CN111514458A - Wearable ECG dynamic full-true mapping intelligent defibrillator and its control method - Google Patents

Abstract

The invention discloses a wearable electrocardiographic dynamic full-true mapping intelligent defibrillator, comprising clothing and a detachable electrocardiographic patch, a defibrillation electrode patch, a flexible accumulator, a miniature embedded device mounted on the clothing The control center, ECG patches and defibrillation electrode patches are connected to the micro-embedded control center; the flexible energy storage supplies power to the micro-embedded control center, defibrillation electrode patches, and micro-embedded control center. The flexible energy storage includes Flexible aqueous batteries and/or flexible supercapacitors. The invention realizes long-term and continuous monitoring of 12-lead cardiac electrical activity, and can be used for the diagnosis, prognosis evaluation and prevention of complications of cardiovascular diseases, sleep apnea syndrome and other diseases; defibrillation can be carried out in a timely and safe manner, and Can effectively avoid mis-discharge. The invention also discloses a control method of the wearable ECG dynamic full-true mapping intelligent defibrillator.

Description

Wearable ECG dynamic full-true mapping intelligent defibrillator and its control method

technical field

The invention relates to an intelligent medical device, in particular to a wearable electrocardiogram dynamic full-true mapping intelligent defibrillator.

Background technique

Cardiovascular disease is the disease with the highest morbidity and mortality worldwide. According to the "Heart Disease and Stroke Statistics (2019 Edition)" released by the American Heart Association, in 2016, more than 17.6 million people died of cardiovascular disease worldwide, ranking first among all causes of death; among them, coronary atherosclerosis Heart disease (coronary heart disease) is the leading cause of death from cardiovascular disease in all regions of the world. "China Cardiovascular Disease Report 2018" pointed out that in 2016, the number of patients with cardiovascular disease in my country was as high as 290 million; the number of deaths due to cardiovascular disease accounted for the first place in the total number of deaths among urban and rural residents; and its prevalence and mortality were still on the rise. stage. According to reports, in 2016 alone, the total number of patients with cardiovascular disease discharged from hospitals in my country was as high as 20.0219 million, accounting for 12.57% of the total number of discharges during the same period. It is not difficult to see that cardiovascular disease has brought a huge national economic and health burden to our country.

The vast majority of patients with cardiovascular disease die from cardiac arrest. Cardiac arrest is when the heart suddenly stops pumping blood, causing severe ischemia and lack of oxygen to vital organs (such as the brain), resulting in the termination of life. This sudden death due to cardiac causes is also known as sudden cardiac death in medicine. According to the "2016 Expert Consensus on Chinese Cardiopulmonary Resuscitation", about 544,000 people suffer from cardiac arrest every year in my country, and an average of 1,500 people die of cardiac arrest every day, and the success rate of rescue is less than 1%. In the United States, there are about 326,000 out-of-hospital cardiac arrests and 209,000 in-hospital cardiac arrests each year, with corresponding survival rates of 10% and 24%, respectively, much higher than in my country. It can be seen that the incidence of cardiac arrest in my country has gradually approached the level of developed countries, but the overall rescue level is far lower than that of developed countries and regions.

The most effective treatment for cardiac arrest is electrical defibrillation. When cardiac arrest occurs, the patient presents as apnea, unconsciousness, unpalatable aortic pulse, and the cardiac electrical activity often manifests as tachy ventricular arrhythmia (such as ventricular fibrillation, pulseless ventricular tachycardia, etc.). Sudden cardiac death can result if a patient's heart fails to beat within a few minutes. Electrical defibrillation can terminate ventricular fibrillation by a large amount of short-term discharge, and then the sinus node, which is the pacemaker of the heart, is normally excited, and the heartbeat is re-controlled so that the heart returns to normal beating. Clinical trials have confirmed that for cardiac arrest patients, effective electrical defibrillation within 3-5 minutes is the only pre-hospital emergency method that can effectively reduce patient mortality. In cardiac arrest with ventricular fibrillation, every minute of defibrillation delay reduces the likelihood of survival by 7%-10% without CPR support and by 3%-4% per minute with CPR support . Therefore, early and timely identification of ventricular fibrillation and electrical defibrillation in cardiac arrest patients are crucial. However, at present, the popularization of first aid knowledge in my country is low, the recognition rate of cardiac arrest is low, and the popularity of automatic external defibrillator (AED) is poor. A number of domestic surveys and studies have shown that the deployment rate of defibrillators in township health centers is less than 10%; in the economically developed Yangtze River Delta region, the development rate of external defibrillation in first-class hospitals is still less than 50%, and emergency department physicians in primary hospitals can be familiar with it. Only 50% of them have knowledge of cardiac electrical defibrillation, and less than 10% of medical staff have ever used a defibrillator. These current situations lead to cardiac arrest patients in my country often missing the best chance of rescue.

In order to prevent the occurrence of sudden cardiac death, for specific patients (specific structural heart disease accompanied by malignant arrhythmia, primary electrocardiographic disease, patients with significantly impaired left ventricular systolic function, etc.), implantable cardiopulmonary bypass The ICD is a common choice in clinical practice. It can automatically detect tachy ventricular arrhythmias such as ventricular tachycardia and ventricular fibrillation and perform overdrive pacing suppression and shock cardioversion. But ICDs need to be surgically implanted into the patient, which can lead to complications such as bleeding, infection, and pneumothorax. There is also the possibility of major adverse events such as dislocation of the endocardial lead, rupture and destruction of the lead insulation, and loose lead and ICD connections. Although the clinical efficacy of ICD is good, it is limited by factors such as my country's economic development level, scarcity of medical resources, traditional medical concept, high surgical risk, multiple and severe complications, and the need for regular surgery to replace batteries. Patients with vascular disease still face a great risk of sudden death.

Existing defibrillation devices mainly include the following:

1. AED: Automatic External Defibrillator

Features: Through 2 leads, the type of malignant arrhythmia can be quickly identified, the defibrillation heart rate can be distinguished in time, and the energy of 200 joules can be instantly reached. It is easy to operate and can be used skillfully with a little training. *Currently, the penetration rate of automatic defibrillators is relatively low, especially in some small cities.

Disadvantages: The coverage of AEDs in China is very low, and most patients lost their lives due to missing the rescue time. Currently, the automatic defibrillators configured in China are not allowed to be used by untrained non-professionals. They are large in size, heavy in quality, and expensive It is more expensive and has a single function (only for cardiac arrest patients).

2. ICD/SICD: Implantable Cardiac Defibrillator/Subcutaneous Implantable Cardiac Defibrillator

Features: Small in size, it can be implanted into the chest or abdominal cavity of patients, and can help control some potentially fatal arrhythmias through electrical pulses or shocks. Implanting defibrillators can improve the survival rate of patients with left ventricular dysfunction.

Disadvantages: The placement of the device is invasive and requires interventional surgery; high cost, long hospital stay, and high opportunity cost; there is a risk of infection, hemorrhage and even death from shock; lack of real-time data analysis, only electrocardiogram diagnosis can be obtained Combined with clinical symptoms, clinical diagnosis can be achieved; it is impossible to formulate a treatment plan according to the patient's condition; it is troublesome to replace the battery.

3. WCD: wearable cardioverter-defibrillator system

WCD is mainly composed of defibrillation electrodes and defibrillation host. Its defibrillation vest contains 1 defibrillation electrode on the front chest, 2 defibrillation electrodes on the back, and 4 ECG sensing patch electrodes. The defibrillation host is located at the waist, and there are function keys and an electrocardiogram display on it. In addition, there are 10 self-breaking conductive gel capsules on each defibrillation paddle to help sense the electrical activity of the heart. The ECG sensing patch electrode detects that the patient's heart rate exceeds the set treatment frequency (usually between 120 and 250 beats/min, usually 150 beats/min), and the tachyarrhythmia exceeds the set time (usually 5 to 6 beats/min). seconds), the instrument compares the ECG with the template to determine whether it is indeed VT/VF; if it is VT/VF, the WCD will send out a vibration alarm and a flashing light to remind the patient, and the patient can manually terminate the treatment; When VT/ventricular fibrillation persists, the WCD automatically charges and releases the conductive gel, and sends out 75-150 focal bidirectional defibrillation waves; if it cannot be terminated, the WCD can also release 4 defibrillation waves. From the design of WCD, it can be seen that WCD has some advantages, such as no surgery, simple use, low cost of short-term use, lower cost of ICD follow-up, and alternative treatment when ICD is temporarily removed.

The above three kinds of defibrillation devices have the following defects:

1. Higher false discharge rate of AED ICD WCD;

2. The ECG monitoring of the three is a fixed algorithm, and the more advanced artificial intelligence, deep learning, cloud computing, big data and other algorithms have not been used to improve the safety and effectiveness of ECG monitoring;

3. The patch used is relatively simple, uncomfortable to wear and easy to fall off;

4. The safety process of discharge monitoring is simple and the safety is not high;

5. The power of the battery used is limited, and the storage measures require a higher power, resulting in a larger battery volume, inconvenient to carry, and limited discharge times.

SUMMARY OF THE INVENTION

The present invention aims to provide a wearable ECG dynamic full-true mapping intelligent defibrillator, capable of performing ECG monitoring and processing of electric shock defibrillation when necessary, and effectively improving the shortcomings and deficiencies of current electric shock defibrillation equipment.

To achieve the above object, the present invention adopts the following technical solutions to realize:

The wearable ECG dynamic full-true mapping intelligent defibrillator disclosed in the present invention includes clothing and a detachable ECG patch, a defibrillation electrode patch, a flexible accumulator, and a micro embedded control device that are detachably mounted on the clothing. The ECG patch and the defibrillation electrode patch are connected to the micro-embedded control center; the flexible energy storage powers the micro-embedded control center, the defibrillation electrode patch, and the micro-embedded control center, and the flexible storage Energy devices include flexible aqueous batteries and/or flexible supercapacitors.

Preferably, the ECG patch has a built-in ECG sensor, including a digital 50Hz wave trap, the ECG patch and its connecting wires are provided with a shielding layer, there are 10 ECG patches, and 10 ECG patches The arrangement is as follows: 5 on the left chest, 1 on the right chest, two on the abdomen, and two between the collar and the chest; there are two defibrillation electrode patches, one of which defibrillates The electrode patch is located on the lower left chest and directly below the 5 ECG patches on the left chest, and another defibrillation electrode patch is located on the upper right chest.

Further, the micro-embedded control center includes a Beidou GPS dual-mode positioning system.

Preferably, the flexible water-based battery is a nickel-zinc primary battery, the positive electrode of the nickel-zinc primary battery is a nickel hydroxide active material supported by nickel foam, the size of the positive electrode is 10×10×0.04cm, and the negative electrode of the nickel-zinc primary battery is Extremely foamed copper electrodeposited zinc, the size of the negative electrode is 10×10×0.1cm, the electrolyte is 6M KOH, the separator is a non-woven separator, and the size of the nickel-zinc primary battery is 10×10×0.3cm.

Preferably, the miniature embedded control center includes an ADS1292 integrated chip, a Cortex-M0 LPC1114 processor, a Flash Memory memory chip and a Bluetooth transmission module.

Preferably, the clothes are women's or men's styles, and the women's style is provided with a chest pad.

Further, the present invention also includes a cloud platform and a mobile terminal, the cloud platform is a composite platform of BIM+3DGIS+CIM technology, the cloud platform is wirelessly connected with the mobile terminal, and the mobile terminal is wirelessly connected with the micro embedded control center.

Preferably, the cloud platform is a corPace cloud platform, and the corPace cloud platform includes a business application layer, a basic support layer and a data layer, and the business application layer and the basic support layer share log records, authority control, business application layers, basic The support layer and the data layer share transaction management, hierarchical management and database management;

The business application layer includes functional services, an operation and maintenance management platform and a terminal view analyzer, and the functional services include comprehensive data analysis, online diagnosis and defibrillation;

The basic support layer includes an ECG classifier based on deep learning;

The data layer includes the MySQ database.

The invention also discloses a control method suitable for the wearable ECG dynamic full-true mapping intelligent defibrillator, including six protective measures, and the six protective measures include:

The first step is to identify specific waveforms and make accurate diagnosis. After obtaining the patient's ECG information, the cloud will combine the patient's previous basic ECG information and cloud big data to perform deep learning to make an accurate diagnosis of ventricular fibrillation. ;

The second channel, dual centers send defibrillation commands. When the cloud platform is online, its control right is higher than that of the micro-embedded control center. When it is identified that the patient has ventricular fibrillation, the cloud platform sends defibrillation commands through the mobile terminal, embedded The embedded control center reaches the defibrillation module for defibrillation; when the mobile terminal or cloud platform is offline, the embedded control center judges according to the R wave and ventricular fibrillation rhythm, and directly sends the defibrillation when the R wave and ventricular fibrillation are identified. Command to the defibrillation module for defibrillation;

The third channel, dual-sensing auxiliary judgment, judges the patient's breathing and heartbeat status through the additional breathing sensor and apical pulse sensor;

The fourth channel, the recognition and early warning of defibrillation pads falling off, when the defibrillation pads fall off, the built-in sensor of the defibrillation pads will identify and upload an alarm, and no defibrillation will be performed;

The fifth channel: Recognition of exogenous bioelectrical signals, identifying exogenous bioelectrical signals through the Corpace heart rhythm, when the exogenous bioelectrical signals exist, the defibrillation module will give a light and voice alarm to remind others not to touch the patient, and will carry out defibrillation;

The sixth channel: Delayed discharge, patient self-control, when the defibrillation command is issued, the defibrillation module will give a 25-second light and sound alarm to remind the patient that defibrillation is about to be defibrillated. The patient can turn off the defibrillation command through the manual switch. After it is not turned off, the defibrillation module performs discharge defibrillation.

Preferably, the method for identifying a specific waveform includes the following steps:

Step 1. Identify the highest point of voltage/amplitude for each lead;

Step 2. Calculate the height difference between the highest points of the waveform and the horizontal distance between the highest points of each lead;

Step 3. If there is a height difference between the highest points between leads exceeding 0.05 mV, it is judged as a non-ventricular fibrillation waveform; if there is no height difference between the highest points between any leads exceeding 0.05 mV, it is judged as a ventricular fibrillation waveform;

The deep learning uses 200,000 ECGs that correctly standardize ECG diagnosis to obtain key models related to ventricular fibrillation. The ECG includes the following categories: normal ECG, atrial tachycardia, ventricular fibrillation, sinus arrhythmia, Atrial tachycardia, atrial fibrillation, junctional tachycardia, pre-excitation syndrome, atrioventricular block, intraventricular block, pacemaker rhythm, and no less than 10,000 electrocardiograms of each category.

The beneficial effects of the present invention are as follows:

1. The present invention realizes long-term and continuous monitoring of 12-lead ECG activity, which can be used for diagnosis, prognosis evaluation and prevention of complications of cardiovascular diseases, sleep apnea syndrome and other diseases.

2. The present invention can defibrillate in a timely and safe manner, and can effectively avoid mis-discharge.

3. The present invention uses an aqueous nickel-zinc battery, which has the characteristics of short charging time and long battery life.

4. The precise positioning of the present invention provides users with safe and effective protection, so as to rescue in time in an emergency and escort life.

5. The present invention can store, map and manage various types of data, and provide support services and protection services for various types of analysis and data integration. It can intelligently identify the transmitted ECG signal, and use computer vision and natural language processing technology to combine with other clinical data of the patient, give timely feedback and reports after comprehensive analysis and processing, and carry out accurate diagnosis of the patient.

6. The CorPace cloud platform can realize the treatment of asymptomatic (occult) coronary heart disease, atrial fibrillation, sinus arrhythmia, supraventricular tachycardia, ventricular tachycardia, atrioventricular block, sick sinus syndrome symptoms, torsades de pointes, pre-excitation syndrome, atrioventricular dyskinesia, myocarditis, myocardial strain, coronary atherosclerotic heart disease, ischemic cardiomyopathy, dilated cardiomyopathy, pericardial effusion Screening and diagnosis of pulmonary embolism, sleep apnea syndrome, etc.

Description of drawings

Fig. 1 is the structural representation of the male model of the present invention;

Fig. 2 is the structural representation of the female model of the present invention;

Fig. 3 is the electrical principle block diagram one of the present invention;

Fig. 4 is the electrical principle block diagram two of the present invention;

Figure 5 is the architecture diagram of the CorPace cloud platform;

Fig. 6 is the control flow chart of the present invention in the offline state of the cloud platform;

FIG. 7 is a control flow chart of the present invention in the online state of the cloud platform.

In the picture: 1-Micro embedded control center, 2-Flexible energy storage, 3-ECG patch, 4-Defibrillation electrode patch, 5-Chest pad.

Detailed ways

In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings.

As shown in Figures 1-5, the new wearable ECG dynamic full-true mapping intelligent defibrillator disclosed by the present invention is a piece of clothing with real-time ECG monitoring function and automatic emergency defibrillation function when necessary, specifically ventilation Sex underwear, its weight is only 350g, and the comfort is better. There are unloadable ECG patches 3, defibrillation electrode patches 4, flexible energy storage 2 and micro-embedded control center 1 (ie product logo style), etc. The flexible energy storage 2 can be a flexible water battery or Flexible supercapacitors.

The ECG patch 3 has a built-in ECG sensor, including a digital 50Hz wave trap. The ECG patch 3 and its connecting wires are provided with a shielding layer. There are 10 ECG patches 3 and 10 ECG patches 3. The arrangement is as follows: 5 on the left chest, 1 on the right chest, two on the abdomen, and two between the collar and the chest; there are two defibrillation electrode patches 4, one of which is a defibrillation electrode patch The patch 4 is located in the lower left chest and just below the five ECG patches 3 on the left chest, and another defibrillation electrode patch 4 is located in the upper right chest.

All the above-mentioned patches and clothing have good self-cleaning and self-adaptability, which can make the surface pollutants or dust particles fall off naturally under the action of gravity or be removed by photocatalytic degradation, and can also reduce the incidence of skin inflammation and improve the patient experience. The ECG patch is equipped with an ECG signal acquisition sensor, and the local micro embedded controller is equipped with a new energy micro water-based flexible battery with ultra-long battery life, high safety and flash charging performance.

The wearable ECG dynamic full-true mapping intelligent defibrillator is divided into women's and men's models. The women's model has chest pads 5. Various sizes, colors and styles are available for patients to choose from. The material is mainly a flexible textile material with ductility, conformability, self-cleaning, high air permeability, light and thin insulation, and its strong compliance can make the clothes fit closely with the skin.

The ECG monitoring block of the wearable ECG dynamic full-true mapping intelligent defibrillator includes 10 ECG patches, a miniature embedded control center, and a water-based nickel-zinc battery. The ECG patch has a built-in ECG sensor, which can realize long-term, continuous and real-time recording of ECG signals in 12 leads; a digital 50Hz notch filter is used to filter out power frequency interference, and there is a shielding device on the lead line to shield the interference signal. The shielding layer has a strong anti-interference ability, so that the ECG collection is not affected by the patient's activity, and the ECG information of each lead of the patient can be accurately collected even if the patient is exercising vigorously. The miniature embedded control center consists of ADS1292 integrated chip, Cortex-M0 LPC1114 processor, Flash Memory memory chip and Bluetooth transmission module to form a local control center, which can realize front-end processing of ECG signals, data storage, offline analysis, and short-term Distance transmission (transmission to mobile terminal).

Specifically, it includes the following modules:

1. ECG acquisition module: The ECG collector includes 10 ECG patches and a micro-embedded control center, which realizes long-term and continuous monitoring of 12-lead ECG activity, and can be used for cardiovascular diseases and sleep apnea. Syndrome and other diseases diagnosis, prognosis evaluation and prevention and treatment of complications. The ECG patch has a built-in ECG sensor, and a digital 50Hz notch filter is used to filter out power frequency interference. The patch and lead are provided with an interference signal shielding layer, so that the ECG collection is not affected by external signals and activities of the subject. , even with strenuous exercise, the ECG information of each lead of the patient can be accurately collected. The miniature embedded control center consists of ADS1292 integrated chip, Cortex-M0 LPC1114 processor, Flash Memory memory chip and Bluetooth transmission module to form a local control center, which can realize front-end processing of ECG signals, data storage, offline analysis, and short-term distance transmission.

2. Electric shock defibrillation module: The electric shock defibrillation module is controlled by the micro-embedded control center and the cloud platform; and when there is a network abnormality, the electric shock and defibrillation module is controlled by the offline local micro-embedded control center. In addition, the new wearable ECG dynamic full-true mapping intelligent defibrillator adopts 6 protective measures, which greatly reduces the false discharge rate and leakage discharge rate. When it is recognized that the ECG signal is abnormal, the local control center will immediately detect whether the R wave exists as one of the defibrillation conditions. At the same time, the electrode patch on the projection position of the apex body can sense whether the heart is beating or not, as the second defibrillation condition. In addition to this, the ECG patch will monitor the patient for the presence of normal breathing as the third defibrillation condition. When multiple conditions are matched, the local control center will issue a command to prepare for defibrillation. If the local control center can connect to the network, it will quickly summarize the identified information and send it to the CorPace cloud platform, and the cloud will also issue defibrillation preparation instructions after judging the patient's condition. The defibrillator will only work if both commands are met. When the defibrillation is started, there is a 25s buffer time. During this period, if the patient's condition improves, the cancel button can be pressed to terminate the defibrillation.

3. Power supply module: The power supply system adopts nickel-zinc primary battery, the positive electrode material is nickel hydroxide active material supported by foam nickel (10x 10x 0.04cm), the negative electrode is foam copper electrodeposited zinc (10x 10x 0.1cm), and the electrolyte is 6M KOH, the diaphragm adopts non-woven diaphragm. The size of the whole battery is 10x 10cm and the thickness is 3mm. The monitoring system has the characteristics of long working time and low power, so it must have sufficient safety and energy storage. In view of these two characteristics, the water-based nickel-zinc battery is selected, which has the characteristics of short charging time and long battery life.

4. Dual-mode positioning system: built-in BeiDou navigation and positioning module, real-time connection with China's BeiDou Navigation Satellite System (BDS), accurate positioning, providing users with safe and effective protection, so as to rescue in time in an emergency and protect life. convoy. Built-in UM220 dual-mode positioning chip, with positioning accuracy within 10 meters, and can receive Beidou/GPS satellite positioning data.

5. Cloud platform: The cloud platform builds a composite platform of BIM+3DGIS+CIM technology. The application layer is the cloud storage data service center for data storage on the cloud platform. Provide support services and protection services for class analysis and data integration. It can intelligently identify the transmitted ECG signal, and use computer vision and natural language processing technology to combine with other clinical data of the patient, give timely feedback and reports after comprehensive analysis and processing, and carry out accurate diagnosis of the patient. CorPace cloud platform can treat asymptomatic (occult) coronary heart disease, atrial fibrillation, sinus arrhythmia, supraventricular tachycardia, ventricular tachycardia, atrioventricular block, sick sinus syndrome, tip Torsional ventricular tachycardia, pre-excitation syndrome, atrioventricular incoordination, myocarditis, myocardial strain, coronary atherosclerotic heart disease, ischemic cardiomyopathy, dilated cardiomyopathy, pericardial effusion, pulmonary embolism , Screening and diagnosis of sleep apnea syndrome, etc.

As shown in FIG. 6 and FIG. 7 , the present invention also discloses a control method suitable for the wearable ECG dynamic full-true mapping intelligent defibrillator, including the following six protective measures for defibrillation:

The first track: Identify specific waveforms for accurate diagnosis. After obtaining the patient's ECG information, the cloud will combine the patient's previous basic ECG information and cloud big data to perform deep learning to make an accurate diagnosis of ventricular fibrillation. Specific waveform identification method and ventricular fibrillation judgment method:

1. Fixed algorithm: First, identify the specific R wave, the specific method is as follows:

1. Identify the highest point of voltage/amplitude for each lead;

2. Calculate the height difference between the highest points of the waveform and the horizontal distance between the highest points of each lead;

3. If the height difference between the highest points between leads exceeds 0.05 mV, it is judged as a non-ventricular fibrillation waveform;

4. If there is no height difference between the highest points of any leads exceeding 0.05 mV, it is judged as ventricular fibrillation waveform.

2. Non-fixed algorithm: Deep learning of 200,000 ECGs that correctly standardize ECG diagnosis, and obtain key models related to ventricular fibrillation. ECGs studied include: normal ECG, atrial tachycardia, ventricular fibrillation (ventricular fibrillation), sinus arrhythmia, atrial tachycardia, atrial fibrillation, junctional tachycardia, pre-excitation syndrome, atrioventricular conduction block, intraventricular conduction block, pacemaker rhythm, etc. And each category of ECG is not less than 10,000.

The second channel: the dual center sends defibrillation commands. When the cloud platform is online, its control right is higher than that of the micro-embedded control center. When a patient is identified as having ventricular fibrillation, the cloud platform will send defibrillation instructions to the defibrillation module through the mobile terminal and the embedded control center in turn for defibrillation. . When the mobile terminal or cloud platform is offline, the embedded control center will make judgments based on R wave and ventricular fibrillation rhythm. When R wave and ventricular fibrillation are identified, it will directly send a defibrillation command to the defibrillation module for defibrillation.

The third way: dual-sensing auxiliary judgment. In addition to relying on the patch to collect ECG signals to diagnose ventricular fibrillation, we will additionally add a respiration sensor and an apical beat sensor to determine the patient's breathing and heartbeat status.

The fourth course: Defibrillation electrode shedding identification and early warning. For effective defibrillation, the electrode pads need to be in close contact with the body surface skin. When the electrode pads fall off, the built-in sensor will recognize and upload an alarm, and the defibrillation will not be performed until it is effectively fitted again.

The fifth track: identification of exogenous bioelectrical signals. During defibrillation, it is forbidden for bystanders to touch the patient, or it will cause electrical damage to others, and at the same time, it cannot be defibrillated effectively. The Corpace heart rhythm can identify the exogenous bioelectrical signal. When the exogenous bioelectrical signal exists, the defibrillation module will give a light and voice alarm to remind others not to touch the patient, and the defibrillation will be performed.

The sixth channel: delayed discharge, patient self-control. When the defibrillation command is issued, the defibrillation module will give a 25-second light and sound alarm to remind you that defibrillation is about to be done. If the patient is conscious, the patient can turn off the defibrillation command through the manual switch. When it is not turned off after 25 seconds, the defibrillation module will consider the patient to be unconscious and perform discharge defibrillation.

Of course, the present invention can also have other various embodiments, without departing from the spirit and essence of the present invention, those skilled in the art can make various corresponding changes and deformations according to the present invention, but these corresponding changes and deformation should belong to the protection scope of the appended claims of the present invention.

Claims (10)

1. Wearable ECG dynamic full-true mapping intelligent defibrillator, characterized in that: comprising clothing and detachable ECG patches, defibrillation electrode patches, flexible energy storage, micro-embedded on the clothing The ECG patch and the defibrillation electrode patch are connected to the micro-embedded control center; the flexible energy storage powers the micro-embedded control center, the defibrillation electrode patch, and the micro-embedded control center, Flexible energy storage includes flexible aqueous batteries and/or flexible supercapacitors. 2. The wearable ECG dynamic full-true mapping intelligent defibrillator according to claim 1, wherein the ECG patch has a built-in ECG sensor, comprising a digital 50Hz trap, and the ECG patch There are shielding layers on its connecting wires, there are 10 ECG patches, and the 10 ECG patches are arranged as follows: 5 on the left chest, 1 on the right chest, 2 on the abdomen, There are two between the collar and the chest; there are two defibrillation electrode patches, one of which is located in the lower part of the left chest and just below the 5 ECG patches on the left chest, and the other defibrillation electrode patch The electrode patch is located on the upper right chest. 3 . The wearable ECG dynamic full-true mapping intelligent defibrillator according to claim 1 , wherein the micro-embedded control center comprises a Beidou GPS dual-mode positioning system. 4 . 4. The wearable electrocardiographic dynamic full-true mapping intelligent defibrillator according to claim 1, wherein the flexible water-based battery is a nickel-zinc primary battery, and the positive electrode of the nickel-zinc primary battery is a nickel-foam load The nickel hydroxide active material, the size of the positive electrode is 10×10×0.04cm, the negative electrode of the nickel-zinc primary battery is foamed copper electrodeposited zinc, the size of the negative electrode is 10×10×0.1cm, the electrolyte is 6M KOH, and the separator is Non-woven separator, nickel-zinc primary battery size is 10x10x 0.3cm. 5. wearable electrocardiographic dynamic full-true mapping intelligent defibrillator according to claim 1, is characterized in that: described miniature embedded control center comprises ADS1292 integrated chip, Cortex-M0 LPC1114 processor, Flash Memory memory chip and Bluetooth transmission module. 6 . The wearable ECG dynamic full-truth mapping intelligent defibrillator according to claim 1 , wherein the clothes are women's or men's, and the women's model is provided with a chest pad. 7 . 7. The wearable electrocardiographic dynamic full-true mapping intelligent defibrillator according to any one of claims 1-6, characterized in that: it also includes a cloud platform and a mobile terminal, and the cloud platform is BIM+3DGIS+CIM A composite platform of technology, the cloud platform is wirelessly connected with the mobile terminal, and the mobile terminal is wirelessly connected with the micro-embedded control center. 8. The wearable electrocardiographic dynamic full-true mapping intelligent defibrillator according to claim 7, wherein the cloud platform is a corPace cloud platform, and the corPace cloud platform comprises a business application layer, a basic support layer and a The data layer, the business application layer and the basic support layer share log records and authority control, and the business application layer, the basic support layer and the data layer share transaction management, hierarchical management and database management; The business application layer includes functional services, an operation and maintenance management platform and a terminal view analyzer, and the functional services include comprehensive data analysis, online diagnosis and defibrillation; The basic support layer includes an ECG classifier based on deep learning; The data layer includes the MySQ database. 9. The control method applicable to the wearable electrocardiographic dynamic full-true mapping intelligent defibrillator as claimed in claim 8, characterized in that: comprising six protective measures, the six protective measures comprising: The first step is to identify specific waveforms and make accurate diagnosis. After obtaining the patient's ECG information, the cloud will combine the patient's previous basic ECG information and cloud big data to perform deep learning to make an accurate diagnosis of ventricular fibrillation. ; The second channel, dual centers send defibrillation commands. When the cloud platform is online, its control right is higher than that of the micro-embedded control center. When it is identified that the patient has ventricular fibrillation, the cloud platform sends defibrillation commands through the mobile terminal, embedded The embedded control center reaches the defibrillation module for defibrillation; when the mobile terminal or cloud platform is offline, the embedded control center judges according to the R wave and ventricular fibrillation rhythm, and directly sends the defibrillation when the R wave and ventricular fibrillation are identified. Command to the defibrillation module for defibrillation; The third channel, dual-sensing auxiliary judgment, judges the patient's breathing and heartbeat status through the additional breathing sensor and apical pulse sensor; The fourth channel, the recognition and early warning of defibrillation pads falling off, when the defibrillation pads fall off, the built-in sensor of the defibrillation pads will identify and upload an alarm, and no defibrillation will be performed; The fifth channel: Recognition of exogenous bioelectrical signals, identifying exogenous bioelectrical signals through the Corpace heart rhythm, when the exogenous bioelectrical signals exist, the defibrillation module will give a light and voice alarm to remind others not to touch the patient, and will carry out defibrillation; The sixth channel: Delayed discharge, patient self-control, when the defibrillation command is issued, the defibrillation module will give a 25-second light and sound alarm to remind the patient that defibrillation is about to be performed, and the patient can turn off the defibrillation command through the manual switch. After it is not turned off, the defibrillation module performs discharge defibrillation. 10. The control method according to claim 9, wherein the method for identifying a specific waveform comprises the following steps: Step 1. Identify the highest point of voltage/amplitude for each lead; Step 2. Calculate the height difference between the highest points of the waveform and the horizontal distance between the highest points of each lead; Step 3. If there is a height difference between the highest points between leads exceeding 0.05 mV, it is judged as a non-ventricular fibrillation waveform; if there is no height difference between the highest points between any leads exceeding 0.05 mV, it is judged as a ventricular fibrillation waveform; The deep learning uses 200,000 ECGs that correctly standardize ECG diagnosis to obtain key models related to ventricular fibrillation. The ECG includes the following categories: normal ECG, atrial tachycardia, ventricular fibrillation, sinus arrhythmia, Atrial tachycardia, atrial fibrillation, junctional tachycardia, pre-excitation syndrome, atrioventricular block, intraventricular block, pacemaker rhythm, and no less than 10,000 electrocardiograms of each category.

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