module 5 is connected with the electrocardio analysis module 4 and is used for outputting a wake-up signal after the electrocardio analysis module 4 detects the abnormality.

Specifically, the invention aims to realize continuous monitoring of the structure and the function of the heart by combining 24-hour electrocardiographic monitoring with wearable ultrasound, and provide more comprehensive and accurate auxiliary information for the subsequent diagnosis and treatment of heart diseases.

In a preferred embodiment, the device further comprises a heart color ultrasound pre-scanning module, which is used for pre-scanning the heart part of the tested object to obtain pre-scanning data, and determining the wearing position of the ultrasonic device 2 based on the pre-scanning data.

Specifically, the heart color ultrasound pre-scanning module performs heart color ultrasound pre-scanning before monitoring to obtain pre-scanning data, the wearing position of the ultrasonic device 2 is determined according to the pre-scanning data, in a preferred embodiment, the pre-scanning data is transmitted to an external abnormality detection system, heart parts including a left ventricle, a left atrium, a right ventricle and a right atrium are marked by a manual observation mode, and then the wearing position for placing the ultrasonic device 2, such as a long axial surface, a short axial surface and a four-cavity surface of the apex of the heart, is set.

In a preferred embodiment, and with further reference to fig. 2, the ultrasound device 2 comprises,

A transducer 21 for transmitting and receiving ultrasonic waves, generating heart monitoring data;

A solid coupling agent 22, which is arranged between the measured object and the transducer 21 and is used for transmitting ultrasonic waves;

and a mounting band 23 for binding the transducer 21 and the solid couplant 22 to the outside of the body surface of the object to be measured.

Specifically, the wearable ultrasonic device 2 is a portable patch-type ultrasonic probe apparatus, which is composed of a transducer 21, a solid-state couplant 22, and a mounting tape 23, and the transducer 21 is a core component of the ultrasonic probe, responsible for transmitting and receiving ultrasonic waves, thereby generating images of the heart and blood flow data. A solid couplant 22 is located between the transducer 21 and the skin and is primarily responsible for providing an unobstructed propagation medium for the ultrasound waves, ensuring that the ultrasound waves are efficiently transmitted from the probe to the skin and penetrate into the heart tissue. The mounting straps 23 are used to secure the entire device to the skin, ensuring intimate contact between the probe and the skin during monitoring, preventing displacement or removal due to activity. The mounting belt 23 in this embodiment may be an adhesive tape to bind the ultrasonic device 2 and the object to be measured.

When the ultrasound device 2 starts monitoring, the transducer 21 starts emitting ultrasound waves of low intensity. Ultrasound enters the body of the object to be measured through the solid couplant 22, and echoes are generated when the ultrasound encounters tissues with different densities such as the heart. The transducer 21 receives the echoes and converts them into electrical signals. The electrical signals are then converted into two-dimensional images and blood flow velocity data for further analysis and diagnostic use.

It should be noted that in order to ensure efficient operation of the ultrasound device 2, it is necessary to precisely adjust its position and angle in order to capture an optimal image of the heart. According to the result of the heart color ultrasound pre-scanning, medical staff can place the probe at a set wearing position, and the optimal monitoring angle is determined through debugging.

In a preferred embodiment, the electrocardiographic analysis module 4 is a trained long-short term memory network model for identifying characteristic waveforms of arrhythmias and predicting abnormalities of the next cardiac cycle.

Specifically, the system adopts a long-short-term memory network (LSTM) model to carry out deep learning analysis on the real-time electrocardiosignals. The LSTM model is particularly suitable for handling and predicting long-term dependency problems of the interval and delay in the time series. In the analysis of the electrocardiographic signals, the model is trained to identify characteristic waveforms of arrhythmias, such as abnormal cardiac rhythm events such as ventricular premature beat, atrial premature beat, tachycardia, etc.

In the monitoring process, the system continuously receives data of electrocardiosignals, and feeds the LSTM model by using the data updated in real time. The LSTM model analyzes the current heartbeat waveform and predicts the abnormality of the next cardiac cycle. When the model predicts potential arrhythmia, the system automatically enters a high alert state and is ready to trigger ultrasonic monitoring; preferably, the neural network is utilized to analyze the electrocardiosignals in real time, predict abnormal cardiac cycles and improve the sensitivity to arrhythmia.

In a preferred embodiment, the cardiac monitoring data includes two-dimensional imaging data and blood flow velocity data.

Specifically, once the triggering condition of electrocardiographic monitoring is satisfied, for example, arrhythmia predicted by the LSTM model, the ultrasound triggering module 5 immediately sends a wake-up signal to wake up the ultrasound device 2. The ultrasound device 2 then starts recording the ultrasound image sequence for a predetermined time by switching on the B mode and the doppler mode. During this period, the wearable ultrasonic device 2 continuously monitors the dynamic change of the heart until the electrocardiographic analysis module 4 monitors that the heartbeat is restored to the normal state. Once the heart rhythm is restored to be normal, the ultrasonic equipment 2 automatically freezes the current monitoring state and enters a sleep mode to wait for the next triggering; preferably, by means of electrocardiographic triggering ultrasound, corresponding ultrasound images are obtained in time when electrocardiographic abnormality is concerned, and subsequent further understanding of abnormal heart structures and functions is facilitated.

More specifically, the B-mode is a basic two-dimensional ultrasound imaging mode for displaying the structure and morphology of tissue. In B mode, ultrasound scans tissue in a line-by-line fashion, producing a series of horizontal slice images, producing two-dimensional image data. The Doppler mode is used for detecting and displaying blood flow conditions and acquiring blood flow velocity data, so that the invention realizes comprehensive monitoring of heart structure and functions and provides more information for subsequent diagnosis of heart diseases.

In a preferred embodiment, the ultrasound device 2 is also connected to an external medical image system for deriving cardiac monitoring data to the medical image system.

Specifically, cardiac monitoring data is exported to a medical image (PACS) system for subsequent offline analysis and long-term review.

An artificial intelligence aided electrocardio and wearable ultrasonic monitoring method is applied to an artificial intelligence aided electrocardio and wearable ultrasonic monitoring system in any one embodiment, as shown in figure 3, and comprises,

Step S1, attaching an electrode sheet 1 to a measured object and connecting an electrocardiographic monitoring device 3, and wearing an ultrasonic device 2 on the body surface of the measured object according to a wearing position;

Step S2, starting the electrocardiograph monitoring equipment 3 and the ultrasonic equipment 2, setting parameters of the ultrasonic equipment 2, and acquiring electrocardiograph signals in real time by the electrocardiograph monitoring equipment 3 through the electrode sheet 1;

Step S3, the electrocardio-signal analysis module 4 analyzes electrocardio-signals in real time, detects the abnormal state of the current waveform and predicts the abnormal condition of the next cardiac cycle;

Step S4, the ultrasonic triggering module 5 judges whether the triggering condition of the ultrasonic equipment 2 is met, if yes, a wake-up signal is sent out, the ultrasonic equipment 2 transmits and receives ultrasonic waves, and heart monitoring data are generated; otherwise, the step S3 is executed back.

In a preferred embodiment, the method further comprises,

Step S0, the heart color ultrasound pre-scanning module performs pre-scanning on a heart part of a measured object to obtain pre-scanning data, and determines a wearing position based on the pre-scanning data.

In a preferred embodiment, the setting of the parameters of the ultrasound device 2 in step S2 includes the triggering conditions of the ultrasound device 2, the gain of the ultrasound, the blood flow region box of interest and the sampling line.

Specifically, the triggering condition of the ultrasonic device 2 in the invention is arrhythmia detected by the electrocardiographic analysis module 4, the ultrasonic gain can adjust the ultrasonic intensity, a blood flow region interest (ROI) box is used for selecting a region of interest, and the region of interest can be placed in a blood vessel to measure the blood flow speed. The sampling line may be moved within a blood vessel or within a blood flow ROI frame to obtain blood flow velocity information at different locations.

In a preferred embodiment, the method further comprises,

Step S5, the ultrasonic equipment 2 records heart monitoring data in a period of time until the heart beat of the tested object is recovered to be normal, the ultrasonic equipment 2 stops working to enter a sleep state after the heart beat of the tested object is recovered to be normal, and the heart monitoring data is imported to an external medical image system.

The foregoing description is only illustrative of the preferred embodiments of the present invention and is not to be construed as limiting the scope of the invention, and it will be appreciated by those skilled in the art that equivalent substitutions and obvious variations may be made using the description and illustrations of the present invention, and are intended to be included within the scope of the present invention.

Claims (10)

1. An artificial intelligence assisted electrocardiograph and wearable ultrasonic monitoring system is characterized by comprising,

The electrode plate is attached to the measured object and is used for collecting electrocardiosignals of the measured object;

The wearable ultrasonic equipment is arranged on the body surface of the tested object, and can controllably transmit and receive ultrasonic waves based on a wake-up signal to generate heart monitoring data of the tested object;

The electrocardiograph monitoring equipment is connected with the electrode plate to receive the electrocardiograph signals;

The electrocardio analysis module is connected with the electrocardio monitoring equipment and is used for analyzing the electrocardio signals in real time, detecting the abnormal state of the current waveform and predicting the abnormal condition of the next cardiac cycle;

The ultrasonic triggering module is connected with the electrocardio analysis module and is used for outputting the wake-up signal after the electrocardio analysis module detects the abnormality.

2. The artificial intelligence assisted electrocardiograph and wearable ultrasound monitoring system of claim 1, further comprising a heart color ultrasound pre-scanning module configured to pre-scan a heart portion of a subject to be measured to obtain pre-scan data, and determine a wearing position of the ultrasound device based on the pre-scan data.

3. The artificial intelligence assisted electrocardiography and wearable ultrasound monitoring system of claim 1 wherein the ultrasound device comprises,

A transducer for transmitting and receiving ultrasound waves, producing the cardiac monitoring data;

The solid coupling agent is arranged between the measured object and the transducer and used for transmitting ultrasonic waves;

And the mounting belt is used for binding the transducer and the solid coupling agent on the outer side of the body surface of the tested object.

4. The artificial intelligence assisted cardiac electrical and wearable ultrasound monitoring system of claim 1, wherein the electrocardiographic analysis module is a trained long and short term memory network model for identifying characteristic waveforms of arrhythmias and predicting abnormalities for the next cardiac cycle.

5. The artificial intelligence assisted cardiac electrical and wearable ultrasound monitoring system of claim 1, wherein the cardiac monitoring data comprises two-dimensional imaging data and blood flow velocity data.

6. The artificial intelligence assisted cardiac electrical and wearable ultrasound monitoring system of claim 1, wherein the ultrasound device is further connected to an external medical imaging system for deriving the cardiac monitoring data to the medical imaging system.

7. An artificial intelligence aided electrocardio and wearable ultrasonic monitoring method, which is characterized in that the method is applied to the artificial intelligence aided electrocardio and wearable ultrasonic monitoring system in any one of claims 1-6, and comprises the following steps of,

Step S1, attaching the electrode plate to a measured object, connecting the electrode plate to the electrocardiograph monitoring equipment, and wearing the ultrasonic equipment on the body surface of the measured object according to a wearing position;

Step S2, starting the electrocardiograph monitoring equipment and the ultrasonic equipment, setting parameters of the ultrasonic equipment, and acquiring the electrocardiograph signals in real time by the electrocardiograph monitoring equipment through the electrode plates;

Step S3, the electrocardio signal is analyzed in real time by the electrocardio analysis module, and the abnormal state of the current waveform is detected and the abnormal condition of the next cardiac cycle is predicted;

step S4, the ultrasonic triggering module judges whether the triggering condition of the ultrasonic equipment is met, if yes, the wake-up signal is sent out, the ultrasonic equipment transmits and receives ultrasonic waves, and heart monitoring data are generated; otherwise, the step S3 is executed back.

8. The artificial intelligence assisted electrocardiograph and wearable ultrasound monitoring method of claim 7, further comprising,

Step S0, a heart color ultrasound pre-scanning module performs pre-scanning on a heart part of a measured object to obtain pre-scanning data, and the wearing position is determined based on the pre-scanning data.

9. The artificial intelligence aided electrocardiographic and wearable ultrasound monitoring method of claim 7, wherein setting parameters of the ultrasound device in step S2 includes triggering conditions of the ultrasound device, gain of ultrasound, blood flow region interest box and sampling line.

10. The artificial intelligence assisted electrocardiograph and wearable ultrasound monitoring method of claim 7, further comprising,

And S5, the ultrasonic equipment records the heart monitoring data in a period of time until the heart beat of the tested object is recovered to be normal, the ultrasonic equipment stops working and enters a sleep state after the heart beat of the tested object is recovered to be normal, and the heart monitoring data is imported into an external medical image system.