Blood pressure and heart rate monitoring method and system based on smart helmet and smart helmet

Abstract

The present invention relates to the technical field of blood pressure and heart rate monitoring equipment, and in particular to a blood pressure and heart rate monitoring method and system based on a smart helmet, and a smart helmet, wherein the smart helmet comprises a helmet body and a control module, wherein the helmet body is provided with a first terminal for detecting a PPG signal and a second terminal for detecting an ECG signal, the control module is communicatively connected to the first terminal and the second terminal, and the control module is used to execute the blood pressure and heart rate monitoring method based on the smart helmet, which realizes heart rate monitoring through a PPG signal, and monitors electrocardiogram signals through an ECG signal at the same time, and realizes blood pressure monitoring in combination with the PPG signal, thereby avoiding squeezing behavior and improving comfort when monitoring blood pressure, and further evaluating the credibility of the ECG signal based on the heart rate, thereby calculating the blood pressure in combination with the credibility to improve the monitoring accuracy, and perfectly solving the problem of how to more comfortably monitor heart rate and blood pressure through wearable devices.

Description

Technical Field

[0001] The present invention relates to the technical field of blood pressure and heart rate monitoring equipment, and in particular to a blood pressure and heart rate monitoring method and system based on a smart helmet, and a smart helmet. Background Art

[0002] Wearable devices are increasingly becoming a powerful assistant in people's daily lives. These devices provide users with a convenient and real-time means of monitoring physiological indicators through their non-invasive characteristics, greatly enhancing people's understanding and control of their own health conditions. They not only improve the feasibility of disease prevention, but also improve the pertinence and efficiency of the treatment process, making health management more personalized and proactive.

[0003] The indicators that need to be monitored generally include heart rate and blood pressure. In terms of heart rate monitoring, the application of photoplethysmography (PPG) technology enables wearable devices to track heartbeats in real time through changes in light reflection from the skin surface. The advantage of this technology is that it can provide continuous heart rate data, allowing users to understand their heart health status while doing daily activities, whether they are exercising, working or resting.

[0004] However, wearable devices have difficulties in monitoring blood pressure. The commonly used blood pressure monitoring method is the Korotkoff sound method, which requires a cuff to pressurize the body. Obviously, this method requires active pressure on the human body for wearable devices, which affects the wearing comfort. Therefore, people need a more comfortable wearable device for monitoring heart rate and blood pressure. Summary of the invention

[0005] Therefore, the present invention provides a blood pressure and heart rate monitoring method and system based on a smart helmet, and a smart helmet, so as to solve the problem in the prior art of how to monitor heart rate and blood pressure more comfortably through wearable devices.

[0006] The present invention provides a blood pressure and heart rate monitoring method based on a smart helmet, which is applied to a smart helmet. The smart helmet comprises a helmet body and a control module. The helmet body is provided with a first terminal for detecting a PPG signal and a second terminal for detecting an ECG signal. The control module is communicatively connected with the first terminal and the second terminal. The control module is used to execute the blood pressure and heart rate monitoring method based on the smart helmet. The method comprises:

[0007] Obtain the PPG signal, and obtain the target heart rate based on the PPG signal;

[0008] Acquire an ECG signal, and obtain a reference heart rate according to the ECG signal;

[0009] The credibility of the ECG signal is obtained according to the deviation between the target heart rate and the reference heart rate;

[0010] The target blood pressure is obtained based on the PPG signal and ECG signal combined with the credibility.

[0011] The present invention also provides a preferred solution: according to the PPG signal and the ECG signal, combined with the credibility, the target blood pressure is obtained, including:

[0012] According to the PPG signal and ECG signal, the initial blood pressure is obtained;

[0013] Obtain baseline heart rate and baseline blood pressure;

[0014] According to the deviation between the target heart rate and the baseline heart rate, the initial blood pressure is corrected based on the baseline blood pressure and the credibility to obtain the target blood pressure;

[0015] Among them, the higher the credibility, the smaller the correction of the initial blood pressure.

[0016] The present invention also provides a preferred solution: the target blood pressure is obtained by the following formula:

[0017]

[0018] Where P is the target blood pressure, P 0 is the initial blood pressure, P b is the baseline blood pressure, R is the target heart rate, and R b is the baseline heart rate, r is the reliability, and α is the preset unit adjustment coefficient.

[0019] The present invention also provides a preferred solution: according to the PPG signal and the ECG signal, combined with the credibility, the target blood pressure is obtained, including:

[0020] Establishing a feature vector according to the PPG signal, the ECG signal and the credibility, wherein the feature vector includes a credibility feature element, and the credibility feature element is used to characterize the credibility;

[0021] The feature vector is input into a preset neural network model to obtain the target blood pressure output by the preset neural network model.

[0022] The present invention also provides a preferred solution: the preset neural network model is a recurrent neural network, the data input to the preset neural network model is a feature vector sequence composed of feature vectors, each feature vector in the feature vector sequence corresponds to a detection moment, and multiple feature vectors in the feature vector sequence are arranged in chronological order based on their corresponding detection moments, and the time span of the detection moments corresponding to the multiple feature vectors in the feature vector sequence is greater than the preset cardiac cycle; the feature vector also includes PPG numerical elements and ECG numerical elements, the PPG numerical elements in the feature vector are used to characterize the PPG detection value in the PPG signal at the detection moment corresponding to the feature vector, and the ECG numerical elements in the feature vector are used to characterize the ECG detection value in the ECG signal at the detection moment corresponding to the feature vector.

[0023] The present invention also provides a preferred solution: according to the PPG signal and the ECG signal, combined with the credibility, the target blood pressure is obtained, including:

[0024] Based on the credibility, the ECG signal is corrected to obtain a corrected ECG signal;

[0025] According to the PPG and corrected ECG signals, the target blood pressure is obtained;

[0026] The higher the reliability, the smaller the correction amplitude of the ECG signal.

[0027] The present invention also provides a blood pressure and heart rate monitoring system based on a smart helmet, which is applied to a smart helmet. The smart helmet includes a helmet body and a control module. The helmet body is provided with a first terminal for detecting a PPG signal and a second terminal for detecting an ECG signal. The control module is communicatively connected with the first terminal and the second terminal. The control module is used to run the blood pressure and heart rate monitoring system based on the smart helmet. The system includes:

[0028] A heart rate calculation module is used to obtain a PPG signal and obtain a target heart rate based on the PPG signal;

[0029] A reference calculation module, used for acquiring an ECG signal and obtaining a reference heart rate according to the ECG signal;

[0030] An error analysis module is used to obtain the credibility of the ECG signal according to the deviation between the target heart rate and the reference heart rate;

[0031] The blood pressure calculation module is used to obtain the target blood pressure based on the PPG signal and the ECG signal in combination with the credibility.

[0032] The present invention also provides a smart helmet, comprising a helmet body and a control module, wherein a first terminal for detecting a PPG signal and a second terminal for detecting an ECG signal are arranged inside the helmet body, and the control module is communicatively connected with the first terminal and the second terminal; the control module is used to:

[0033] Obtain the PPG signal, and obtain the target heart rate based on the PPG signal;

[0034] Acquire an ECG signal, and obtain a reference heart rate according to the ECG signal;

[0035] The credibility of the ECG signal is obtained according to the deviation between the target heart rate and the reference heart rate;

[0036] The target blood pressure is obtained based on the PPG signal and ECG signal combined with the credibility.

[0037] The present invention also provides a preferred solution: it also includes a pad, the pad is arranged on the inner side of the helmet body, a slide is opened in the pad, the second terminal can be movably inserted in the slide, and a drive component is also arranged on the inner side of the second terminal in the slide, the drive component includes a movable output end, and the output end is connected to the second terminal.

[0038] The present invention also provides a preferred solution: the driving component includes a push-type inflatable bag, a check valve and a driving airbag that are connected in sequence, the push-type inflatable bag is arranged on the outside of the helmet body, the check valve and the driving airbag are both arranged in the slide, the driving airbag abuts the second terminal, and a deflation valve is also arranged on the outside of the helmet body, and the deflation valve is connected to the driving airbag.

[0039] The beneficial effects of adopting the above embodiment are:

[0040] The present invention provides a blood pressure and heart rate monitoring method and system based on a smart helmet, and a smart helmet, wherein the smart helmet comprises a helmet body and a control module, wherein a first terminal for detecting a PPG signal and a second terminal for detecting an ECG signal are arranged inside the helmet body, and the control module is communicatively connected with the first terminal and the second terminal, and the control module is used to execute the blood pressure and heart rate monitoring method based on the smart helmet, wherein the method first obtains a PPG signal, and obtains a target heart rate according to the PPG signal, then obtains an ECG signal, and obtains a reference heart rate according to the ECG signal, and then obtains the credibility of the ECG signal according to the deviation between the target heart rate and the reference heart rate, and finally obtains the target blood pressure according to the PPG signal and the ECG signal in combination with the credibility. Compared with the prior art, the present invention monitors heart rate through PPG signals, monitors electrocardiogram signals through ECG signals, and monitors blood pressure in combination with PPG signals, thereby avoiding squeezing behavior such as the Korotkoff sound method and improving the comfort level when monitoring blood pressure. It is worth noting that the present invention further evaluates the credibility of the ECG signal based on the heart rate, thereby calculating the blood pressure in combination with the credibility to improve monitoring accuracy, thus perfectly solving the problem of how to more comfortably monitor heart rate and blood pressure through wearable devices. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 A method flow chart of an embodiment of a blood pressure and heart rate monitoring method based on a smart helmet provided by the present invention;

[0042] Figure 2 A system architecture diagram of an embodiment of a blood pressure and heart rate monitoring system based on a smart helmet provided by the present invention;

[0043] Figure 3 A schematic structural diagram of an embodiment of a smart helmet provided by the present invention;

[0044] Figure 4 for Figure 3 A cross-sectional view of the second terminal. DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] Combination Figure 1As shown, a specific embodiment of the present invention discloses a blood pressure and heart rate monitoring method based on a smart helmet, which is characterized in that it is applied to a smart helmet, the smart helmet includes a helmet body and a control module, the inner side of the helmet body is provided with a first terminal for detecting a PPG signal and a second terminal for detecting an ECG signal, and the control module is communicatively connected with the first terminal and the second terminal; the control module is used to execute the blood pressure and heart rate monitoring method based on the smart helmet, and the method includes:

[0047] S101, obtaining a PPG signal, and obtaining a target heart rate according to the PPG signal;

[0048] S102, acquiring an ECG signal, and obtaining a reference heart rate according to the ECG signal;

[0049] S103, obtaining the credibility of the ECG signal according to the deviation between the target heart rate and the reference heart rate;

[0050] S104. Obtain target blood pressure based on the PPG signal and ECG signal in combination with the credibility.

[0051] Compared with the prior art, the present invention monitors heart rate through PPG signals, monitors electrocardiogram signals through ECG signals, and monitors blood pressure in combination with PPG signals, thereby avoiding squeezing behavior such as the Korotkoff sound method and improving the comfort level when monitoring blood pressure. It is worth noting that the present invention further evaluates the credibility of the ECG signal based on the heart rate, thereby calculating the blood pressure in combination with the credibility to improve monitoring accuracy, thus perfectly solving the problem of how to more comfortably monitor heart rate and blood pressure through wearable devices.

[0052] In the above process, the PPG (Photo Plethysmo Graphy) signal is the detection signal of the photoplethysmogram. Photoplethysmogram detection is a non-invasive technology that works by emitting light (usually a green LED light) to the skin and measuring the amount of light reflected back. The terminal of the emitting optical fiber is the above-mentioned first terminal. These light beams are irradiated to the surface of the skin, and part of the light will be absorbed by the blood and tissues. As the heart beats, changes in arterial blood volume will cause changes in the amount of light absorbed. These changes are captured by the photodetector and converted into electrical signals, thereby forming a PPG waveform. In the PPG waveform, each peak represents a heartbeat, and the heart rate can be calculated by calculating the number of peaks within a certain period of time. In this embodiment, the target heart rate, that is, the final desired heart rate, is obtained through the ECG signal.

[0053] The ECG (electrocardiogram) signal is an electrocardiogram signal. The electrocardiogram (ECG) is a test that records the electrical activity of the heart. It captures the electrical activity emitted by the heart by placing a series of electrodes on the surface of the body. Every time the heart contracts, an electrical signal is generated, which is transmitted through the blood and surrounding tissues. ECG can capture these electrical signals and convert them into waveforms. The principle of combining ECG and PPG signals to detect blood pressure is mainly based on the concept of pulse transit time (PTT). PTT refers to the time from the wave generated by the heart pumping blood to the measurement point (usually a finger, in the present invention, the part where the human head contacts the second terminal in the smart helmet). Changes in blood pressure can affect the stiffness of blood vessels and the propagation speed of pulse waves, so blood pressure can be indirectly estimated by measuring PTT. Specifically, when the heart contracts, blood is pumped into the artery, causing the arterial wall to vibrate. This vibration propagates along the blood vessel in the form of a wave and eventually reaches the location of the PPG sensor. PTT can be measured by using the R peak in the ECG signal as the starting point and the peak in the PPG signal as the end point. Studies have shown that there is a certain correlation between PTT and blood pressure, and this relationship can be used to estimate blood pressure. The advantages of this method are that it is non-invasive and continuous, and is suitable for long-term monitoring.

[0054] In this embodiment, one of the most important advantages of measuring blood pressure in the above manner is that it can greatly improve comfort. On the one hand, when measuring ECG signals, the electrode (i.e., the second terminal) for obtaining ECG signals only needs to contact the human body, without squeezing the human body too hard, thus avoiding the discomfort caused by squeezing during Korotkoff sound detection. At the same time, for wearable devices, the design difficulty of the structure used for ECG signal detection is obviously lower than that of the structure used for Korotkoff sound detection. On the other hand, it is undeniable that although the detection of ECG signals does not require squeezing as hard as Korotkoff sound detection, it still needs to contact the human body, and generally requires multi-point detection to form multiple leads. The clever part is that the present invention is designed based on a smart helmet. For safety reasons, the smart helmet often contacts the human body over a large area, which provides an environment for multi-point detection of ECG signals. Moreover, when people wear helmets, their acceptance of fit and squeeze feelings is significantly higher than that of other wearable devices such as watches. At this time, the contact feeling generated when the second terminal fits the skin to detect ECG signals is relatively less likely to affect the comfort of the human body.

[0055] The relevant standards in the prior art stipulate that the detection position of ECG signals is generally fingers, chest, ankles, etc., to ensure the accuracy and reliability of the signals. However, in the present invention, the detection terminal of the ECG signal is set in the helmet, which will inevitably sacrifice some accuracy. Therefore, the present invention also determines the accuracy of ECG signal detection by evaluating the credibility to obtain a more accurate final blood pressure detection result.

[0056] Although ECG signals and PPG signals are different in nature, the information they contain has certain commonalities, and heart rate information is one of them. For ECG signals, the period of its R wave peak (i.e., RR interval) can also be considered as heart rate. Therefore, this embodiment uses heart rate as a bridge, regards the target heart rate detected by the PPG signal as accurate data, and uses the reference heart rate and target heart rate to calculate an evaluation value to indicate the credibility of the ECG signal. In this way, a more accurate blood pressure detection value can be obtained in combination with credibility.

[0057] Obviously, the greater the deviation between the reference heart rate and the target heart rate, the lower the credibility. Credibility can be interpreted as the accuracy of the ECG signal, and in the subsequent calculation process of the target blood pressure, credibility can also be understood as the degree of influence of the ECG signal on the final result of the target blood pressure. The specific influence method can be flexibly designed according to the specific calculation method. To give an extreme example, when the credibility is 0, it means that the ECG signal is completely inaccurate. At this time, you can choose to discard all current data and re-test. At this time, the impact of credibility on the final target blood pressure is 0.

[0058] Specifically, the influence of credibility on target blood pressure in the present invention can be reflected from the following three aspects:

[0059] 1. Correction of ECG signals;

[0060] 2. Impact on the target blood pressure calculation process;

[0061] 3. Correct the final calculated blood pressure data.

[0062] The following examples are provided to explain the above three aspects in more detail. It is understood that in practice, any one, two or all three of the above three aspects can be selected for implementation according to specific circumstances, and the present invention is not limited thereto.

[0063] Specifically, in a preferred embodiment, the above step S104, obtaining the target blood pressure according to the PPG signal and the ECG signal in combination with the credibility, specifically includes:

[0064] Based on the credibility, the ECG signal is corrected to obtain a corrected ECG signal;

[0065] According to the PPG and corrected ECG signals, the target blood pressure is obtained;

[0066] The higher the reliability, the smaller the correction amplitude of the ECG signal.

[0067] The above process is a correction of the ECG signal itself. The credibility can be used to control the correction amplitude of the ECG signal. For example, the average R value in the ECG signal is counted, and then all R values ​​are corrected to the average R value. The credibility can control the strength of the R value correction. The higher the credibility, the greater the deviation of the R value from the average R value. Similarly, credibility can be applied to the correction amplitude control of other defects such as baseline drift of ECG signals.

[0068] As can be seen from the foregoing, the PPG signal and the ECG signal can determine the blood pressure through the pulse wave propagation time PTT, and the present invention also provides a more preferred method to further consider the credibility. In a preferred embodiment, the above step S104, based on the PPG signal and the ECG signal, combined with the credibility, obtains the target blood pressure, specifically including:

[0069] Establishing a feature vector according to the PPG signal, the ECG signal and the credibility, wherein the feature vector includes a credibility feature element, and the credibility feature element is used to characterize the credibility;

[0070] The feature vector is input into a preset neural network model to obtain the target blood pressure output by the preset neural network model.

[0071] In this embodiment, the target blood pressure is calculated by a neural network. Compared with the traditional method of calculating blood pressure by relying on a fixed mathematical model, the neural network can analyze more data at the same time and learn the nonlinear relationship between the characteristics of the PPG signal and the ECG signal and the blood pressure, and thus can more deeply analyze the potential information of the PPG signal and the ECG signal to obtain a more accurate blood pressure calculation result. Most importantly, the neural network can analyze the credibility as input data, so that the calculation process is combined with the consideration of the credibility of the ECG signal. For example, the weight control in the neural network can ensure that only high-quality signals are used in the training and prediction process, thereby improving the accuracy of blood pressure calculation.

[0072] It can be understood that the feature vector input into the preset neural network model, in addition to the credibility feature elements, can also include relevant waveform features and other features extracted from the PPG signal and ECG signal, such as the user's physiological characteristics (such as age, gender, height, weight, etc.) or medical history, living habits and other characteristic parameters.

[0073] Furthermore, in a preferred embodiment, the preset neural network model is a recurrent neural network, and the data input to the preset neural network model is a feature vector sequence composed of feature vectors, each feature vector in the feature vector sequence corresponds to a detection moment, and the multiple feature vectors in the feature vector sequence are arranged in chronological order based on their corresponding detection moments, and the time span of the detection moments corresponding to the multiple feature vectors in the feature vector sequence is greater than the preset cardiac cycle; the feature vector also includes PPG numerical elements and ECG numerical elements, the PPG numerical elements in the feature vector are used to characterize the PPG detection values ​​in the PPG signal at the detection moments corresponding to the feature vector, and the ECG numerical elements in the feature vector are used to characterize the ECG detection values ​​in the ECG signal at the detection moments corresponding to the feature vector.

[0074] The recurrent neural network in the above process can be any form of neural network capable of analyzing sequential information in sequence data, such as RNN, LSTM, etc. Such a network can analyze the changes in PPG signals and ECG signals, capture the time dependence of blood pressure changes, and obtain more accurate calculation results.

[0075] On the basis of the recurrent neural network, this embodiment further improves the feature vector. Through its recursive connection characteristics, the recurrent neural network can maintain an internal state in each time step of the sequence. This state can summarize the information of the previous time step and merge it with the input of the current time step to generate the output of the current time step. The maintenance of this internal state enables the recurrent neural network to take into account the impact of historical information on the current output, so as to better understand the dynamic changes in the sequence data. Therefore, this embodiment uses the recursive characteristics of the recurrent neural network to directly use the signal values ​​of the PPG signal and the ECG signal as elements in the feature vector, eliminating the cumbersome feature extraction process for the two, and improving the operating efficiency of the method. In addition, the advantages of the recurrent neural network in processing time series data enable it to take into account the dynamic changes of the PPG and ECG signals, which is crucial for accurate estimation of blood pressure. For example, heart rate variability (HRV) is an important indicator for evaluating cardiovascular health, and RNN can capture subtle changes in HRV, thereby providing more accurate blood pressure estimates.

[0076] Further, in a preferred embodiment, the above step S104, obtaining the target blood pressure according to the PPG signal and the ECG signal in combination with the credibility, specifically includes:

[0077] According to the PPG signal and ECG signal, the initial blood pressure is obtained;

[0078] Obtain baseline heart rate and baseline blood pressure;

[0079] According to the deviation between the target heart rate and the baseline heart rate, the initial blood pressure is corrected based on the baseline blood pressure and the credibility to obtain the target blood pressure;

[0080] Among them, the higher the credibility, the smaller the correction of the initial blood pressure.

[0081] The above process is the correction of the calculation result, wherein the reference heart rate and reference blood pressure are the heart rate and blood pressure values ​​(including diastolic pressure and systolic pressure) of a person in a daily state, which can be obtained in any way in practice, such as input by the user or detected at a designated location. This embodiment takes the reference heart rate and reference blood pressure as the reference, and takes the deviation between the target heart rate and the reference heart rate as the reference, and further corrects the initial blood pressure according to the deviation between the initial blood pressure and the reference blood pressure, and controls the correction amplitude by credibility. For example, the greater the deviation between the target heart rate and the reference heart rate, the more intense the human body may be at this time, and the change of the human body's blood pressure compared to the reference blood pressure should also be greater. At this time, by comparing the deviation between the initial blood pressure and the reference blood pressure with the deviation between the target heart rate and the reference heart rate, the accuracy of the initial blood pressure can be estimated, and then correction can be made.

[0082] Specifically, in a preferred embodiment, the target blood pressure is obtained by the following formula:

[0083]

[0084] Where P is the target blood pressure, P 0 is the initial blood pressure, P b is the baseline blood pressure, R is the target heart rate, and R b is the baseline heart rate, r is the reliability, and α is the preset unit adjustment coefficient.

[0085] The significance of the above formula is to compare the change range of the target heart rate relative to the baseline heart rate, obtain a theoretical blood pressure value at this time through the baseline blood pressure, and correct the initial blood pressure to the theoretical blood pressure value, while controlling the deviation of the initial blood pressure through the credibility. The higher the credibility, the more accurate the initial blood pressure, and the smaller the deviation of the initial blood pressure to the theoretical blood pressure, and vice versa.

[0086] Combination Figure 2 As shown, the present invention also provides a blood pressure and heart rate monitoring system based on a smart helmet, which is applied to a smart helmet. The smart helmet includes a helmet body and a control module. The helmet body is provided with a first terminal for detecting a PPG signal and a second terminal for detecting an ECG signal. The control module is communicatively connected with the first terminal and the second terminal. The control module is used to run the blood pressure and heart rate monitoring system based on the smart helmet. The system includes:

[0087] A heart rate calculation module 210 is used to obtain a PPG signal and obtain a target heart rate according to the PPG signal;

[0088] A reference calculation module 220, for acquiring an ECG signal and obtaining a reference heart rate according to the ECG signal;

[0089] The error analysis module 230 is used to obtain the credibility of the ECG signal according to the deviation between the target heart rate and the reference heart rate;

[0090] The blood pressure calculation module 240 is used to obtain the target blood pressure based on the PPG signal and the ECG signal in combination with the credibility.

[0091] It should be noted here that the corresponding system provided in the above embodiments can implement the technical solutions described in the above method embodiments. The specific implementation principles of the above modules or units can be found in the corresponding contents in the above method embodiments, which will not be repeated here.

[0092] Combination Figure 3-4 As shown, the present invention also provides a smart helmet, including a helmet body 310 and a control module (not shown in the figure), wherein the helmet body 310 is provided with a first terminal 320 for detecting a PPG signal and a second terminal 330 for detecting an ECG signal, and the control module is communicatively connected with the first terminal 320 and the second terminal 330; the control module is used to:

[0093] Obtain the PPG signal, and obtain the target heart rate based on the PPG signal;

[0094] Acquire an ECG signal, and obtain a reference heart rate according to the ECG signal;

[0095] The credibility of the ECG signal is obtained according to the deviation between the target heart rate and the reference heart rate;

[0096] The target blood pressure is obtained based on the PPG signal and ECG signal combined with the credibility.

[0097] It can be understood that the specific structure of the first terminal 320 and the second terminal 330 is the existing technology that can be understood by technical personnel in this field, so it will not be explained in detail in this article. At the same time, the specific setting positions of the first terminal 320 and the second terminal 330 can be flexibly determined according to actual conditions, and are preferably designed near the ears and neck of the human head to obtain better detection effects.

[0098] The control module may be a chip with computing and storage capabilities integrated in the helmet body 310, and in the case where the computing power requirement is more stringent, it may also be a remotely connected server or other facilities. Similarly, the above structure can implement the technical solutions described in the above method embodiments, and the specific implementation principles of the above structures can refer to the corresponding contents in the above method embodiments, which will not be repeated here.

[0099] Furthermore, in a preferred embodiment, the smart helmet also includes a pad 340, which is arranged on the inner side of the helmet body 310, and a slide is opened in the pad 340, and the second terminal 330 can be movably inserted in the slide. A driving component 350 is also arranged on the inner side of the second terminal 330 in the slide, and the driving component 350 includes a movable output end, and the output end is connected to the second terminal 330.

[0100] On the one hand, in this embodiment, the second terminal 330 is disposed in the liner 340, and the wrapping property of the liner 340 is used to improve the comfort of the human body when contacting the second terminal 330. On the other hand, in this embodiment, the second terminal 330 can be moved through the design of the slideway, and the driving force is applied to the second terminal 330 through the driving component 350, so that it can contact the human body more closely, thereby improving the detection accuracy.

[0101] It is understandable that, according to actual needs, the driving component 350 can be any existing driving device that can be integrated into the smart helmet, such as a telescopic motor.

[0102] This embodiment provides a more preferred embodiment, combined with Figure 4 As shown, the driving component 350 includes a push-type airbag 351, a check valve 352 and a driving airbag 353 which are connected in sequence, the push-type airbag 351 is arranged on the outside of the helmet body 310, the check valve 352 and the driving airbag 353 are both arranged in the slide, the driving airbag 353 abuts the second terminal 330, and a deflation valve 360 ​​is also arranged on the outside of the helmet body 310, and the deflation valve 360 ​​is connected to the driving airbag 353.

[0103] In the above description, the push-type inflatable bag 351 is arranged outside the helmet body 310, which means that the push-type inflatable bag 351 can be located outside the helmet body 310 as a whole, or can be partially embedded in the helmet body 310, with only the pressed side exposed to the outside. When in use, by pressing the push-type heavy air bag, the driving air bag 353 can be inflated in conjunction with the check valve 352, thereby pushing the second terminal 330 forward to abut against the human skin. The driving air bag 353 can be deflated through the deflation valve 360 ​​to restore it to its initial state.

[0104] The significance of this embodiment is that the driving of the second terminal 330 is changed to passive driving by means of the push-type inflatable bag 351 and the driving air bag 353, which reduces the cost, weight and power consumption of the helmet and improves its practicality. At the same time, compared with the driving method of rigid connection such as a motor, the driving air bag 353 will not limit the angular deviation of the second terminal 330. Its elastic deformation feature can retain the deformation margin to adapt to the angular change of the second terminal 330 when driving the second terminal 330, so that the second terminal 330 can produce an angular deviation to better fit the surface of the human body, further improving the detection accuracy.

[0105] The present invention provides a blood pressure and heart rate monitoring method and system based on a smart helmet, and a smart helmet, wherein the smart helmet comprises a helmet body and a control module, wherein a first terminal for detecting a PPG signal and a second terminal for detecting an ECG signal are arranged inside the helmet body, and the control module is communicatively connected with the first terminal and the second terminal, and the control module is used to execute the blood pressure and heart rate monitoring method based on the smart helmet, wherein the method first obtains a PPG signal, and obtains a target heart rate according to the PPG signal, then obtains an ECG signal, and obtains a reference heart rate according to the ECG signal, and then obtains the credibility of the ECG signal according to the deviation between the target heart rate and the reference heart rate, and finally obtains the target blood pressure according to the PPG signal and the ECG signal in combination with the credibility. Compared with the prior art, the present invention monitors heart rate through PPG signals, monitors electrocardiogram signals through ECG signals, and monitors blood pressure in combination with PPG signals, thereby avoiding squeezing behavior such as the Korotkoff sound method and improving the comfort level when monitoring blood pressure. It is worth noting that the present invention further evaluates the credibility of the ECG signal based on the heart rate, thereby calculating the blood pressure in combination with the credibility to improve monitoring accuracy, thus perfectly solving the problem of how to more comfortably monitor heart rate and blood pressure through wearable devices.

[0106] It should be noted that the various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0107] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A blood pressure and heart rate monitoring method based on a smart helmet, characterized in that: Applied to a smart helmet, the smart helmet includes a helmet body and a control module, the helmet body is provided with a first terminal for detecting a PPG signal and a second terminal for detecting an ECG signal, and the control module is communicatively connected with the first terminal and the second terminal; The control module is used to execute a blood pressure and heart rate monitoring method based on a smart helmet, the method comprising: Obtain the PPG signal, and obtain the target heart rate based on the PPG signal; Acquire an ECG signal, and obtain a reference heart rate according to the ECG signal; The credibility of the ECG signal is obtained according to the deviation between the target heart rate and the reference heart rate; According to the PPG signal and ECG signal, combined with the credibility, the target blood pressure is obtained; Among them, according to the PPG signal and ECG signal, combined with the credibility, the target blood pressure is obtained, including: Establishing a feature vector according to the PPG signal, the ECG signal and the credibility, wherein the feature vector includes a credibility feature element, and the credibility feature element is used to characterize the credibility; The feature vector is input into a preset neural network model to obtain the target blood pressure output by the preset neural network model.

2. The blood pressure and heart rate monitoring method based on a smart helmet according to claim 1, characterized in that: The preset neural network model is a recurrent neural network, and the input data of the preset neural network model is a feature vector sequence composed of feature vectors. Each feature vector in the feature vector sequence corresponds to a detection moment, and multiple feature vectors in the feature vector sequence are arranged in chronological order based on their corresponding detection moments. The time span of the detection moments corresponding to the multiple feature vectors in the feature vector sequence is greater than the preset cardiac cycle; the feature vector also includes PPG numerical elements and ECG numerical elements. The PPG numerical elements in the feature vector are used to characterize the PPG detection values ​​in the PPG signal at the detection moment corresponding to the feature vector, and the ECG numerical elements in the feature vector are used to characterize the ECG detection values ​​in the ECG signal at the detection moment corresponding to the feature vector.

3. A blood pressure and heart rate monitoring system based on a smart helmet, characterized in that: Applied to a smart helmet, the smart helmet includes a helmet body and a control module, the helmet body is provided with a first terminal for detecting a PPG signal and a second terminal for detecting an ECG signal, and the control module is communicatively connected with the first terminal and the second terminal; The control module is used to operate the blood pressure and heart rate monitoring system based on the smart helmet, which includes: A heart rate calculation module is used to obtain a PPG signal and obtain a target heart rate based on the PPG signal; A reference calculation module, used for acquiring an ECG signal and obtaining a reference heart rate according to the ECG signal; An error analysis module is used to obtain the credibility of the ECG signal according to the deviation between the target heart rate and the reference heart rate; The blood pressure calculation module is used to obtain the target blood pressure based on the PPG signal and the ECG signal in combination with the credibility; Among them, according to the PPG signal and ECG signal, combined with the credibility, the target blood pressure is obtained, including: Establishing a feature vector according to the PPG signal, the ECG signal and the credibility, wherein the feature vector includes a credibility feature element, and the credibility feature element is used to characterize the credibility; The feature vector is input into a preset neural network model to obtain the target blood pressure output by the preset neural network model.

4. A smart helmet, characterized in that: The helmet body includes a helmet body and a control module. The helmet body is provided with a first terminal for detecting a PPG signal and a second terminal for detecting an ECG signal. The control module is communicatively connected with the first terminal and the second terminal. The control module is used for: Obtain the PPG signal, and obtain the target heart rate based on the PPG signal; Acquire an ECG signal, and obtain a reference heart rate according to the ECG signal; The credibility of the ECG signal is obtained according to the deviation between the target heart rate and the reference heart rate; According to the PPG signal and ECG signal, combined with the credibility, the target blood pressure is obtained; Among them, according to the PPG signal and ECG signal, combined with the credibility, the target blood pressure is obtained, including: Establishing a feature vector according to the PPG signal, the ECG signal and the credibility, wherein the feature vector includes a credibility feature element, and the credibility feature element is used to characterize the credibility; The feature vector is input into a preset neural network model to obtain the target blood pressure output by the preset neural network model.

5. The smart helmet according to claim 4, characterized in that: The helmet further comprises a liner, which is arranged on the inner side of the helmet body. A slideway is provided in the liner, and the second terminal is movably inserted in the slideway. A driving component is also provided on the inner side of the second terminal in the slideway. The driving component comprises a movable output end, and the output end is connected to the second terminal.

6. The smart helmet according to claim 5, characterized in that: The driving component includes a push-type inflatable bag, a check valve and a driving airbag which are connected in sequence. The push-type inflatable bag is arranged on the outside of the helmet body. The check valve and the driving airbag are both arranged in the slideway. The driving airbag abuts the second terminal. A deflation valve is also arranged on the outside of the helmet body, and the deflation valve is connected to the driving airbag.

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