Dynamic arrhythmia early warning system and method based on wearable device

Abstract

The invention relates to the field of heart rate and heart rhythm real-time monitoring methods, in particular to a dynamic arrhythmia early warning system and method based on wearable equipment, and the method comprises the steps: 1, actually measuring an electrocardiogram of a user target in real time through the wearable equipment; step 2, the wearable device receives an active positioning signal in the medical place in real time, generates a movement track of a user target, and judges whether internal interference factors in the medical place exist on the movement track or not; 3, when the internal interference factors exist, interference marking is conducted on the electrocardiogram through the wearable device, and when the internal interference factors do not exist, abnormity judgment is conducted on the electrocardiogram through the wearable device, and early warning information is sent to the background when it is judged that the electrocardiogram is abnormal; the system comprises wearable equipment for monitoring an electrocardiogram and a background for wirelessly receiving the electrocardiogram, the wearable device collects the electrocardiogram of the target user in real time, and carries out early warning according to the early warning method. According to the invention, the interference condition in the activity process can be accurately identified.

Description

Technical Field

[0001] The present invention relates to the field of real-time monitoring methods for heart rate and heart rhythm, and in particular to a dynamic arrhythmia early warning system and method based on wearable devices. Background Art

[0002] Arrhythmia refers to abnormalities in the origin, frequency, rhythm, conduction velocity and activation order of cardiac impulses. Arrhythmia is the most complex cardiovascular disease, with large variations, wide range and many types. Diagnosis mainly relies on electrocardiogram or dynamic electrocardiogram. Therefore, monitoring of arrhythmia is very important.

[0003] In current medical activities, arrhythmia monitoring methods include Holter (24-hour dynamic electrocardiogram) monitoring, event recorders, implantable recorders and wearable devices. Among them, wearable devices are the most flexible and convenient, especially suitable for use in environments where the medical process allows patients to move freely but there is a need for arrhythmia monitoring. Wearable devices monitor patients' medical parameters in real time, and store them first and then read them or send them wirelessly so that medical staff in the background can check and judge them. Wearable devices are used in various forms, such as bracelets, clothes, etc.

[0004] However, wearable devices may be interfered by the external environment during the patient's free activities. The external environment includes indoor and outdoor environments other than the ward. If the positioning function is simply added, the indoor positioning signal will be weak, resulting in inaccurate positioning and inability to accurately judge the interference during the monitoring process. In addition, when the wearable device detects abnormal heart rhythm, it cannot promptly issue an early warning to the background, resulting in some patients being unable to receive timely treatment. Summary of the invention

[0005] One of the purposes of the present invention is to provide a dynamic arrhythmia warning method based on a wearable device to solve the problem of inaccurate environmental interference identification caused by the inability to accurately locate the existing wearable devices during use.

[0006] The dynamic arrhythmia warning method based on wearable devices in this scheme includes the following steps:

[0007] Step 1: Use a wearable device to measure the user's electrocardiogram in real time;

[0008] Also includes the steps:

[0009] Step 2: The wearable device receives active positioning signals in the medical place in real time, generates an activity trajectory of the user target, and determines whether there are internal interference factors in the medical place on the activity trajectory;

[0010] Step 3, when there are internal interference factors, the wearable device will mark the interference on the electrocardiogram. When there are no internal interference factors, the wearable device will judge the electrocardiogram as abnormal and send an early warning message to the background when the electrocardiogram is judged to be abnormal.

[0011] The beneficial effects of this program are:

[0012] During use, active positioning signals are used to determine the target user's activity trajectory in medical places such as hospitals, and internal interference factors on the activity trajectory are judged. If internal interference factors are judged, the real-time monitored electrocardiogram will be marked on the wearable device, and abnormalities on the electrocardiogram will be warned when internal interference factors are not marked. Interference situations during use in accurately positioned indoor environments can be discovered in a timely manner, so as to facilitate the subsequent elimination of misjudgment of electrocardiogram abnormalities caused by external interference.

[0013] Furthermore, in step 2, the wearable device receives in real time active positioning signals sent from different locations of the same floor marker of the medical site, and sets the transmission distance of the active positioning signal of each location with interference to be less than a threshold.

[0014] The beneficial effects are: signals are transmitted at multiple locations on the same floor to distinguish different interference sources, and the transmission distance of the active positioning signal for the location with interference is set to be smaller, which can distinguish each signal, locate each close-range location in the room more accurately, make the interfering signal more obvious, and prevent mutual interference between each signal.

[0015] Furthermore, in step 2, the transmission distance is set from small to large in the order of the interference degree, and the transmission direction of the active positioning signal is set in a directionally preset range in the order of the interference degree.

[0016] The beneficial effect is: the distance and transmission direction of active positioning signals with different interference levels are set, the interference range of equipment at some interference locations is accurately limited, and various interference factors in a small range are prevented from interfering with each other and being unable to be distinguished.

[0017] Further, in step 2, it is first determined whether it is an active positioning signal for leaving the medical place. When the wearable device receives the active positioning signal for leaving the medical place, the wearable device performs GPS real-time positioning, and determines the activity direction of the target user according to the real-time positioning. When GPS real-time positioning cannot be completed, the wearable device determines the target place according to the activity direction, and determines the external interference factors in the target place;

[0018] In step 3, when it is determined that the target location has external interference factors, an interference mark is made on the electrocardiogram.

[0019] The beneficial effect is: after leaving the medical facility, when you may enter the indoor environment of a shopping mall, bank, printing shop, etc., the activity direction is determined by real-time positioning during this activity. According to the positioning direction, when the positioning signal is weak, the target location is inferred, and it is determined whether there are external interference factors in the target location. If so, it is marked on the electrocardiogram, which can timely monitor different interference situations during heart rhythm monitoring using wearable devices in scenarios other than medical facilities.

[0020] Furthermore, in step 3, when there are no external or internal interference factors, the background obtains real-time voice information by sending a voice collection signal to the wearable device, and identifies mobile phone usage keywords in the real-time voice information. When the mobile phone usage keywords are identified, a mobile phone interference tag is added to the electrocardiogram.

[0021] The beneficial effects are: monitoring the use of mobile phones can eliminate the interference of mobile phone signals on electrocardiogram monitoring; at the same time, different interferences are monitored and judged separately in different situations and conditions, avoiding the increase in equipment complexity caused by the judgment conditions required by wearable devices being too high and too complicated, reducing the setting requirements of wearable devices, and judging various interference situations separately to improve the accuracy of judgment.

[0022] Furthermore, in step 3, when the mobile phone usage keyword is continuously identified, a timing is performed, and it is determined whether the timing duration is greater than the set value. If not, it is determined that the mobile phone of the user next to it is being used, and no mobile phone interference tag is added.

[0023] The beneficial effect is that it can eliminate the relatively minor interference to the use of mobile phones caused by short-term contact with nearby users and avoid the interference tags from being added by mistake.

[0024] Furthermore, in step 1, multimodal parameters of blood pressure, respiration and psychological state are simultaneously monitored by a wearable device, and the multimodal parameters are sent to the background.

[0025] The beneficial effects are: monitoring of multi-modal parameters improves the integrity of monitoring results.

[0026] Furthermore, in step 3, when the background receives the warning information, it is determined in real time whether there is any abnormality in the multimodal parameters.

[0027] The beneficial effect is that the multimodal parameters are judged only after receiving the warning message, and the physical condition of the target user can be judged by combining multiple parameters.

[0028] A second object of the present invention is to provide a dynamic arrhythmia warning system based on a wearable device, which monitors the interference of the wearable device during the use of monitoring heart rhythm to prevent electrocardiogram abnormalities caused by interference from being misjudged as arrhythmia.

[0029] A dynamic arrhythmia warning system based on wearable devices, including a wearable device that monitors an electrocardiogram and automatically identifies an abnormal electrocardiogram and a background for wirelessly receiving the electrocardiogram. The wearable device sends the electrocardiogram to the background when an abnormal electrocardiogram is identified and reaches an alarm threshold;

[0030] The wearable device collects the electrocardiogram of the target user in real time and issues an early warning according to the above-mentioned early warning method.

[0031] Furthermore, the wearable device includes a wearable electrocardiograph clothing and / or a wristband. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 The present invention is a flowchart of a dynamic arrhythmia warning method based on a wearable device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0033] The following is further explained in detail through specific implementation methods.

[0034] Example

[0035] The dynamic arrhythmia warning system based on wearable devices includes a wearable device that monitors the electrocardiogram and automatically identifies electrocardiogram abnormalities and a background that wirelessly receives the electrocardiogram. When the wearable device identifies an electrocardiogram abnormality and reaches the alarm threshold, it sends the electrocardiogram to the background, and can identify the heart rate and rhythm from the electrocardiogram. The alarm threshold is set according to the actual medical monitoring needs; the wearable device collects the electrocardiogram of the target user in real time, and issues an early warning according to the judgment process of the following early warning method. The early warning method can be set to sound warning or light warning according to actual needs, and dynamic changes in sound or light can be set during the early warning, such as different decibels of sound, different sound types, etc., different brightness of light, different intervals of flashing, etc. In addition to collecting electrocardiograms, wearable devices also collect multimodal parameters of blood pressure, respiration, and psychological state. Wearable devices collect different parameters by setting different monitoring sensors, such as some sensor devices related to electrocardiogram, blood pressure, and respiratory rate. Wearable devices are also equipped with microprocessors for data analysis for early warning. The background can be a computer server, mobile terminal, etc. in medical places such as hospitals, and has a processor function. The wireless communication between the wearable device and the background can be WiFi, Bluetooth, Internet, etc., according to the actual construction requirements. Wearable devices include wearable electrocardiogram clothes and / or bracelets. Wearable devices are set in different sizes according to the size of the human body, such as small, medium, large, and extra large, so that different people can put on and take off easily.

[0036] Dynamic arrhythmia warning methods based on wearable devices, such as Figure 1 As shown, the steps include:

[0037] Step 1: measure the electrocardiogram of the user target in real time through a wearable device, for example, by using a corresponding sensor device set on the wearable device to measure the electrocardiogram.

[0038] In step 1, multimodal parameters of blood pressure, respiration and psychological state are simultaneously monitored by a wearable device, and the multimodal parameters are sent to the background. The monitoring of multimodal parameters is performed through different sensors, and the specific multimodal parameters can be adaptively changed and set according to the needs of actual applications.

[0039] Step 2: The wearable device receives the active positioning signal in the medical place in real time and generates the activity trajectory of the user target. The activity trajectory is formed by the position points represented by the received active positioning signal. It is judged whether there are internal interference factors in the medical place on the activity trajectory. The internal interference factors on the activity trajectory are judged according to the position represented by the corresponding active positioning signal. The active positioning signal is sent through a directional signal transmitter.

[0040] In step 2, the wearable device receives active positioning signals sent from different locations of the same floor of the medical site in real time, and sets the transmission distance of the active positioning signal of each location with interference to be less than the threshold. Locations with interference include water rooms with microwave ovens, printers at nurse stations, radiology departments of hospitals, etc. The threshold is set according to the relevant width dimensions of the building in the actual scenario. For example, the threshold is set to 1.5m in the case of a wider floor corridor, and the threshold is set to 0.5m in the case of a narrower floor corridor. Medical places such as hospitals set multiple signal transmitters on each floor, and the transmission distances of active positioning signals of signal transmitters at different locations are different.

[0041] In step 2, the transmission distance is set from small to large in the order of the interference degree, and the transmission direction of the active positioning signal is set in a preset range in the order of the interference degree. The preset range is the angle range where the interference may affect the wearable device. For example, the preset range of the interference area in front of the microwave oven is 90°, 180°, etc., and the preset range of the interference area in front of the printer due to the placement position is 90°, etc. The interference degree of the microwave oven is less than that of the printer, and the interference degree of the printer is less than that of the radiology inspection equipment. For example, the transmission distances at the microwave oven, the printer, and the radiology equipment are 1m, 0.8m, and 0.5m respectively. Because the greater the ionizing radiation interference, the better the protection, so the transmission distance is set relatively small.

[0042] In step 2, first determine whether it is an active positioning signal for leaving the medical place. When the wearable device receives the active positioning signal for leaving the medical place, the wearable device performs GPS real-time positioning, and determines the activity direction of the target user based on the real-time positioning. The activity direction is determined based on the sequence of the GPS real-time positioning positions, and the activity direction always points to the positioning position that comes later. When GPS real-time positioning cannot be completed, for example, when entering a building in a certain place and causing the positioning signal to be weak, the wearable device determines the target place based on the activity direction, and determines the external interference factors in the target place. For example, if the activity direction points to a shopping mall, it is determined whether there are external interference factors in the shopping mall, such as interference factors such as a large number of electrical appliances in the shopping mall.

[0043] Step 3: When there are internal interference factors, the wearable device will mark the interference on the electrocardiogram. When there are no internal interference factors, the wearable device will judge the electrocardiogram for abnormality and send an early warning message to the background when the electrocardiogram is judged to be abnormal. The early warning message sent to the background can be a signal, a text message, or a sound message. The abnormal judgment of the electrocardiogram is based on the fluctuation of the graph and other performances.

[0044] When marking interference on an electrocardiogram, it can be marked by additional range identification symbols, such as using curly brackets and square brackets to represent the range of data that may be interfered with; or using colors to mark the curves or images on the electrocardiogram.

[0045] In step 3, when the background receives the warning information, it is determined in real time whether the multimodal parameters are abnormal, and the processor in the background performs corresponding data analysis and judgment. The analysis and judgment of whether the multimodal parameters are abnormal can be obtained by setting the normal value range for comparison. The specific normal value range of each parameter is set according to the regulations in medicine, and an early warning is issued when the multimodal parameters are abnormal. By checking the multimodal parameters and judging whether the multimodal parameters are abnormal when the background receives the warning, abnormal judgment can be made from many aspects, improving the accuracy and comprehensiveness of the judgment results.

[0046] In step 3, when it is determined that the target location has external interference factors, an interference mark is made on the electrocardiogram, and if there are no external interference factors, no mark is made.

[0047] In step 3, when there are no external or internal interference factors, the background obtains real-time voice information by sending a voice collection signal to the wearable device, and identifies the mobile phone usage keywords in the real-time voice information. The recognition of keywords is performed through existing recognition algorithms, such as recognizing phone calls, videos, or some terms in telephone calls, etc., such as "Hello, hello, is this Mr. A?" When the mobile phone usage keyword is recognized, a mobile phone interference label is added to the electrocardiogram. If the mobile phone usage keyword is not recognized, no label is added.

[0048] In step 3, when the mobile phone usage keyword is continuously recognized, timing is performed and it is determined whether the timing duration is greater than the set value. The set value can be set to 5s. If the timing duration is less than the set value, it is determined that the mobile phone of the user next to you is being used, and no mobile phone interference tag is added. If the timing duration is greater than the set value, it means that the person is using the mobile phone, and a mobile phone interference tag is added.

[0049] The solution of this embodiment measures multimodal parameters such as electrocardiogram, blood pressure, and respiration through wearable devices, so as to timely monitor the physical condition of the patient as the target user; and accurately monitors different types of interference conditions in the room during dynamic monitoring of the electrocardiogram, so as to detect in real time the interference conditions that cause electrocardiogram abnormalities during the dynamic monitoring process, and prevent the misjudgment of the user's physical condition based on the electrocardiogram; and after multimodal parameter monitoring, further data analysis and judgment are performed when receiving the early warning from the wearable device to accurately judge the user's status, without the need to judge a large amount of multi-type data at the same time, and the data processing speed is fast, which reduces the design requirements for wearable devices and increases the scope of application of wearable devices.

[0050] In another embodiment, in step 2, it is first determined whether it is an active positioning signal for leaving the medical place. The determination of the active positioning signal for leaving the medical place can be determined by the position represented by the signal, for example, the position of the signal represents an exit, a lobby or a door, etc. When the wearable device receives the active positioning signal for leaving the medical place, the wearable device detects the real-time temperature value and walking speed around the target user. The real-time temperature can be detected by a temperature sensor, and the walking speed can be detected by an existing Hall sensor. According to the specific size, model, temperature value and walking speed of the wearable device, it is determined whether the electrode sheet for electrocardiogram detection has a probability of falling off. When the probability is greater than a predetermined value, it is determined that the activity of the target user will affect the electrocardiogram. The predetermined value is set to 80%. The wearable device is used to determine whether the electrocardiogram is abnormal. If the electrocardiogram is abnormal, it is marked on the electrocardiogram. If the electrocardiogram is normal, it is not marked. When the probability is less than the predetermined value, it is determined that the activity of the target user has no effect on the electrocardiogram.

[0051] When judging the probability of electrode sheet falling off, the wearable device is first used to judge whether the real-time temperature value is greater than or equal to the first set temperature and less than the second set temperature. The first set temperature and the second set temperature are set according to the heat conditions caused by the actual regional temperature conditions. For example, in a city with a greater sense of heat, the first set temperature is 35°C and the second set temperature is 37°C. When the real-time temperature value is greater than or equal to the first set temperature and less than the second set temperature, the user may sweat. Then, it is judged whether the wearable device is plus-sized and the walking speed is greater than the set speed. If the wearable device is plus-sized and the walking speed is greater than the set speed, The speed is set, then the probability of the electrode sheet falling off is judged to be 81%-85%. The set speed is set according to the walking speed that causes sweating under the temperature of the area; when the real-time temperature value is greater than or equal to the second set temperature, it is judged whether the model of the wearable device is large and the walking speed is greater than the set speed. If the model of the wearable device is large and the walking speed is greater than the set speed, the probability of the electrode sheet falling off is judged to be 85%-90%; if the real-time temperature value is greater than or equal to the second set temperature, and the model of the wearable device is large, then the probability of the electrode sheet falling off is judged to be more than 90%, and the probability is judged to be less than 80% in other cases. Further, according to the model of the wearable device and whether there is a faster walking speed, the accuracy of sweating judgment is increased, and the faster the walking speed, the greater the possibility of knocking off the electrode sheet. The specific value can also be set to other according to actual needs.

[0052] Since the user's activities in the medical facilities of the hospital are relatively close activities, they may be carried out under the condition that the physical condition is not very good, and the medical facilities are mostly flat roads, the amplitude and frequency of the activities are relatively small, while in other places outside the medical facilities, the road surface may have slopes, or because the patient's physical condition will be much better, and the patient's body shape affects sweating, the patient's activity amplitude and frequency will be much larger. Therefore, this embodiment determines whether the user's activities will cause the electrode sheet to fall off through the judgment of the real-time temperature value and walking speed, and then judges the abnormality of the electrocardiogram and makes corresponding indications to avoid the electrocardiogram abnormality caused by the falling of the electrode sheet from being misjudged as the patient's physical abnormality.

[0053] When marking an abnormality on an electrocardiogram, it can be done by recording the time point when the abnormality is detected or a certain range of time information before and after the time point, such as recording the abnormal electrocardiogram at 12:26 or 11:58-12:02. It can also be marked directly by adding corresponding text, characters, symbols, colors, etc. on the horizontal axis of the electrocardiogram, such as adding triangle symbols, alphabetic characters, abnormal text, and eye-catching red marks to the electrocardiogram. The specific mark can be distinguished from the interference mark.

[0054] In another embodiment, when an active positioning signal leaves a medical setting, motion artifact elimination is performed using a preset algorithm, where the preset algorithm is an existing one, such as motion artifact elimination based on periodic element analysis, motion artifact elimination based on Savitzy-Golay and EMD, and the like.

[0055] At the same time, for the chargers and wires required for monitoring work of wearable devices, when setting them up, use a three-core AC power socket with a ground wire to ensure that the charger and wires are grounded to reduce electromagnetic interference; when charging, keep a certain distance from the charger and wires, or design a bandpass filter according to different equipment settings to filter out signals within the 50Hz or 60Hz frequency range, reduce power supply interference, try not to share power sockets, and reduce electromagnetic field interference.

[0056] Considering that the amplitude and frequency of activities after leaving the medical facility will be relatively large, the elimination of motion artifacts and the interference caused by chargers and wires required by some devices themselves can reduce the abnormalities caused by too much interference. Only the interference identifiers of external and internal interference factors are retained, preventing the installation of too many processing algorithms on wearable devices, which will cause an increase in device hardware requirements.

[0057] The above is only an embodiment of the present invention, and the common knowledge such as the known specific structure and characteristics in the scheme is not described in detail here. It should be pointed out that for those skilled in the art, several deformations and improvements can be made without departing from the structure of the present invention, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicality of the patent. The scope of protection required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to interpret the content of the claims.

Claims

1. A dynamic arrhythmia warning method based on a wearable device, comprising the steps of: Step 1: Use a wearable device to measure the user's electrocardiogram in real time; Features: Also includes the steps: Step 2: The wearable device receives active positioning signals in the medical place in real time, generates an activity trajectory of the user target, and determines whether there are internal interference factors in the medical place on the activity trajectory; Step 3, when there are internal interference factors, the wearable device will mark the interference on the electrocardiogram. When there are no internal interference factors, the wearable device will judge the electrocardiogram as abnormal and send an early warning message to the background when the electrocardiogram is judged to be abnormal.

2. The dynamic arrhythmia early warning method based on a wearable device according to claim 1, characterized in that: In step 2, the wearable device receives in real time active positioning signals sent from different locations of the same floor marker of the medical site, and sets the transmission distance of the active positioning signal of each location with interference to be less than a threshold.

3. The wearable device-based dynamic arrhythmia early warning method according to claim 2, characterized in that: In the step 2, the transmission distance is set from small to large in the order of the interference degree, and the transmission direction of the active positioning signal is set in a direction within a preset range in the order of the interference degree.

4. The wearable device-based dynamic arrhythmia early warning method according to claim 3, characterized in that: In step 2, it is first determined whether it is an active positioning signal for leaving the medical place. When the wearable device receives the active positioning signal for leaving the medical place, the wearable device performs GPS real-time positioning, and determines the activity direction of the target user based on the real-time positioning. When GPS real-time positioning cannot be completed, the wearable device determines the target place based on the activity direction and determines the external interference factors in the target place. In step 3, when it is determined that the target location has external interference factors, an interference mark is made on the electrocardiogram.

5. The dynamic arrhythmia early warning method based on a wearable device according to claim 4, characterized in that: In step 3, when there are no external or internal interference factors, the background obtains real-time voice information by sending a voice collection signal to the wearable device, and identifies mobile phone usage keywords in the real-time voice information. When the mobile phone usage keywords are identified, a mobile phone interference tag is added to the electrocardiogram.

6. The dynamic arrhythmia early warning method based on a wearable device according to claim 5, characterized in that: In step 3, when the mobile phone usage keyword is continuously identified, timing is performed and it is determined whether the timing duration is greater than the set value. If not, it is determined that the mobile phone of the user next to it is in use, and no mobile phone interference tag is added.

7. The dynamic arrhythmia early warning method based on a wearable device according to claim 1, characterized in that: In step 1, multimodal parameters of blood pressure, respiration and psychological state are simultaneously monitored by a wearable device, and the multimodal parameters are sent to the background.

8. The wearable device-based dynamic arrhythmia early warning method according to claim 7, characterized in that: In step 3, when the background receives the warning information, it is determined in real time whether there is any abnormality in the multimodal parameters.

9. A dynamic arrhythmia warning system based on wearable devices, comprising a wearable device that monitors an electrocardiogram and automatically identifies an abnormal electrocardiogram and a background for wirelessly receiving the electrocardiogram, wherein the wearable device sends the electrocardiogram to the background when an abnormal electrocardiogram is identified and reaches an alarm threshold; characterized in that: The wearable device collects the electrocardiogram of the target user in real time, and issues an early warning according to the early warning method according to any one of claims 1 to 8.

10. The wearable device-based dynamic arrhythmia warning system according to claim 9, characterized in that: The wearable device includes a wearable electrocardiograph clothing and / or a wristband.

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