A method and system for monitoring and warning of autologous arteriovenous fistula based on triboelectric technology

Abstract

The present invention provides a method and system for self - arteriovenous fistula monitoring and early warning based on piezoelectric technology, relating to the technical field of wearable medical devices. The method includes the following steps: interference impact assessment; data deviation level acquisition; data transmission assessment. The present invention obtains the skin contamination coefficient by evaluating the acquired initial arteriovenous fistula data, then obtains the arteriovenous fistula deviation score based on the initial arteriovenous fistula data and the skin contamination coefficient, conducts level division to obtain the data deviation level, optimizes the data according to the data deviation level, and finally obtains the data transmission evaluation value based on the network - transmitted data, the arteriovenous fistula data after transmission and the initial arteriovenous fistula data, achieving the effect of improving the monitoring accuracy in the process of self - arteriovenous fistula monitoring and early warning, and solving the problem of low monitoring accuracy in the prior art during the process of self - arteriovenous fistula monitoring and early warning.

Description

Technical Field

[0001] The present invention relates to the technical field of wearable medical devices, and particularly to a method and system for monitoring and warning of autogenous arteriovenous fistulas based on triboelectric technology. Background Art

[0002] In recent years, the number of patients with chronic kidney disease has been gradually increasing, and most of these patients will develop into end-stage kidney disease, namely uremia. Such patients need to undergo regular hemodialysis to maintain their lives. As the main access for hemodialysis, the health status of autogenous arteriovenous fistulas is directly related to the smooth progress of dialysis and the life safety of patients. Triboelectric technology is a new emerging technical field that uses flexible electronic devices and sensors to monitor and sense human physiological signals. Therefore, real-time monitoring and warning of autogenous arteriovenous fistulas are of great significance for ensuring the life safety of patients and improving the dialysis effect.

[0003] In the prior art, physiological parameter data of autogenous arteriovenous fistulas are collected in real time through flexible sensors, and then the collected data are preprocessed and feature extracted. Finally, it is judged whether there is an abnormality in the autogenous arteriovenous fistulas according to the extracted feature information. During long-term use, the sensors may experience a decrease in sensitivity and drift. In addition, the data accuracy is usually affected by various factors, including the influence of external devices, the activities of the monitored object, and the limitations of the processing algorithm. The existence of these factors may lead to fluctuations and instabilities in the measurement results. Therefore, it is necessary to design a method and system for monitoring and warning of autogenous arteriovenous fistulas based on triboelectric technology that can detect the accuracy of data and process data problems in a timely manner, so as to solve the problem of low monitoring accuracy in the process of monitoring and warning of autogenous arteriovenous fistulas. Summary of the Invention

[0004] The present invention provides a method and system for monitoring and warning of autogenous arteriovenous fistulas based on triboelectric technology, which solves the problem of low monitoring accuracy in the process of monitoring and warning of autogenous arteriovenous fistulas in the prior art, and realizes the improvement of monitoring accuracy in the process of monitoring and warning of autogenous arteriovenous fistulas. The technical solution is as follows:

[0005] A method for monitoring and warning of autogenous arteriovenous fistula based on triboelectric technology, comprising: S1, evaluating the interference impact on the initial arteriovenous fistula data obtained by the sensor to obtain a skin contamination coefficient, and the skin contamination coefficient is used to evaluate the degree of influence of the sensor by skin contamination; S2, obtaining a data deviation level by grading the arteriovenous fistula deviation score obtained according to the initial arteriovenous fistula data and the skin contamination coefficient, and optimizing the arteriovenous fistula data according to the data deviation level; S3, after data optimization, obtaining a data transmission evaluation value according to the obtained network transmission data, the transmitted arteriovenous fistula data and the initial arteriovenous fistula data, and judging whether to perform transmission optimization based on the data transmission evaluation value, and the data transmission evaluation value is used to evaluate the quality of the transmitted data.

[0006] Optionally, the specific method for obtaining the skin contamination coefficient is as follows: obtaining skin interference data, where the skin interference data includes skin surface grease data and skin surface sweat data; judging whether the skin surface grease data is greater than a preset grease threshold, if the skin surface grease data is greater than the preset grease threshold, then record the first contamination coefficient as 1, otherwise record the first contamination coefficient as 0, and the first contamination coefficient is used to evaluate whether the sensor is interfered by grease; judging whether the skin surface sweat data is greater than a preset sweat threshold, if the skin surface sweat data is greater than the preset sweat threshold, then record the second contamination coefficient as 1, otherwise record the second contamination coefficient as 0, and the second contamination coefficient is used to evaluate whether the sensor is interfered by sweat; adding the first contamination coefficient and the second contamination coefficient to obtain the skin contamination coefficient.

[0007] Optionally, the specific method for obtaining the arteriovenous fistula deviation score is as follows: Obtain preset arteriovenous fistula data from a preset database, where the preset arteriovenous fistula data includes preset blood flow rate data extremes, preset blood vessel inner diameter data extremes, and preset distance from the skin thickness data extremes. The preset blood flow rate data extremes include a preset blood flow rate data maximum value and a preset blood flow rate data minimum value. The preset blood vessel inner diameter data extremes include a preset blood vessel inner diameter data maximum value and a preset blood vessel inner diameter data minimum value. The preset distance from the skin thickness data extremes include a preset distance from the skin thickness data maximum value and a preset distance from the skin thickness data minimum value; Obtain the blood flow rate data deviation based on the relative relationship between the initial blood flow rate data and the preset blood flow rate data extremes. The blood flow rate data deviation represents the deviation between the initial blood flow rate data and the preset blood flow rate data extremes; Obtain the blood vessel inner diameter data deviation based on the relative relationship between the initial blood vessel inner diameter data and the preset blood vessel inner diameter data extremes. The blood vessel inner diameter data deviation represents the deviation between the initial blood vessel inner diameter data and the preset blood vessel inner diameter data extremes; Obtain the distance from the skin thickness data deviation based on the relative relationship between the initial distance from the skin thickness data and the preset distance from the skin thickness data extremes. The distance from the skin thickness data deviation represents the deviation between the initial distance from the skin thickness data and the preset distance from the skin thickness data extremes; Process the skin contamination coefficient, blood flow rate data deviation, blood vessel inner diameter data deviation, and distance from the skin thickness data deviation to obtain the arteriovenous fistula deviation score.

[0008] Optionally, the data deviation levels include a first deviation level, a second deviation level, and a third deviation level; The first deviation level represents the level with the smallest data deviation degree of the arteriovenous fistula when the arteriovenous fistula deviation score is less than a preset first threshold; The second deviation level represents the level corresponding to the arteriovenous fistula deviation when the arteriovenous fistula deviation score is less than a preset second threshold; The third deviation level represents the level with the largest data deviation degree of the arteriovenous fistula when the arteriovenous fistula deviation score is not less than the preset second threshold.

[0009] Optionally, the specific method for obtaining the data transmission evaluation value based on the acquired network transmission data, post-transmission arteriovenous fistula data, and initial arteriovenous fistula data is as follows: Obtain preset network transmission data from a preset database, where the preset network transmission data includes a preset packet loss rate, a preset delay, and a preset transmission rate; obtain the post-transmission blood flow velocity data deviation based on the relative relationship between the post-transmission blood flow velocity data and the extreme values of the preset blood flow velocity data; obtain the post-transmission blood vessel inner diameter data deviation based on the relative relationship between the post-transmission blood vessel inner diameter data and the extreme values of the preset blood vessel inner diameter data; obtain the post-transmission distance from the skin thickness data deviation based on the relative relationship between the post-transmission distance from the skin thickness data and the extreme values of the preset distance from the skin thickness data; process the post-transmission blood flow velocity data deviation, the post-transmission blood vessel inner diameter data deviation, and the post-transmission distance from the skin thickness data deviation to obtain the post-transmission arteriovenous fistula deviation score; obtain the packet loss rate deviation based on the relative relationship between the packet loss rate and the preset packet loss rate, where the packet loss rate deviation represents the deviation between the packet loss rate and the preset packet loss rate; obtain the delay deviation based on the relative relationship between the delay and the preset delay, where the delay deviation represents the deviation between the delay and the preset delay; obtain the transmission rate deviation based on the relative relationship between the transmission rate and the preset transmission rate, where the transmission rate deviation represents the deviation between the transmission rate and the preset transmission rate; process the packet loss rate deviation, the delay deviation, and the transmission rate deviation to obtain a network transmission coefficient, which is used to evaluate network performance; obtain the data transmission evaluation value based on the relative relationship between the network transmission coefficient, the arteriovenous fistula deviation score, and the post-transmission arteriovenous fistula deviation score.

[0010] Optionally, the specific limit expression of the data transmission evaluation value is:

[0011]

[0012]

[0013] In the formula, i represents the acquisition times serial number of the initial arteriovenous fistula data, i = 1, 2,..., T, T represents the total acquisition times of the initial arteriovenous fistula data, SHU represents the data transmission evaluation value, LUO represents the network transmission coefficient, DIU represents the packet loss rate, YAN represents the delay, SUL represents the transmission rate, DIU 0 represents the preset packet loss rate, YAN 0 represents the preset delay, SUL 0 represents the preset transmission rate, GAN i represents the skin contamination coefficient collected for the i-th time, CHA i represents the arteriovenous fistula deviation score of the initial arteriovenous fistula data collected for the i-th time, CHA i ′ represents the post-transmission arteriovenous fistula deviation score corresponding to the initial arteriovenous fistula data collected for the i-th time, LP i′ It represents the deviation of the post - transmission blood flow velocity data corresponding to the initial arteriovenous fistula data collected in the i - th collection, NP i ′ It represents the deviation of the post - transmission blood vessel inner diameter data corresponding to the initial arteriovenous fistula data collected in the i - th collection, DP i ′ It represents the deviation of the post - transmission skin - to - depth thickness data corresponding to the initial arteriovenous fistula data collected in the i - th collection, CLS i ′ It represents the post - transmission blood flow velocity data corresponding to the initial arteriovenous fistula data collected in the i - th collection, CLS max It represents the maximum value of the preset blood flow velocity data, CLS min It represents the minimum value of the preset blood flow velocity data, CNJ i ′ It represents the post - transmission blood vessel inner diameter data corresponding to the initial arteriovenous fistula data collected in the i - th collection, CNJ max It represents the maximum value of the preset blood vessel inner diameter data, CNJ min It represents the minimum value of the preset blood vessel inner diameter data, CJP i ′ It represents the post - transmission skin - to - depth thickness data corresponding to the initial arteriovenous fistula data collected in the i - th collection, CJP max It represents the maximum value of the preset skin - to - depth thickness data, CJP min It represents the minimum value of the preset skin - to - depth thickness data.

[0014] An embodiment of the present invention provides a self - body arteriovenous fistula monitoring and early warning system based on triboelectric technology, including: an interference impact assessment module, a data deviation level acquisition module, and a data transmission assessment module; wherein, the interference impact assessment module is used to conduct an interference impact assessment on the initial arteriovenous fistula data obtained through a sensor to obtain a skin contamination coefficient, and the skin contamination coefficient is used to evaluate the influence degree of the sensor affected by skin contamination; the data deviation level acquisition module is used to perform level division on the arteriovenous fistula deviation score obtained according to the initial arteriovenous fistula data and the skin contamination coefficient to obtain a data deviation level, and perform data optimization on the arteriovenous fistula data according to the data deviation level; the data transmission assessment module is used to, after data optimization, obtain a data transmission assessment value according to the obtained network transmission data, post - transmission arteriovenous fistula data, and initial arteriovenous fistula data, and judge whether to perform transmission optimization based on the data transmission assessment value, and the data transmission assessment value is used to evaluate the quality of the transmitted data.

[0015] The above - mentioned technical solution of the present invention has at least the following beneficial effects compared with the prior art:

[0016] 1. Obtain the skin contamination coefficient from the acquired initial arteriovenous fistula data, then obtain the data deviation level based on the arteriovenous fistula deviation score and the skin contamination coefficient, and perform data optimization according to the data deviation level. Finally, obtain the data transmission evaluation value based on the network transmission data, the arteriovenous fistula data after transmission, and the initial arteriovenous fistula data, thereby accurately quantifying the data accuracy, and further improving the monitoring accuracy in the process of autologous arteriovenous fistula monitoring and early warning, effectively solving the problem of low monitoring accuracy in the process of autologous arteriovenous fistula monitoring and early warning in the prior art.

[0017] 2. Obtain the blood flow rate data deviation from the initial blood flow rate data and the extreme values of the preset blood flow rate data, then obtain the blood vessel inner diameter data deviation from the initial blood vessel inner diameter data and the extreme values of the preset blood vessel inner diameter data, then obtain the distance from the skin thickness data deviation from the initial distance from the skin thickness data and the extreme values of the preset distance from the skin thickness data. Finally, obtain the arteriovenous fistula deviation score based on the skin contamination coefficient, the blood flow rate data deviation, the blood vessel inner diameter data deviation, and the distance from the skin thickness data deviation, thereby quantitatively evaluating the interference degree of external factors on the data, and further improving the data accuracy in the process of autologous arteriovenous fistula monitoring and early warning.

[0018] 3. Process the arteriovenous fistula deviation score after transmission through the blood flow rate data deviation after transmission, the blood vessel inner diameter data deviation after transmission, and the distance from the skin thickness data deviation after transmission, then process the packet loss rate deviation, the delay deviation, and the transmission rate deviation to obtain the network transmission coefficient. Finally, obtain the data transmission evaluation value based on the relative relationship between the network transmission coefficient, the arteriovenous fistula deviation score, and the arteriovenous fistula deviation score after transmission, thereby quantitatively evaluating the quality of the arteriovenous fistula data after transmission, and further improving the quality and stability of data transmission in the process of autologous arteriovenous fistula monitoring and early warning. Brief Description of the Drawings

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0020] Figure 1 It is a flowchart of a method for monitoring and early warning of autologous arteriovenous fistula based on flexible electric technology of the present invention;

[0021] Figure 2 It is a schematic diagram of the change of the network transmission coefficient of the present invention with the change of the packet loss rate;

[0022] Figure 3 It is a schematic diagram of the change of the network transmission coefficient of the present invention with the change of the delay;

[0023] Figure 4 This is a schematic diagram showing the change of the network transmission coefficient of the present invention with the change of the transmission rate;

[0024] Figure 5 This is a schematic structural diagram of a self - arteriovenous fistula monitoring and warning system based on the flexible electricity technology of the present invention. Detailed implementation manners

[0025] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the described embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0026] Unless otherwise defined, the technical terms or scientific terms used in the present invention shall have the ordinary meanings understood by those of ordinary skill in the art to which the present invention pertains. The "first", "second", and similar terms used in the present invention do not denote any order, quantity, or importance, but are only used to distinguish different components. Similarly, terms such as "a", "an", or "the" do not denote a quantity limitation, but mean that there is at least one. The terms "including" or "comprising" and the like mean that the elements or items appearing before this word cover the elements or items listed after this word and their equivalents, without excluding other elements or items. The terms "connected" or "coupled" and the like are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect.

[0027] It should be noted that the "upper", "lower", "left", "right", "front", "rear", etc. used in the present invention are only used to represent relative positional relationships. When the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0028] Aiming at the problem of low monitoring accuracy in the existing self - arteriovenous fistula monitoring and warning process, the present invention provides a self - arteriovenous fistula monitoring and warning method and system based on the flexible electricity technology.

[0029] As Figure 1As shown in the figure, an autogenous arteriovenous fistula monitoring and early warning method and system based on triboelectric technology are provided in an embodiment of the present invention, including: S1, interference impact assessment: performing interference impact assessment on the initial arteriovenous fistula data obtained through a sensor to obtain a skin contamination coefficient, which is used to evaluate the degree of influence of the sensor by skin contamination; S2, obtaining data deviation level: obtaining a data deviation score based on the initial arteriovenous fistula data and the skin contamination coefficient, performing level division to obtain a data deviation level, and optimizing the arteriovenous fistula data according to the data deviation level. The arteriovenous fistula deviation score represents the deviation degree of the initial arteriovenous fistula data; S3, data transmission assessment: after data optimization, obtaining a data transmission assessment value based on the obtained network transmission data, the arteriovenous fistula data after transmission, and the initial arteriovenous fistula data, and judging whether to perform transmission optimization based on the data transmission assessment value. The data transmission assessment value is used to evaluate the quality of the transmitted data.

[0030] It should be added that the initial blood flow velocity data and the initial skin-to-vessel thickness data are obtained through a flexible ultrasonic sensor. The flexible ultrasonic sensor probe measures the blood flow velocity by continuously emitting ultrasonic waves and receiving reflected waves; the flexible ultrasonic sensor probe obtains the initial skin-to-vessel thickness data by emitting a signal and calculating the reflection time, and is usually arranged on the skin surface and closely attached to the artery site (such as the carotid artery, radial artery, femoral artery, etc., and a suitable position is selected according to the thickness of the skin and the depth of the blood vessel).

[0031] The initial blood vessel inner diameter data is obtained through a flexible pressure sensor; the flexible pressure sensor monitors the expansion and contraction of the blood vessel wall caused by blood flow pressure during each heartbeat, and calculates the inner diameter of the blood vessel by detecting the stress change of the blood vessel; when the flexible pressure sensor is used to measure the initial blood vessel inner diameter data, it is usually arranged on the skin surface, close to or attached to the main artery site, and a site where it is easy to sense the expansion and contraction of the blood vessel is selected, such as the wrist, leg, neck, etc.

[0032] In this embodiment, in hemodialysis patients, arteriovenous fistula is a commonly used vascular access for drawing blood from the body for dialysis and then returning the purified blood to the body; interference impact assessment refers to detecting and quantifying the interference existing in the initial arteriovenous fistula data; the interference includes motion artifacts, multi-channel interference, sensor contamination interference, and environmental noise interference; motion artifacts are usually caused by the patient's movement during dialysis, which may lead to serious deviations in the monitoring data; in a multi-channel monitoring system, signal interference between channels may cause cross-influence of data, especially when multiple physiological parameters need to be monitored simultaneously; the oil on the skin surface may cover the sensor surface, forming an isolation layer, resulting in the sensor being unable to accurately sense the physiological signals under the skin; sweat contains salts and other electrolytes, which may affect the electrochemical performance of the sensor, leading to errors in data acquisition; through the above steps, the improvement of data accuracy is achieved, and further the improvement of monitoring accuracy in the process of autologous arteriovenous fistula monitoring and early warning is realized.

[0033] Among them, the specific method for obtaining the skin contamination coefficient is as follows: Obtain skin interference data, where the skin interference data includes skin surface oil data and skin surface sweat data; Determine whether the skin surface oil data is greater than a preset oil threshold. If the skin surface oil data is greater than the preset oil threshold, record the first contamination coefficient as 1, otherwise record the first contamination coefficient as 0. The first contamination coefficient is used to evaluate whether the sensor is interfered by oil; Determine whether the skin surface sweat data is greater than a preset sweat threshold. If the skin surface sweat data is greater than the preset sweat threshold, record the second contamination coefficient as 1, otherwise record the second contamination coefficient as 0. The second contamination coefficient is used to evaluate whether the sensor is interfered by sweat; Add the first contamination coefficient and the second contamination coefficient to obtain the skin contamination coefficient.

[0034] In this embodiment, the skin surface oil data represents the oil content on the skin surface; the skin surface oil data is obtained by electrochemical impedance spectroscopy; the skin surface sweat data represents the humidity on the skin surface; the skin surface sweat data is obtained by a hygrometer; the preset oil threshold is set according to the sensor characteristics. For example, if the sensor's oil tolerance range is that the oil layer thickness does not exceed 5 microns, then the preset oil threshold is set to 5 microns; the preset sweat threshold is set according to the sensor characteristics. For example, if the sensor's sweat tolerance range is 60% RH, then the preset sweat threshold is set to 60% RH.

[0035] Among them, the specific method for obtaining the arteriovenous fistula deviation score is as follows: Obtain preset arteriovenous fistula data from a preset database. The preset arteriovenous fistula data includes preset extreme values of blood flow rate data, preset extreme values of blood vessel inner diameter data, and preset extreme values of distance from the skin thickness data. The preset extreme values of blood flow rate data include the maximum value of the preset blood flow rate data and the minimum value of the preset blood flow rate data. The preset extreme values of blood vessel inner diameter data include the maximum value of the preset blood vessel inner diameter data and the minimum value of the preset blood vessel inner diameter data. The preset extreme values of distance from the skin thickness data include the maximum value of the preset distance from the skin thickness data and the minimum value of the preset distance from the skin thickness data; Obtain the blood flow rate data deviation (i.e., LP in the specific limit expression of the arteriovenous fistula deviation score) according to the relative relationship between the initial blood flow rate data and the preset extreme values of blood flow rate data. The blood flow rate data deviation represents the deviation between the initial blood flow rate data and the preset extreme values of blood flow rate data. i ) Obtain the blood vessel inner diameter data deviation (i.e., NP in the specific limit expression of the arteriovenous fistula deviation score) according to the relative relationship between the initial blood vessel inner diameter data and the preset extreme values of blood vessel inner diameter data. The blood vessel inner diameter data deviation represents the deviation between the initial blood vessel inner diameter data and the preset extreme values of blood vessel inner diameter data. i ) Obtain the distance from the skin thickness data deviation (i.e., DP in the specific limit expression of the arteriovenous fistula deviation score) according to the relative relationship between the initial distance from the skin thickness data and the preset extreme values of distance from the skin thickness data. The distance from the skin thickness data deviation represents the deviation between the initial distance from the skin thickness data and the preset extreme values of distance from the skin thickness data. i ) Process the skin contamination coefficient, blood flow rate data deviation, blood vessel inner diameter data deviation, and distance from the skin thickness data deviation to obtain the arteriovenous fistula deviation score.

[0036] Among them, the specific limit expression of the arteriovenous fistula deviation score is:

[0037]

[0038] In the formula, i represents the acquisition times number of the initial arteriovenous fistula data, i = 1, 2,..., T, T represents the total number of acquisitions of the initial arteriovenous fistula data, GAN i represents the skin contamination coefficient of the i-th acquisition, CHA i represents the arteriovenous fistula deviation score of the initial arteriovenous fistula data of the i-th acquisition, LP i represents the blood flow rate data deviation of the initial arteriovenous fistula data of the i-th acquisition, NP i represents the blood vessel inner diameter data deviation of the initial arteriovenous fistula data of the i-th acquisition, DP i represents the distance from the skin thickness data deviation of the initial arteriovenous fistula data of the i-th acquisition, CLS i represents the initial blood flow rate data of the initial arteriovenous fistula data of the i-th acquisition, CLS maxRepresents the maximum value of the preset blood flow rate data, CLS min Represents the minimum value of the preset blood flow rate data, CNJ i Represents the initial blood vessel inner diameter data of the initial arteriovenous fistula data collected for the i-th time, CNJ max Represents the maximum value of the preset blood vessel inner diameter data, CNJ min Represents the minimum value of the preset blood vessel inner diameter data, CJP i Represents the initial distance from the skin thickness data of the initial arteriovenous fistula data collected for the i-th time, CJP max Represents the maximum value of the preset distance from the skin thickness data, CJP min Represents the minimum value of the preset distance from the skin thickness data.

[0039] In this embodiment, the maximum value of the preset blood flow rate data is represented by the maximum value of the initial blood flow rate data within the historical time period; the minimum value of the preset blood flow rate data is represented by the minimum value of the initial blood flow rate data within the historical time period; the maximum value of the preset blood vessel inner diameter data is represented by the maximum value of the initial blood vessel inner diameter data within the historical time period; the minimum value of the preset blood vessel inner diameter data is represented by the minimum value of the initial blood vessel inner diameter data within the historical time period; the maximum value of the preset distance from the skin thickness data is represented by the maximum value of the initial distance from the skin thickness data within the historical time period; the minimum value of the preset distance from the skin thickness data is represented by the minimum value of the initial distance from the skin thickness data within the historical time period; through the above steps, a quantitative evaluation of the deviation of the initial arteriovenous fistula data caused by external factors is realized, and further, the data accuracy in the process of autologous arteriovenous fistula monitoring and early warning is improved.

[0040] In a multi-channel interference scenario, the deviation of the blood flow rate data may further affect the measurement of the initial blood vessel inner diameter data, because the change of the initial blood flow rate data may affect the pressure distribution and diameter in the blood vessel; the deviation of the blood vessel inner diameter data may affect the judgment of the blood vessel wall structure, thus indirectly affecting the accuracy of the measurement of the initial distance from the skin thickness data; similarly, the deviation of the initial distance from the skin thickness data may affect the measurement of the initial blood vessel inner diameter data and the initial blood flow rate data, because the deviation of the distance from the skin thickness data may reflect the change of the blood vessel wall structure; as the deviation of the blood flow rate data, the blood vessel inner diameter data and the distance from the skin thickness data increases, the arteriovenous fistula deviation score may increase accordingly.

[0041] Taking the number of times of collecting the initial arteriovenous fistula data as 1 time and the skin contamination coefficient as 2 as an example, the change statistical table of the arteriovenous fistula deviation score is shown in Table 1:

[0042] Table 1 Change Statistical Table of Arteriovenous Fistula Deviation Score

[0043]

[0044] It can be seen from the data of the first group and the second group in the table that when the deviations of the blood flow velocity data and the blood vessel inner diameter data remain unchanged, the arteriovenous fistula deviation score increases with the increase of the deviation of the subcutaneous thickness data; it can be seen from the data of the second group and the third group that when the deviations of the blood flow velocity data and the subcutaneous thickness data remain unchanged, the arteriovenous fistula deviation score increases with the increase of the deviation of the blood vessel inner diameter data; it can be seen from the data of the third group and the fourth group that when the deviations of the blood vessel inner diameter data and the subcutaneous thickness data remain unchanged, the arteriovenous fistula deviation score increases with the increase of the deviation of the blood flow velocity data.

[0045] Among them, the data deviation levels include the first deviation level, the second deviation level, and the third deviation level; the first deviation level represents the level corresponding to the arteriovenous fistula deviation when the arteriovenous fistula deviation score is less than the preset first threshold, and the first deviation level represents the level with the smallest data deviation degree of the arteriovenous fistula; the second deviation level represents the level corresponding to the arteriovenous fistula deviation when the arteriovenous fistula deviation score is less than the preset second threshold; the third deviation level represents the level corresponding to the arteriovenous fistula deviation when the arteriovenous fistula deviation score is not less than the preset second threshold, and the third deviation level represents the level with the largest data deviation degree of the arteriovenous fistula.

[0046] In this embodiment, the preset first threshold is represented by the average value of the arteriovenous fistula deviation scores in the historical time period minus twice the variance; the preset second threshold is represented by the maximum value of the arteriovenous fistula deviation scores in the historical time period; through the real-time monitoring of the initial arteriovenous fistula data and combining different data deviation levels to judge the deviation degree of the data, data support is provided for subsequent data optimization, and the management efficiency of the initial arteriovenous fistula data in the process of autologous arteriovenous fistula monitoring and early warning is improved.

[0047] Among them, data optimization includes first data optimization, second data optimization, and third data optimization; the specific process of the first data optimization is as follows: judge whether there is broadband noise in the initial arteriovenous fistula data, if so, perform noise filtering, otherwise prompt the preset personnel to clean the sensor, and the broadband noise is measured by a spectrum analyzer; the specific process of the second data optimization is as follows: judge whether there is multi-channel interference in the initial arteriovenous fistula data, if so, perform multi-channel interference optimization, otherwise perform the first data optimization, and the multi-channel interference optimization includes adjusting the sampling frequency and signal denoising, and the multi-channel interference refers to the interference generated due to the mutual influence between multiple signal channels; the specific process of the third data optimization is as follows: judge whether there is motion artifact in the initial arteriovenous fistula data, if so, remove the motion artifact through Kalman filtering, otherwise perform the second data optimization, and the motion artifact refers to the false signal caused by the movement of the measurement object or the movement of the sensor.

[0048] In this embodiment, for broadband noise, a low-pass filter, a high-pass filter, or a band-stop filter can be used to remove it; the specific steps for adjusting the sampling frequency are as follows: The sampling frequency is set according to the Nyquist sampling theorem. For example, if the signal frequency range is from 1 kHz to 10 kHz, the sampling frequency is at least twice the highest frequency in the initial arteriovenous fistula data, that is, 20 kHz. After adjusting the sampling frequency, the initial arteriovenous fistula data is re-collected and the quality evaluation value of the collected data is evaluated. If the arteriovenous fistula deviation score after adjustment is 0, the sampling frequency can be further fine-tuned, and the verification process is repeated until the optimal sampling frequency setting is found; Signal denoising is achieved by the wavelet denoising algorithm to remove noise. Wavelet denoising utilizes the multi-resolution characteristics of wavelet transform to decompose the signal into different scales, and then processes the wavelet coefficients at each scale to remove noise; By methods such as noise filtering, multi-channel interference optimization, and Kalman filtering, adverse factors such as broadband noise, multi-channel interference, and motion artifacts can be effectively removed, realizing the improvement of the quality of the initial arteriovenous fistula data in the process of autologous arteriovenous fistula monitoring and early warning.

[0049] Among them, the specific method for obtaining the data transmission evaluation value based on the acquired network transmission data, the arteriovenous fistula data after transmission, and the initial arteriovenous fistula data is as follows: Obtain the preset network transmission data from the preset database. The preset network transmission data includes the preset packet loss rate, the preset delay, and the preset transmission rate; According to the relative relationship between the blood flow velocity data after transmission and the extreme values of the preset blood flow velocity data, obtain the deviation of the blood flow velocity data after transmission (i.e., LP in the specific limit expression of the data transmission evaluation value) i ′ ), the deviation of the blood flow velocity data after transmission represents the deviation between the blood flow velocity data after transmission and the extreme values of the preset blood flow velocity data; According to the relative relationship between the inner diameter data of the blood vessel after transmission and the extreme values of the preset inner diameter data of the blood vessel, obtain the deviation of the inner diameter data of the blood vessel after transmission (i.e., NP in the specific limit expression of the data transmission evaluation value) i ′ ), the deviation of the inner diameter data of the blood vessel after transmission represents the deviation between the inner diameter data of the blood vessel after transmission and the extreme values of the preset inner diameter data of the blood vessel; According to the relative relationship between the skin-to-depth thickness data after transmission and the extreme values of the preset skin-to-depth thickness data, obtain the deviation of the skin-to-depth thickness data after transmission (i.e., DP in the specific limit expression of the data transmission evaluation value) i ′ ), the deviation of the skin-to-depth thickness data after transmission represents the deviation between the skin-to-depth thickness data after transmission and the extreme values of the preset skin-to-depth thickness data; According to the deviation of the blood flow velocity data after transmission, the deviation of the inner diameter data of the blood vessel after transmission, and the deviation of the skin-to-depth thickness data after transmission, process to obtain the arteriovenous fistula deviation score after transmission (i.e., CHA in the specific limit expression of the data transmission evaluation value) i ′), the arteriovenous fistula deviation score after transmission represents the deviation between the arteriovenous fistula data after transmission and the preset arteriovenous fistula data; the packet loss rate deviation is obtained according to the relative relationship between the packet loss rate and the preset packet loss rate (i.e., ) in the specific limit expression of the data transmission evaluation value, and the packet loss rate deviation represents the deviation between the packet loss rate and the preset packet loss rate; the delay deviation is obtained according to the relative relationship between the delay and the preset delay (i.e., ) in the specific limit expression of the data transmission evaluation value, and the delay deviation represents the deviation between the delay and the preset delay; the transmission rate deviation is obtained according to the relative relationship between the transmission rate and the preset transmission rate (i.e., ) in the specific limit expression of the data transmission evaluation value, and the transmission rate deviation represents the deviation between the transmission rate and the preset transmission rate; the packet loss rate deviation, the delay deviation and the transmission rate deviation are processed to obtain the network transmission coefficient (i.e., LUO in the specific limit expression of the data transmission evaluation value), and the network transmission coefficient is used to evaluate the network performance; the relative relationship between the network transmission coefficient, the arteriovenous fistula deviation score and the arteriovenous fistula deviation score after transmission is used to obtain the data transmission evaluation value;

[0050] Specifically, the specific limit expression of the data transmission evaluation value is:

[0051]

[0052] In the formula, i represents the acquisition times number of the initial arteriovenous fistula data, i = 1, 2,..., T, T represents the total acquisition times of the initial arteriovenous fistula data, SHU represents the data transmission evaluation value, LUO represents the network transmission coefficient, DIU represents the packet loss rate, YAN represents the delay, SUL represents the transmission rate, DIU 0 represents the preset packet loss rate, YAN 0 represents the preset delay, SUL 0 represents the preset transmission rate, GAN i represents the skin contamination coefficient of the i-th acquisition, CHA i represents the arteriovenous fistula deviation score of the initial arteriovenous fistula data of the i-th acquisition, CHA i ′ represents the arteriovenous fistula deviation score after transmission corresponding to the initial arteriovenous fistula data of the i-th acquisition, LP i ′ represents the deviation of the blood flow velocity data after transmission corresponding to the initial arteriovenous fistula data of the i-th acquisition, NP i ′ represents the deviation of the blood vessel inner diameter data after transmission corresponding to the initial arteriovenous fistula data of the i-th acquisition, DP i ′ represents the deviation of the skin-to-depth thickness data after transmission corresponding to the initial arteriovenous fistula data of the i-th acquisition, CLSi ′ Denote the blood flow velocity data after transmission corresponding to the initial arteriovenous fistula data collected in the i-th collection, CLS max Denote the maximum value of the preset blood flow velocity data, CLS min Denote the minimum value of the preset blood flow velocity data, CNJ i ′ Denote the blood vessel inner diameter data after transmission corresponding to the initial arteriovenous fistula data collected in the i-th collection, CNJ max Denote the maximum value of the preset blood vessel inner diameter data, CNJ min Denote the minimum value of the preset blood vessel inner diameter data, CJP i ′ Denote the distance from the skin thickness data after transmission corresponding to the initial arteriovenous fistula data collected in the i-th collection, CJP max Denote the maximum value of the preset distance from the skin thickness data, CJP min Denote the minimum value of the preset distance from the skin thickness data.

[0053] In this embodiment, the preset packet loss rate is represented by the average value of the packet loss rate within the historical time period; the preset delay is represented by the average value of the delay within the historical time period; the preset transmission rate is represented by the average value of the transmission rate within the historical time period; through the above steps, a quantitative evaluation of the data quality after the transmission process in the monitoring and early warning process of the autologous arteriovenous fistula is realized, and further, the quality and stability of the data transmission in the monitoring and early warning process of the autologous arteriovenous fistula are improved.

[0054] During the data transmission process (in the hospital), due to the large number of people, a large number of computer devices, and the frequent and large changes in the monitoring data, it may lead to an increase in the network transmission burden, thereby increasing the risk of network delay and packet loss, and further may lead to a loss of the quality of the arteriovenous fistula data. Therefore, the smaller the network transmission coefficient, the greater the difference between the arteriovenous fistula deviation score and the arteriovenous fistula deviation score after transmission may be, which may lead to a decrease in the data transmission evaluation value. The smaller the data transmission evaluation value, the worse the data quality.

[0055] When the latency is high, it indicates that the data may encounter obstacles during transmission, such as network congestion, routing issues, or excessive physical distance. This may cause the buffer in the network to be filled, leading to packet loss and a decrease in the network transmission coefficient. The increase in the packet loss rate may trigger the retransmission mechanism, thereby increasing the transmission latency and further reducing the network transmission coefficient. As the packet loss rate increases, the transmission rate usually decreases because packet loss means that the data needs to be resent, increasing the total time required for transmission. When the latency is high, it means that the waiting time of the data during transmission increases, which may cause the transmission rate to decrease and further reduce the network transmission coefficient. Therefore, the network transmission coefficient decreases as the latency and packet loss rate increase, and increases as the transmission rate increases. The larger the network transmission coefficient, the better the network performance.

[0056] Taking the preset packet loss rate of 0.05%, the preset latency of 100 ms, the preset transmission rate of 500 Mbps, the range of packet loss rate from 0% to 0.5%, the range of latency from 50 ms to 150 ms, and the range of transmission rate from 450 Mbps to 550 Mbps as an example, as Figure 2 shown, it is a schematic diagram of the change of the network transmission coefficient of the present invention with the packet loss rate; when the latency is 100 ms and the transmission rate is 500 Mbps, the larger the packet loss rate, the smaller the network transmission coefficient; as Figure 3 shown, it is a schematic diagram of the change of the network transmission coefficient of the present invention with the latency; when the packet loss rate is 0.05% and the transmission rate is 500 Mbps, the larger the latency, the smaller the network transmission coefficient; as Figure 4 shown, it is a schematic diagram of the change of the network transmission coefficient of the present invention with the transmission rate; when the packet loss rate is 0.05% and the latency is 100 ms, the larger the transmission rate, the larger the network transmission coefficient.

[0057] Among them, the specific process of judging whether to perform transmission optimization based on the data transmission evaluation value is as follows: B1, judge whether the data transmission evaluation value is less than the preset data transmission threshold. If the data transmission evaluation value is less than the preset data transmission threshold, then execute B2, otherwise do not perform transmission optimization; B2, perform packet loss compensation, and judge whether the data transmission evaluation value obtained after packet loss compensation is less than the preset data transmission threshold. If so, then execute B3, otherwise end the transmission optimization; B3, send an automatic retransmission request to recover the data loss, and judge whether the data transmission evaluation value obtained after retransmission is less than the preset data transmission threshold. If the transmission data quality evaluation value obtained after retransmission is less than the preset transmission data quality threshold, then execute B4, otherwise end the transmission optimization; B4, perform encryption integrity verification, and judge whether the data transmission evaluation value obtained after encryption integrity verification is less than the preset data transmission threshold. If so, feedback to the preset personnel, otherwise end the transmission optimization.

[0058] In this embodiment, the preset data transmission threshold is represented by the maximum value of the data transmission evaluation value within the historical time period; the data packet loss compensation restores the data packet through linear interpolation technology; if the data transmission evaluation value after the data packet loss compensation is less than the preset data transmission threshold, it enters the Automatic Repeat Request (ARQ) phase, sends an ARQ signal to the sending end to request the retransmission of the lost or incorrect data packet, and after receiving the ARQ signal, the sending end retransmits the requested data packet.

[0059] The arteriovenous fistula data involves the patient's personal privacy and health status, which is of great value to patients, medical institutions, and researchers. However, it also faces the risk of being leaked or misused. Therefore, it is necessary to encrypt the arteriovenous fistula data; the encrypted integrity check is achieved by adding an encrypted hash value to the initial transmitted arteriovenous fistula data, and the receiving end uses the same hash algorithm and key to verify whether the received arteriovenous fistula data is complete and has not been tampered with; by gradually applying data packet loss compensation, automatic repeat request, and encrypted integrity check, errors and losses in the data transmission process of the autologous arteriovenous fistula monitoring and warning are detected, and thus the quality and stability of data transmission in the autologous arteriovenous fistula monitoring and warning process are improved.

[0060] Among them, it also includes judging whether the arteriovenous fistula is mature; comparing the transmitted blood flow rate data, transmitted subcutaneous thickness data, and transmitted blood vessel inner diameter data with the corresponding standard blood flow rate data, standard subcutaneous thickness data, and standard blood vessel inner diameter data respectively: if the transmitted blood flow rate data is greater than the standard blood flow rate data, the transmitted subcutaneous thickness data is less than the standard subcutaneous thickness data, and the transmitted blood vessel inner diameter is greater than the standard blood vessel inner diameter data, then the arteriovenous fistula is mature; otherwise, the arteriovenous fistula is immature.

[0061] In this embodiment, the standard blood flow rate data is set to 500 ml / min; the standard subcutaneous thickness data is set to 5 mm; the standard blood vessel inner diameter data is set to 5 mm; through real-time monitoring and accurate evaluation, the accurate judgment of the maturity of the arteriovenous fistula is achieved, and thus the monitoring accuracy in the autologous arteriovenous fistula monitoring and warning process is improved.

[0062] To determine whether an arteriovenous fistula is mature, the following criteria are also included: physical examination and basic examination tests; physical examination mainly judges whether the arteriovenous fistula is mature by observing the vascular changes around the fistula and palpation; clinical examinations include: (1) observing whether the blood flow in the arm has increased significantly; (2) judging whether there are obvious pathological changes such as cyanosis and swelling around the arteriovenous fistula, and (3) palpating whether a normal pulsation can be felt and whether there is venous dilation; basic examination tests include the arm-raising test and the pulsation enhancement test; the arm-raising test observes the blood flow and pulsation at the arteriovenous fistula by raising the arm; a mature arteriovenous fistula can usually maintain a clear pulsation, while an immature arteriovenous fistula may show insufficient blood flow or weak pulsation; the pulsation enhancement test examines the pulsation enhancement of the arteriovenous fistula through palpation and auscultation; a mature arteriovenous fistula will have a strong pulsation when the limb is relaxed, while an immature arteriovenous fistula may show a weak pulsation or be unable to be palpated.

[0063] Selection of dominant vessels: Vessels available for selection: The radial artery-cephalic vein arteriovenous fistula at the wrist of the forearm is the most commonly used; followed by the ulnar artery-basilic vein arteriovenous fistula at the wrist, forearm vein transposition arteriovenous fistula (mainly basilic vein-radial artery), elbow arteriovenous fistula (cephalic vein, basilic vein or median cubital vein-brachial artery or its branched radial artery or ulnar artery), lower limb arteriovenous fistula (great saphenous vein-dorsalis pedis artery, great saphenous vein-anterior tibial artery or posterior tibial artery), arteriovenous fistula in the anatomical snuffbox, etc.

[0064] As Figure 5 As shown, an embodiment of the present invention provides an autologous arteriovenous fistula monitoring and warning system based on flexible electric technology, including: an interference impact assessment module, a data deviation level acquisition module, and a data transmission assessment module; wherein, the interference impact assessment module is used to perform an interference impact assessment on the initial arteriovenous fistula data obtained through a sensor to obtain a skin contamination coefficient, and the skin contamination coefficient is used to evaluate the degree of influence of the sensor by skin contamination; the data deviation level acquisition module is used to perform level division on the arteriovenous fistula deviation score obtained according to the initial arteriovenous fistula data and the skin contamination coefficient to obtain a data deviation level, and optimize the arteriovenous fistula data according to the data deviation level, and the arteriovenous fistula deviation score represents the deviation degree of the initial arteriovenous fistula data; the data transmission assessment module is used to, after data optimization, obtain a data transmission assessment value according to the obtained network transmission data, the arteriovenous fistula data after transmission, and the initial arteriovenous fistula data, and judge whether to perform transmission optimization based on the data transmission assessment value, and the data transmission assessment value is used to evaluate the quality of the transmitted data.

[0065] In this embodiment, the flexible electronics technology generally refers to the use of flexible electronic materials and technologies to achieve the flexibility and wearability of electronic devices such as sensors and actuators; the autogenous arteriovenous fistula generally refers to a fistula formed by surgically connecting the patient's own artery and vein to establish a vascular access during hemodialysis treatment; by interfering with impact assessment and data optimization, the influence of external interference on the initial arteriovenous fistula data is effectively reduced, and the accuracy and reliability of the data are improved; through data transmission assessment and optimization, the quality of the arteriovenous fistula data after transmission is ensured, and thus the monitoring accuracy during the monitoring and early warning process of the autogenous arteriovenous fistula is improved.

[0066] In summary, the present invention obtains the skin contamination coefficient from the acquired initial arteriovenous fistula data, then obtains the data deviation level according to the arteriovenous fistula deviation score and the skin contamination coefficient, and performs data optimization according to the data deviation level. Finally, the data transmission evaluation value is obtained based on the network transmission data, the arteriovenous fistula data after transmission, and the initial arteriovenous fistula data, thereby accurately quantifying the data accuracy, and further improving the monitoring accuracy during the monitoring and early warning process of the autogenous arteriovenous fistula, effectively solving the problem of low monitoring accuracy in the prior art during the monitoring and early warning process of the autogenous arteriovenous fistula.

[0067] The following points need to be explained:

[0068] (1) The attached drawings of the embodiments of the present invention only relate to the structures involved in the embodiments of the present invention, and other structures can refer to the general design.

[0069] (2) For clarity, in the attached drawings used to describe the embodiments of the present invention, the thickness of the layer or region is enlarged or reduced, that is, these drawings are not drawn according to the actual scale. It can be understood that when an element such as a layer, film, region, or substrate is referred to as being "on" or "under" another element, the element can be "directly" on or under the other element or there can be an intermediate element.

[0070] (3) Without conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other to obtain new embodiments.

[0071] The above is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. The protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A monitoring and early warning method for autologous arteriovenous fistula based on flexible electric technology, characterized in that: The following steps are involved: S1, performing interference impact assessment on initial arteriovenous fistula data acquired by a sensor to obtain a skin contamination coefficient, wherein the skin contamination coefficient is used to assess the degree to which the sensor is affected by skin contamination; S2, classifying the arteriovenous fistula deviation scores obtained according to the initial arteriovenous fistula data and the skin contamination coefficient to obtain the data deviation level, and optimizing the arteriovenous fistula data according to the data deviation level; S3, after data optimization, a data transmission evaluation value is obtained according to the acquired network transmission data, the arteriovenous fistula data after transmission and the initial arteriovenous fistula data, and whether to perform transmission optimization is determined based on the data transmission evaluation value, and the data transmission evaluation value is used to evaluate the data quality after transmission.

2. The method for monitoring and early warning of autologous arteriovenous fistula based on flexible electric technology according to claim 1 is characterized in that: The specific method for obtaining the skin pollution coefficient is as follows: Acquire skin interference data, wherein the skin interference data includes skin surface oil data and skin surface sweat data; Determine whether the skin surface oil data is greater than a preset oil threshold, if the skin surface oil data is greater than the preset oil threshold, the first pollution coefficient is recorded as 1, otherwise the first pollution coefficient is recorded as 0, the first pollution coefficient is used to evaluate whether the sensor is interfered by oil; Determine whether the sweat data on the skin surface is greater than a preset sweat threshold, if the sweat data on the skin surface is greater than the preset sweat threshold, record the second contamination coefficient as 1, otherwise record the second contamination coefficient as 0, the second contamination coefficient is used to evaluate whether the sensor is interfered by sweat; The first pollution coefficient and the second pollution coefficient are added to obtain the skin pollution coefficient.

3. The method for monitoring and early warning of autologous arteriovenous fistula based on flexible electric technology according to claim 1 is characterized in that: The specific method for obtaining the arteriovenous fistula deviation score is as follows: Acquire preset arteriovenous fistula data from a preset database, wherein the preset arteriovenous fistula data includes preset blood flow velocity data extreme values, preset blood vessel inner diameter data extreme values, and preset distance-to-skin thickness data extreme values, wherein the preset blood flow velocity data extreme values ​​include preset blood flow velocity data maximum values ​​and preset blood flow velocity data minimum values, wherein the preset blood vessel inner diameter data extreme values ​​include preset blood vessel inner diameter data maximum values ​​and preset blood vessel inner diameter data minimum values, wherein the preset distance-to-skin thickness data extreme values ​​include preset distance-to-skin thickness data maximum values ​​and preset distance-to-skin thickness data minimum values; Obtaining a blood flow velocity data deviation according to a relative relationship between the initial blood flow velocity data and a preset blood flow velocity data extreme value, wherein the blood flow velocity data deviation represents a deviation between the initial blood flow velocity data and the preset blood flow velocity data extreme value; Obtaining a blood vessel inner diameter data deviation according to a relative relationship between the initial blood vessel inner diameter data and a preset blood vessel inner diameter data extreme value, wherein the blood vessel inner diameter data deviation represents a deviation between the initial blood vessel inner diameter data and the preset blood vessel inner diameter data extreme value; Obtaining a skin thickness data deviation according to a relative relationship between the initial skin thickness data and a preset skin thickness data extreme value, wherein the skin thickness data deviation represents a deviation between the initial skin thickness data and the preset skin thickness data extreme value; The arteriovenous fistula deviation score was obtained by processing the skin contamination coefficient, blood flow velocity data deviation, blood vessel inner diameter data deviation and skin thickness data deviation.

4. The method for monitoring and early warning of autologous arteriovenous fistula based on flexible electric technology according to claim 3 is characterized in that: The data deviation level includes a first deviation level, a second deviation level and a third deviation level; The first deviation level indicates the level at which the data deviation of the arteriovenous fistula is the smallest when the arteriovenous fistula deviation score is less than a preset first threshold value; The second deviation level indicates the level corresponding to the arteriovenous dysfunction deviation when the arteriovenous dysfunction deviation score is less than a preset second threshold value; The third deviation level indicates the level at which the data deviation of the arteriovenous fistula is the greatest when the arteriovenous fistula deviation score is not less than the preset second threshold.

5. The method for monitoring and early warning of autologous arteriovenous fistula based on flexible electric technology according to claim 4 is characterized in that: The data optimization includes first data optimization, second data optimization and third data optimization; The specific process of the first data optimization is as follows: Determine whether there is broadband noise in the initial arteriovenous fistula data, if yes, perform noise filtering, otherwise prompt the preset personnel to clean the sensor, the broadband noise is measured by a spectrum analyzer; The specific process of the second data optimization is as follows: Determine whether there is multi-channel interference in the initial arteriovenous fistula data, if yes, perform multi-channel interference optimization, otherwise perform first data optimization, the multi-channel interference optimization includes adjusting the sampling frequency and signal denoising, the multi-channel interference represents the interference caused by the mutual influence between multiple signal channels; The specific process of the third data optimization is as follows: It is determined whether there is motion artifact in the initial arteriovenous fistula data. If so, the motion artifact is removed by Kalman filtering, otherwise a second data optimization is performed. The motion artifact represents an erroneous signal caused by the movement of the measurement object or the movement of the sensor.

6. The method for monitoring and early warning of autologous arteriovenous fistula based on flexible electric technology according to claim 1 is characterized in that: The specific method for obtaining the data transmission evaluation value according to the acquired network transmission data, the arteriovenous fistula data after transmission and the initial arteriovenous fistula data is as follows: Acquire preset network transmission data from a preset database, wherein the preset network transmission data includes a preset packet loss rate, a preset delay, and a preset transmission rate; Obtaining the deviation of the blood flow velocity data after transmission according to the relative relationship between the blood flow velocity data after transmission and the preset blood flow velocity data extreme value; Obtaining the deviation of the blood vessel inner diameter data after transmission according to the relative relationship between the blood vessel inner diameter data after transmission and the preset blood vessel inner diameter data extreme value; The deviation of the thickness data after transmission is obtained according to the relative relationship between the thickness data after transmission and the extreme value of the preset thickness data from the skin; The deviation score of arteriovenous fistula after transmission is obtained by processing the deviation of blood flow velocity data after transmission, the deviation of blood vessel inner diameter data after transmission and the deviation of skin thickness data after transmission; Obtaining a packet loss rate deviation according to a relative relationship between the packet loss rate and a preset packet loss rate, wherein the packet loss rate deviation indicates a deviation between the packet loss rate and the preset packet loss rate; Obtaining a delay deviation according to a relative relationship between the delay and the preset delay, wherein the delay deviation indicates a deviation between the delay and the preset delay; Obtaining a transmission rate deviation according to a relative relationship between the transmission rate and the preset transmission rate, wherein the transmission rate deviation indicates a deviation between the transmission rate and the preset transmission rate; Processing the packet loss rate deviation, the delay deviation and the transmission rate deviation to obtain a network transmission coefficient, wherein the network transmission coefficient is used to evaluate network performance; The relative relationship between the network transmission coefficient, the arteriovenous fistula deviation score and the arteriovenous fistula deviation score after transmission was used to obtain the data transmission evaluation value.

7. The method for monitoring and early warning of autologous arteriovenous fistula based on flexible electric technology according to claim 6 is characterized in that: The specific limiting expression of the data transmission evaluation value is: Where i represents the number of times the initial arteriovenous fistula data is collected, i=1,2,...,T, T represents the total number of times the initial arteriovenous fistula data is collected, SHU represents the data transmission evaluation value, LUO represents the network transmission coefficient, DIU represents the packet loss rate, YAN represents the delay, SUL represents the transmission rate, DIU0 represents the preset packet loss rate, YAN0 represents the preset delay, SUL0 represents the preset transmission rate, GAN i represents the skin contamination coefficient collected at the i-th time, CHA i represents the arteriovenous fistula deviation score of the initial arteriovenous fistula data collected at the i-th time, CHA i ′ represents the post-transmission AVF deviation score corresponding to the initial AVF data collected at the i-th time, LP i ′ represents the deviation of the blood flow velocity data after transmission corresponding to the initial arteriovenous fistula data collected for the i-th time, NP i ′ represents the deviation of the vascular inner diameter data after transmission corresponding to the initial arteriovenous fistula data collected for the i-th time, DP i ′ represents the deviation of the skin thickness data after transmission corresponding to the initial arteriovenous fistula data collected for the i-th time, CLS i ′ represents the blood flow velocity data after transmission corresponding to the initial arteriovenous fistula data collected for the i-th time, CLS max Indicates the preset maximum blood flow rate data, CLS min Indicates the preset minimum value of blood flow rate data, CNJ i ′ represents the intravascular diameter data after transmission corresponding to the initial arteriovenous fistula data collected for the i-th time, CNJ max Indicates the maximum value of the preset blood vessel inner diameter data, CNJ min Indicates the preset minimum value of the blood vessel inner diameter data, CJP i ′ represents the post-transmission skin thickness data corresponding to the initial arteriovenous fistula data collected for the i-th time, CJP max Indicates the maximum value of preset skin thickness data, CJP min Indicates the preset minimum value of the skin thickness data.

8. The method for monitoring and early warning of autologous arteriovenous fistula based on flexible electric technology according to claim 7 is characterized in that: The specific process of determining whether to perform transmission optimization based on the data transmission evaluation value is as follows: B1, determine whether the data transmission evaluation value is less than the preset data transmission threshold. If the data transmission evaluation value is less than the preset data transmission threshold, execute B2, otherwise, do not perform transmission optimization; B2, perform data packet loss compensation, and determine whether the data transmission evaluation value obtained after the data packet loss compensation is less than the preset data transmission threshold. If so, execute B3, otherwise terminate the transmission optimization; B3, sending an automatic retransmission request to recover data loss, judging whether the data transmission evaluation value obtained after retransmission is less than the preset data transmission threshold, if the transmission data quality evaluation value obtained after retransmission is less than the preset transmission data quality threshold, executing B4, otherwise ending the transmission optimization; B4, perform encryption integrity check to determine whether the data transmission evaluation value obtained after the encryption integrity check is less than the preset data transmission threshold. If so, feedback is given to the preset personnel, otherwise the transmission optimization is terminated.

9. The method for monitoring and early warning of autologous arteriovenous fistula based on flexible electric technology according to claim 1, characterized in that: It also includes determining whether the arteriovenous fistula is mature; The blood flow velocity data after transmission, the skin thickness data after transmission, and the blood vessel inner diameter data after transmission are compared with the corresponding standard blood flow velocity data, standard skin thickness data, and standard blood vessel inner diameter data respectively: If the blood flow velocity data after transmission is greater than the standard blood flow velocity data, the distance-to-skin thickness data after transmission is less than the standard distance-to-skin thickness data, and the blood vessel inner diameter after transmission is greater than the standard blood vessel inner diameter data, the arteriovenous fistula is mature; Otherwise the arteriovenous fistula is immature.

10. A monitoring and early warning system for autologous arteriovenous fistula based on flexible electric technology, characterized in that: include: Interference impact assessment module, data deviation level acquisition module and data transmission assessment module; Wherein, the interference impact assessment module is used to perform interference impact assessment on the initial arteriovenous fistula data obtained through the sensor to obtain a skin contamination coefficient, and the skin contamination coefficient is used to assess the degree to which the sensor is affected by skin contamination; The data deviation level acquisition module is used to classify the arteriovenous fistula deviation scores obtained by the initial arteriovenous fistula data and the skin contamination coefficient to obtain data deviation levels, and optimize the arteriovenous fistula data according to the data deviation levels; The data transmission evaluation module is used to obtain a data transmission evaluation value based on the acquired network transmission data, post-transmission arteriovenous fistula data and initial arteriovenous fistula data after data optimization, and determine whether to perform transmission optimization based on the data transmission evaluation value. The data transmission evaluation value is used to evaluate the data quality after transmission.

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