Grading early warning system based on multi-parameter vital sign detection

Abstract

The embodiment of the invention discloses a graded early warning system based on multi-parameter vital sign detection. According to a specific embodiment of the system, a monitor device is configured to collect a vital sign data set and send the vital sign data set to a central processing unit; the central processing unit is configured to generate a vital sign characteristic data set according to the received vital sign data set and send the vital sign characteristic data set to the grade detection equipment; in response to the received first early warning information sent by the early warning terminal, adjusting each piece of vital sign characteristic data contained in the first early warning information; and the medical adjustment equipment is configured to respond to the received second early warning information sent by the early warning terminal, and adjust each vital sign characteristic data contained in the second early warning information. According to the embodiment, the risk of vital signs is reduced, the response capability of the system is improved, and the safety of the vital signs is improved.

Description

Technical Field

[0001] The embodiments of the present disclosure relate to the field of computer technology, and in particular to a hierarchical early warning system based on multi-parameter vital sign detection. Background Art

[0002] A graded early warning system based on multi-parameter vital signs detection is a technology that provides early warnings based on the vital signs grading results under multi-parameter vital signs detection. Currently, the common method for issuing early warnings based on vital signs grading results is to manually check the risk level of vital signs and manually issue early warnings.

[0003] However, when using the above method to issue early warnings for vital sign classification results, the following technical problems often arise: Manual early warnings often lead to false alarms due to manual inspection errors, which increases the risk of vital signs and reduces the safety of vital signs. The slow speed of manual inspection reduces the responsiveness of the system, thus reducing the safety of vital signs. Summary of the Invention

[0004] The content of this disclosure is used to briefly introduce concepts that will be described in detail in the detailed description section below. The content of this disclosure is not intended to identify key features or essential features of the claimed technical solution, nor is it intended to limit the scope of the claimed technical solution.

[0005] Some embodiments of the present disclosure propose a hierarchical early warning system based on multi-parameter vital sign detection to solve the technical problems mentioned in the above background technology section.

[0006] In a first aspect, some embodiments of the present disclosure provide a graded early warning system based on multi-parameter vital signs detection, the graded early warning system comprising: the above-mentioned monitor device is configured to: collect a vital signs data set, and send the above-mentioned vital signs data set to a central processing unit; the above-mentioned central processing unit is configured to: generate a vital signs feature data set based on the received vital signs data set, and send the above-mentioned vital signs feature data set to a grade detection device; the above-mentioned grade detection device is configured to: perform grade information detection on the received vital signs feature data set to generate a vital signs feature data grade information set, and send the above-mentioned vital signs feature data grade information set to a grade processing device; the above-mentioned grade processing device is configured to: perform grade report generation on the received vital signs feature data grade information set to generate vital signs feature data, etc. level information group set, and sending the above-mentioned vital signs characteristic data level information group set to the early warning terminal, wherein the above-mentioned vital signs characteristic data level information group set is a collection of a preset number of vital signs characteristic data level information groups of different levels; the above-mentioned early warning terminal is configured to: generate a first early warning message and a second early warning message according to the above-mentioned vital signs characteristic data level information group set, and send the above-mentioned first early warning message to the handheld terminal, and send the above-mentioned second early warning message to the medical adjustment device; the above-mentioned handheld terminal is configured to: in response to receiving the first early warning message sent by the above-mentioned early warning terminal, adjust the various vital signs characteristic data included in the above-mentioned first early warning message; the above-mentioned medical adjustment device is configured to: in response to receiving the second early warning message sent by the above-mentioned early warning terminal, adjust the various vital signs characteristic data included in the above-mentioned second early warning message.

[0007] In a second aspect, some embodiments of the present disclosure provide an electronic device comprising: one or more processors; a storage device storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the concrete construction defect repair system described in any implementation method of the first aspect above.

[0008] In a third aspect, some embodiments of the present disclosure provide a computer-readable medium having a computer program stored thereon, wherein when the program is executed by a processor, the concrete construction defect repair system described in any implementation of the first aspect is implemented.

[0009] The above-described embodiments of the present disclosure have the following beneficial effects: The hierarchical early warning system based on multi-parameter vital sign detection, as implemented in some embodiments of the present disclosure, reduces vital sign risks, improves system responsiveness, and enhances vital sign safety. Specifically, the increased vital sign risks, decreased system responsiveness, and decreased vital sign safety are caused by the fact that manual early warnings often result in false warnings due to manual inspection errors, which increases vital sign risks and reduces vital sign safety. The slow speed of manual inspection reduces system responsiveness, which in turn reduces vital sign safety. Based on this, some embodiments of the present disclosure provide a hierarchical early warning system based on multi-parameter vital sign detection. First, to accurately collect vital sign data sets, monitoring equipment is introduced for detection. Specifically, the monitoring equipment is configured to collect the vital sign data sets and transmit the vital sign data sets to a central processing unit. This eliminates the need for manual inspection of the vital sign data, and uses the monitoring equipment for detection, reducing vital sign risks. The central processing unit is then configured to generate a vital sign feature data set based on the received vital sign data set and transmit the vital sign feature data set to a level detection device. Thus, feature extraction can be performed on the vital signs data set, avoiding errors in manual inspection. Afterwards, the above-mentioned level detection device is configured to: perform level information detection on the received vital signs feature data set to generate a vital signs feature data level information set, and send the above-mentioned vital signs feature data level information set to the level processing device. Thus, the level of the vital signs data can be determined by the level detection device, which is convenient for subsequent early warning processing. Secondly, the above-mentioned level processing device is configured to: generate a level report on the received vital signs feature data level information set to generate a vital signs feature data level information group set, and send the above-mentioned vital signs feature data level information group set to the early warning terminal, wherein the above-mentioned vital signs feature data level information group set is a collection of a preset number of vital signs feature data level information groups of different levels. Thus, the system response can be carried out according to the vital signs feature data level information group set, thereby improving the safety of vital signs. The early warning terminal is configured to generate a first early warning message and a second early warning message based on the received set of vital sign characteristic data level information, and to transmit the first early warning message to the handheld terminal and the second early warning message to the medical adjustment device. Thus, the early warning terminal can automatically issue an early warning based on the received set of vital sign characteristic data level information. The handheld terminal is configured to, in response to receiving the first early warning message from the early warning terminal, adjust the individual vital sign characteristic data included in the first early warning message. This can reduce vital sign risks and improve vital sign safety.The medical adjustment device is configured to, in response to receiving the second warning message sent by the warning terminal, adjust the various vital sign characteristic data contained in the second warning message. This adjustment can reduce vital sign risks and improve vital sign safety. This reduces vital sign risks, improves system responsiveness, and enhances vital sign safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The above and other features, advantages, and aspects of the various embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and that components and elements are not necessarily drawn to scale.

[0011] Figure 1 is a schematic diagram of an application scenario of a graded early warning system based on multi-parameter vital sign detection in some embodiments of the present disclosure; Figure 2 is a flow chart of some embodiments of a hierarchical early warning system based on multi-parameter vital sign detection according to the present disclosure; Figure 3 is a schematic structural diagram of an electronic device suitable for implementing some embodiments of the present disclosure. DETAILED DESCRIPTION

[0012] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments described herein. On the contrary, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are for illustrative purposes only and are not intended to limit the scope of protection of the present disclosure.

[0013] It should also be noted that, for ease of description, only the parts related to the invention are shown in the drawings. In the absence of conflict, the embodiments and features in the embodiments of the present disclosure may be combined with each other.

[0014] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0015] It should be noted that the modifications of "one" and "multiple" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, they should be understood as "one or more".

[0016] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0017] The present disclosure will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0018] Figure 1 This is a schematic diagram of an application scenario of a graded warning system based on multi-parameter vital sign detection in some embodiments of the present disclosure.

[0019] exist Figure 1 In the application scenario, first, the hierarchical warning system based on multi-parameter vital signs detection may include: a monitor device 101, a central processing unit 102, a level detection device 103, a level processing device 104, an early warning terminal 105, a handheld terminal 106 and a medical adjustment device 107. First, the above-mentioned monitor device 101 is configured to: collect a vital sign data set, and send the above-mentioned vital sign data set to a central processing unit; then, the above-mentioned central processing unit 102 is configured to: generate a vital sign feature data set based on the received vital sign data set, and send the above-mentioned vital sign feature data set to a level detection device; secondly, the above-mentioned level detection device 103 is configured to: perform level information detection on the received vital sign feature data set to generate a vital sign feature data level information set, and send the above-mentioned vital sign feature data level information set to a level processing device; thirdly, the above-mentioned level processing device 104 is configured to: generate a level report on the received vital sign feature data level information set to generate a vital sign feature data level information set, and send the above-mentioned vital sign feature data level information set to a level processing device. The information group set is sent to the early warning terminal, wherein the above-mentioned vital signs characteristic data level information group set is a collection of a preset number of vital signs characteristic data level information groups of different levels; then, the above-mentioned early warning terminal 105 is configured to: generate a first early warning information and a second early warning information according to the received vital signs characteristic data level information group set, and send the above-mentioned first early warning information to the handheld terminal, and send the above-mentioned second early warning information to the medical adjustment device; thereafter, the above-mentioned handheld terminal 106 is configured to: in response to receiving the first early warning information sent by the above-mentioned early warning terminal, adjust the various vital signs characteristic data contained in the above-mentioned first early warning information; finally, the above-mentioned medical adjustment device 107 is configured to: in response to receiving the second early warning information sent by the above-mentioned early warning terminal, adjust the various vital signs characteristic data contained in the above-mentioned second early warning information.

[0020] It should be noted that the above-mentioned graded warning system based on multi-parameter vital signs detection can be hardware or software. When the computing device is hardware, it can be implemented as a distributed cluster consisting of multiple servers or terminal devices, or it can be implemented as a single server or a single terminal device. When the computing device is embodied as software, it can be installed in the hardware devices listed above. It can be implemented as multiple software or software modules for providing distributed services, for example, or it can be implemented as a single software or software module. No specific limitation is made here. It should be understood that Figure 1 The number of monitoring devices, early warning terminals, handheld terminals and medical adjustment devices in the hierarchical early warning system based on multi-parameter vital signs detection can be any number according to implementation needs.

[0021] Continue to refer Figure 2 , shows a process 200 of some embodiments of a graded warning system based on multi-parameter vital sign detection according to the present disclosure. The graded warning system based on multi-parameter vital sign detection includes: a monitor device, a central processing unit, a level detection device, a level processing device, an early warning terminal, a handheld terminal and a medical adjustment device, and includes the following steps: In step 201 , the monitor device is configured to collect a vital sign data set and send the vital sign data set to a central processing unit.

[0022] In some embodiments, the monitoring device is configured to collect a vital sign data set and send the vital sign data set to a central processing unit.

[0023] Here, the monitor device may be a portable electrocardiogram monitor. The central processing unit may be a server. The vital sign data set may include but is not limited to at least one of the following: respiratory rate data, blood oxygen saturation data, and pulse data.

[0024] As an example, the monitor device may send the vital sign data set to the central processing unit within a certain distance by wireless communication.

[0025] In step 202 , the central processing unit is configured to generate a vital sign feature data set according to the received vital sign data set, and send the vital sign feature data set to the level detection device.

[0026] In some embodiments, the central processing unit is configured to: generate a vital sign feature data set based on the received vital sign data set, and send the vital sign feature data set to the level detection device.

[0027] Here, the above-mentioned vital sign feature data set may include but is not limited to at least one of the following: heart rate variability data, respiratory rhythm abnormality data and blood oxygen saturation fluctuation data.

[0028] Optionally, the central processing unit generates a vital sign feature dataset based on the received vital sign dataset, including: The first step is to filter the above vital sign data set to generate a filtered vital sign data set.

[0029] As an example, the central processing unit may filter at least one electrocardiogram data item included in the vital signs dataset using a low-pass filter to generate a low-pass filtered vital signs dataset. At least one respiratory rate data item included in the vital signs dataset may be filtered using a high-pass filter to generate a high-pass filtered vital signs dataset. At least one blood oxygen saturation data item included in the vital signs dataset may be filtered using a band-pass filter to generate a band-pass filtered vital signs dataset. The low-pass filtered vital signs dataset, the high-pass filtered vital signs dataset, and the band-pass filtered vital signs dataset may be determined as the filtered vital signs dataset.

[0030] In the second step, data denoising is performed on the filtered vital signs dataset to generate a denoised vital signs dataset.

[0031] As an example, the central processing unit may denoise at least one low-pass filtered vital sign data included in the filtered vital sign data set using a wavelet transform denoising algorithm to generate a low-pass denoised vital sign data set. Denoise at least one high-pass filtered vital sign data included in the filtered vital sign data set using a median filter algorithm to generate a high-pass denoised vital sign data set. Denoise at least one band-pass filtered vital sign data included in the filtered vital sign data set using an adaptive filtering algorithm to generate a band-pass denoised vital sign data set. The low-pass denoised vital sign data set, the high-pass denoised vital sign data set, and the band-pass denoised vital sign data set are determined as denoised vital sign data sets.

[0032] The third step is to perform data normalization on the above denoised vital signs dataset to generate a standardized vital signs dataset.

[0033] As an example, the central processing unit may normalize the denoised vital sign dataset to generate a normalized vital sign dataset. Then, the normalized vital sign dataset may be unit-converted to generate a converted vital sign dataset. For example, the unit conversion may involve converting blood pressure data from millimeters of mercury (mmHg) to kilopascals (kPa).

[0034] The fourth step is to perform feature extraction on the above-mentioned standardized vital signs dataset to generate a vital signs feature dataset.

[0035] In step 203 , the level detection device is configured to: perform level information detection on the received vital sign feature data set to generate a vital sign feature data level information set, and send the vital sign feature data level information set to the level processing device.

[0036] In some embodiments, the level detection device is configured to: perform level information detection on the received vital sign feature data set to generate a vital sign feature data level information set, and send the vital sign feature data level information set to the level processing device.

[0037] Here, the level detection device may be a device for classifying vital sign feature data into levels, and the level processing device may be a device for processing level information output by the level detection device.

[0038] Optionally, the level detection device may perform level information detection on the received vital sign feature data set through the following steps to generate a vital sign feature data level information set: According to preset data level conditions, each vital sign feature data in the above vital sign feature data set is graded to generate vital sign feature data grade information, thereby obtaining a vital sign feature data grade information set.

[0039] Here, the above-mentioned preset data level conditions may refer to the pre-set "heart rate data: normal (60-100bpm), mild abnormality (40-59bpm or 101-120bpm), severe abnormality (<40bpm or >120bpm), blood oxygen saturation data: normal (>95%), mild abnormality (90%-95%), severe abnormality (<90%), respiratory rate: normal (12-20 times / minute), mild abnormality (21-25 times / minute), severe abnormality (>25 times / minute), blood pressure data: normal (90-120 / 60-80mmHg), mild abnormality (121-140 / 81-90mmHg), severe abnormality (>140 / 90mmHg)".

[0040] As an example, the level detection device matches each vital sign feature data in the above-mentioned vital sign feature data set with the preset data level condition to generate matching level information as the vital sign feature data level information, and obtains a vital sign feature data level information set.

[0041] In step 204 , the level processing device is configured to generate a level report for the received vital sign feature data level information set to generate a vital sign feature data level information group set, and send the vital sign feature data level information group set to the early warning terminal.

[0042] In some embodiments, the level processing device is configured to generate a level report for the received vital sign feature data level information set to generate a vital sign feature data level information group set, and transmit the vital sign feature data level information group set to the early warning terminal. The vital sign feature data level information group set is a collection of a preset number of vital sign feature data level information groups of different levels.

[0043] Here, the warning terminal may be a device for receiving and displaying warning information. The level report may refer to: Heart rate (HR): Current value: 110 bpm. Level standard: {Normal: 60-100 bpm, Mildly abnormal: 101-120 bpm, Severely abnormal: >120 bpm}. Current level: Mildly abnormal. Blood oxygen saturation (SpO2): Current value: 94%. Level standard: {Normal: >95%, Mildly abnormal: 90%-95%, Severely abnormal: <90%}. Current level: Mildly abnormal. Respiratory rate (RR): Current value: 22 breaths / minute. Level standard: {Normal: 12-20 breaths / minute, Mildly abnormal: 21-25 breaths / minute, Severely abnormal: >25 breaths / minute}. Current level: Mildly abnormal. Blood pressure (BP): Current value: 145 / 95 mmHg. Level: {Normal: 90-120 / 60-80 mmHg, Mildly abnormal: 121-140 / 81-90 mmHg, Severely abnormal: >140 / 90 mmHg}. Current level: Mildly abnormal.

[0044] As an example, the grade processing device may cleanse the vital sign feature data grade information set to generate a cleaned vital sign feature data grade information set. Feature extraction may then be performed on the cleaned vital sign feature data grade information set to generate an extracted vital sign feature data grade information group set. Subsequently, each extracted vital sign feature data grade information group in the extracted vital sign feature data grade information group set may be graded according to a grade standard to generate a vital sign feature data grade information group set, thereby obtaining a vital sign feature data grade information group set.

[0045] In the process of adopting technical solutions to solve the problems mentioned in the background technology, the following problems often arise: Due to the varying risk levels of vital signs, it's easy for high-risk vital signs to not be adjusted promptly, resulting in lower vital sign safety. Risk assessment based solely on single vital sign feature data often fails to accurately identify the risk profile of a vital sign, leading to biased warning results.

[0046] Faced with the above technical problems, the inventors decided to adopt the following solutions: Optionally, the level processing device generates a level report for the received vital sign feature data level information set to generate a vital sign feature data level information group set, and sends the vital sign feature data level information group set to the early warning terminal, including: The first step is to perform format verification on the vital sign feature dataset to generate a verification result set, wherein the verification results in the verification result set represent correct verification results and incorrect verification results.

[0047] As an example, the hierarchical processing device performs data type verification on each vital sign feature data in the vital sign feature data set to generate a verified vital sign feature data type, thereby obtaining a verified vital sign feature data data type set. The data type verification may refer to verifying whether the heart rate data is an integer type, or whether the blood pressure data is a floating point type.

[0048] In a second step, in response to determining that a test result indicating a correct test result exists in the test result set, risk information is determined for each piece of vital sign feature data indicating a correct test result, thereby obtaining a vital sign feature data risk information set. The vital sign feature data risk information in the vital sign feature data risk information set includes vital sign feature data risk score information and vital sign feature data risk category information.

[0049] As an example, the grading processing device may input each vital sign feature data that has been verified as correct into a risk information identification model to obtain a risk information set for the vital sign feature data. Here, the risk information identification model may be a model for scoring the each vital sign feature data. The input to the risk information identification model may be each vital sign feature data. The output may be the risk information set for the vital sign feature data. The risk information identification model may be used to characterize the correspondence between each vital sign feature data and the risk information set for the vital sign feature data. The risk information identification model may sequentially compare each vital sign feature data with multiple sets of preset vital sign feature data in a preset vital sign feature relationship table. The preset vital sign feature relationship table may be created based on analysis of a large number of preset vital sign feature data. Each set of preset vital sign feature data corresponds to a preset vital sign feature data risk information set. The preset vital sign feature data risk information set may be a pre-set vital sign feature data risk information set. The vital sign feature data risk score information may refer to the risk score information for the vital sign feature data. For example, the risk score information for the vital sign feature data may be 9 points. The risk category information for the vital sign feature data may refer to the risk category information for the vital sign feature data. For example, the risk category information for the vital sign feature data may refer to low-risk category information, medium-risk category information, or high-risk category information. The risk information identification model structure includes an input layer, a feature extraction layer, a deep learning layer, a risk assessment layer, and an output layer. The feature extraction layer is used to extract key features from each vital sign feature data. For example, the feature extraction layer extracts the mean and standard deviation of heart rate from each vital sign feature data. The deep learning layer may be used to classify the extracted features. For example, the deep learning layer may be a long short-term memory (LSTM) network. The input layer of the LSTM network receives time series data. The LSTM layer of the LSTM network processes the time series data. The dropout layer of the LSTM network prevents overfitting. The fully connected layer of the LSTM network outputs the risk score and category. The risk assessment layer is used to assess the risk of the output of the deep learning model. It first uses a weighted summation to determine a risk score. Then, based on preset thresholds, the risk score is categorized as low, medium, or high risk. Finally, a risk information set for the vital sign feature data is generated.

[0050] The third step is to fuse the above-mentioned vital signs feature data risk information set with the preset vital signs feature data set to obtain a fused vital signs feature data risk information set.

[0051] Here, the preset vital sign feature data set may refer to a set of preset historical vital sign feature data, for example, a set of preset electrocardiogram feature data, blood oxygen saturation feature data, and respiratory rate feature data.

[0052] As an example, the hierarchical processing device may fuse the above-mentioned vital sign feature data risk information set with a preset vital sign feature data set using a multimodal data fusion algorithm to obtain a fused vital sign feature data risk information set. The multimodal data fusion algorithm may refer to a multimodal fusion network in deep learning.

[0053] The fourth step is to classify the risk category of the above-mentioned fused vital sign feature data risk information set to generate a vital sign feature data risk information group set.

[0054] Here, the above-mentioned vital sign characteristic data risk information group set may refer to a set including a low-risk vital sign characteristic data risk information group, a medium-risk vital sign characteristic data risk information group, and a high-risk vital sign characteristic data risk information group. The above-mentioned risk categories may include low risk, medium risk, and high risk.

[0055] In the fifth step, weighted processing is performed on each vital sign feature data risk information group in the above-mentioned vital sign feature data risk information group set to generate a vital sign feature data risk value, thereby obtaining a vital sign feature data risk value set.

[0056] As an example, the above-mentioned grade processing device may first assign a weight to each vital sign characteristic data risk information group in the above-mentioned vital sign characteristic data risk information group set to generate an assigned vital sign characteristic data risk information group, and obtain an assigned vital sign characteristic data risk information group set. For example, the low risk weight is 1, the medium risk weight is 2, and the high risk weight is 3. Then, by The risk value of each assigned vital sign feature data risk information group in the assigned vital sign feature data risk information group set is determined to generate a vital sign feature data risk value, thereby obtaining a vital sign feature data risk value set. Indicates the risk value of vital signs characteristic data. Represents the risk score. Represents weight.

[0057] In the sixth step, based on the preset first risk category condition, the above-mentioned vital signs feature data risk value set is weighted and adjusted to generate an increased vital signs feature data risk value set.

[0058] Here, the preset first risk category condition may refer to a preset risk category of frequently causing adverse events. For example, the preset first risk category condition may refer to a preset risk category of frequently pausing respiratory rate.

[0059] In the seventh step, based on the preset second risk category conditions, the risk value set of the vital signs characteristic data is weighted down to generate a reduced risk value set of the vital signs characteristic data.

[0060] Here, the preset second risk category condition may refer to a preset risk category in which the early warning is accurate but no adverse events are caused. For example, the preset second risk category condition may refer to a risk category in which the blood oxygen saturation is low.

[0061] In the eighth step, the increased vital sign characteristic data risk value set and the decreased vital sign characteristic data risk value set are determined as the vital sign characteristic data risk value set.

[0062] Here, the above-mentioned determination may refer to merging.

[0063] In the ninth step, the risk value set of the vital signs characteristic data is sorted according to a preset sequence to obtain a risk value sequence of the vital signs characteristic data.

[0064] Here, the above-mentioned preset sequence may refer to a pre-set sequence from small to large.

[0065] In the tenth step, the risk value sequence of the vital sign feature data is graded according to the preset grade intervals to generate a grade set of the vital sign feature data after the grade division, which serves as the vital sign feature data grade information set.

[0066] Here, the preset level interval may refer to a preset risk level interval. For example, the preset level interval may refer to a preset interval of “low risk: (0, 3), medium risk (3, 7), high risk (7, 10)”.

[0067] The relevant contents in the first to tenth steps mentioned above serve as an inventive point of the present disclosure, and solve the technical problem mentioned below: "causing low safety of vital signs and deviation in early warning results". The factors that lead to low safety of vital signs and deviation in early warning results are often as follows: Due to the different risk levels of vital signs, it is easy for vital signs with high risk levels to not be adjusted in time, resulting in low safety of vital signs. Risk judgment based only on a single vital sign feature data is often unable to accurately identify the risk situation of vital signs, resulting in deviation in early warning results. If the above factors are solved, the effect of improving the safety of vital signs and reducing the deviation of early warning results can be achieved. In order to achieve this effect, first, the format of the above vital sign feature data set is checked to generate a test result set, wherein the test results in the above test result set represent correct test results and incorrect test results. In this way, it can be ensured that there are no missing values ​​and data in the wrong format in the data, avoiding misjudgment due to incomplete data. Next, in response to determining that a test result indicating a correct test result exists in the test result set, risk information is determined for each vital sign feature data item indicating a correct test result, resulting in a vital sign feature data risk information set. The vital sign feature data risk information in the vital sign feature data risk information set includes vital sign feature data risk score information and vital sign feature data risk category information. This allows for timely identification of potential risks, improved system responsiveness, and enhanced vital sign safety. Next, the vital sign feature data risk information set is fused with a preset vital sign feature data set to obtain a fused vital sign feature data risk information set. This allows for the integration of data from different sources to comprehensively reflect the patient's vital signs. Subsequently, the fused vital sign feature data risk information set is classified by risk category to generate a vital sign feature data risk information group set. This allows for more rapid identification and treatment of high-risk patients through risk category classification. Next, each vital sign characteristic data risk information group in the above-mentioned vital sign characteristic data risk information group set is weighted to generate a vital sign characteristic data risk value, thereby obtaining a vital sign characteristic data risk value set. Secondly, according to the preset first risk category condition, the above-mentioned vital sign characteristic data risk value set is weighted to increase the weight to generate an increased vital sign characteristic data risk value set. In this way, the deviation of the early warning result can be reduced. Thirdly, according to the preset second risk category condition, the above-mentioned vital sign characteristic data risk value set is weighted to decrease the weight to generate a decreased vital sign characteristic data risk value set. Then, the above-mentioned increased vital sign characteristic data risk value set and the above-mentioned decreased vital sign characteristic data risk value set are determined as the vital sign characteristic data risk value set. Next, the above-mentioned vital sign characteristic data risk value set is sorted in a preset sequence to obtain a vital sign characteristic data risk value sequence.Thus, categorizing risk values ​​into different levels provides an intuitive understanding of the severity of a patient's condition, improving the safety of vital signs. Finally, the risk value sequence of the vital sign feature data is classified according to preset level intervals to generate a set of divided vital sign feature data levels, which serves as the vital sign feature data level information set. This improves the safety of vital signs and reduces bias in warning results.

[0068] Step 205: The warning terminal is configured to generate first warning information and second warning information according to the received vital sign characteristic data level information set, and send the first warning information to the handheld terminal and the second warning information to the medical adjustment device.

[0069] In some embodiments, the early warning terminal is configured to: generate first early warning information and second early warning information based on the received vital sign feature data level information set, and send the above-mentioned first early warning information to the handheld terminal, and send the above-mentioned second early warning information to the medical adjustment device.

[0070] Here, the handheld terminal may refer to a tablet computer, and the medical adjustment device may refer to a ventilator. For example, the medical adjustment device may refer to a Mindray SV300 ventilator.

[0071] Optionally, the early warning terminal generates first early warning information and second early warning information according to the received vital sign feature data level information set, including: In the first step, early warning information is generated for the vital sign characteristic data level information groups that meet the preset first level conditions, thereby obtaining first early warning information.

[0072] Here, the preset first-level conditions may include "heart rate (HR): >101 bpm or <120 bpm, blood oxygen saturation (SpO2): <95% and greater than 90%, respiratory rate (RR): <25 breaths / minute and greater than 21 breaths / minute, blood pressure (BP): systolic pressure >121 mmHg or diastolic pressure >81 mmHg." The first warning message indicates a mild abnormality. For example, the first warning message may read "Mild abnormality!"

[0073] In the second step, warning information is generated for the vital sign characteristic data level information groups that meet the preset second level conditions, thereby obtaining second warning information.

[0074] Here, the preset second-level condition may be "heart rate (HR): >120 bpm, blood oxygen saturation (SpO2): <90%, respiratory rate (RR): >25 breaths / minute, blood pressure (BP): systolic pressure >140 mmHg or diastolic pressure >90 mmHg." The second warning message indicates a severe abnormality. For example, the second warning message may be "Severe abnormality!"

[0075] In the process of adopting technical solutions to solve the problems mentioned in the background technology, the following problems often arise: Manual early warning may cause data processing delays, which reduces the system's responsiveness, resulting in untimely adjustments to medical equipment and reduced safety of vital signs.

[0076] Faced with the above technical problems, the inventors decided to adopt the following solutions: Optionally, the early warning terminal generates first early warning information and second early warning information according to the received vital sign feature data level information set, including: The first step is to label the above vital sign feature data level information set with identification information to obtain a labeled vital sign feature data level information set.

[0077] Here, the identification information may refer to identifier information. For example, the identification information may refer to patient ID information.

[0078] As an example, the early warning terminal can use a labeling tool to label the above-mentioned vital sign feature data level information group set with identification information to obtain a labeled vital sign feature data level information group set. The labeled vital sign feature data level information group in the labeled vital sign feature data level information group set can refer to a collection of information including the patient's vital sign feature data and its corresponding risk level. For example, the labeled vital sign feature data level information group set can refer to the vital sign data of patient 001 {heart rate: 110bpm (mild abnormality), blood oxygen saturation: 94% (mild abnormality), respiratory rate: 22 times / minute (mild abnormality), blood pressure: 145 / 95mmHg (mild abnormality)}.

[0079] In the second step, the detection time information corresponding to the above-mentioned annotated vital sign feature data level information set is determined to obtain a vital sign detection time information set.

[0080] Here, the detection time information may refer to the time information of the vital sign characteristic data registration information group after the detection and annotation. For example, the detection time information may refer to 5:30 p.m. on June 10, 2025.

[0081] The third step is to match the annotated vital sign feature data level information set with the preset first level information set to obtain a first matching result, wherein the first matching result includes: a level information matching consistent result and a level information matching inconsistent result.

[0082] Here, the above-mentioned preset first-level information set may refer to the pre-set "heart rate: 101-120bpm (mild abnormality), blood oxygen saturation: 90%-95% (mild abnormality), respiratory rate: 21-25 times / minute (mild abnormality), blood pressure: 121-140 / 81-90mmHg (mild abnormality)".

[0083] In the fourth step, in response to determining that there is a first matching result in the first matching result set that is a level information matching inconsistent result, the difference between the above-mentioned vital sign detection time information set and the above-mentioned preset time difference information is determined to obtain a time information difference.

[0084] Here, the preset time difference information may refer to a preset maximum time difference. For example, the preset time difference information may be 5 minutes. The time information difference value may refer to the difference between the current detection time and the preset time difference. For example, the current detection time may be 5:36 p.m. on June 10, 2025. In this case, the time information difference value is 1 minute.

[0085] In the fifth step, in response to determining that the time information difference is a preset first numerical condition, a first warning message is sent to the handheld terminal.

[0086] Here, the preset first numerical condition may refer to a pre-set numerical value being a positive number. For example, the time information difference of 1 minute satisfies the preset first numerical condition.

[0087] Step 6: In response to determining that the time information difference is a preset second numerical condition, sending a second warning message to the medical adjustment device.

[0088] Here, the preset second numerical condition may refer to a preset value being a negative number. For example, the time information difference of -2 minutes satisfies the preset second numerical condition.

[0089] Step 7: Match the annotated vital sign feature data level information set with the preset second level information set to obtain a second matching result, wherein the second matching result includes: a level information matching consistent result and a level information matching inconsistent result.

[0090] Here, the above-mentioned preset second-level information set may refer to the pre-set "heart rate: >120bpm (severe abnormality), blood oxygen saturation: <90% (severe abnormality), respiratory rate: >25 times / minute (severe abnormality), blood pressure: >140 / 90mmHg (severe abnormality)".

[0091] In step 8, in response to determining that a second matching result in the second matching result set is a level information matching inconsistent result, a second warning message is sent to the medical adjustment device according to the vital sign detection time information set and the preset time difference information.

[0092] As an example, the warning terminal may subtract the vital sign detection time information set from the preset time difference information to obtain a time difference, and then send the time difference to the medical adjustment device and send the second warning information to the medical adjustment device.

[0093] The relevant contents in the above-mentioned first to eighth steps serve as an inventive point of the present disclosure, and solve the following technical problem: "The responsiveness of the system is reduced, and the safety of vital signs is low." The factors that lead to the reduction of the responsiveness of the system, the untimely adjustment of the medical adjustment equipment, and the reduction of the safety of vital signs are often as follows: manual early warning may cause data processing delays, which reduces the responsiveness of the system, thereby causing the untimely adjustment of the medical adjustment equipment and reducing the safety of vital signs. If the above-mentioned factors are solved, the responsiveness of the system can be improved and the safety of vital signs can be improved. In order to achieve this effect, first, the identification information of the above-mentioned vital signs feature data level information group set is annotated to obtain the annotated vital signs feature data level information group set. This can provide convenience for subsequent processing. Then, the detection time information corresponding to the above-mentioned annotated vital signs feature data level information group set is determined to obtain the vital signs detection time information set. This can provide time information for subsequent time difference calculation. Afterwards, the annotated vital sign feature data level information set is matched with a preset first level information set to obtain a first matching result, wherein the first matching result includes a level information matching consistency result and a level information matching inconsistency result. This allows identification of abnormalities in the data. Next, in response to determining that a first matching result in the first matching result set is a level information matching inconsistency result, the vital sign detection time information set is subtracted from the preset time difference information to obtain a time information difference. This time information difference can be provided for subsequent generation of warning information. Furthermore, in response to determining that the time information difference meets a preset first numerical condition, a first warning message is sent to the handheld terminal. This improves the system's responsiveness, thereby enhancing the safety of vital signs. In response to determining that the time information difference meets a preset second numerical condition, a second warning message is sent to the medical adjustment device. This improves the system's responsiveness, thereby enhancing the safety of vital signs. Next, the annotated vital sign feature data level information set is matched with a preset second level information set to obtain a second matching result, wherein the second matching result includes: a level information matching consistent result and a level information matching inconsistent result. This allows for the identification of serious anomalies in the data and timely processing of the data, thereby improving the system's responsiveness and thereby enhancing the safety of vital signs. Finally, in response to determining that a second matching result in the second matching result set is a level information matching inconsistent result, a second warning message is transmitted to the medical adjustment device based on the vital sign detection time information set and the preset time difference information. This improves the system's responsiveness and enhances the safety of vital signs.

[0094] Step 206: The handheld terminal is configured to: in response to receiving the first warning information sent by the warning terminal, adjust each vital sign characteristic data included in the first warning information.

[0095] In some embodiments, the handheld terminal is configured to: in response to receiving the first warning information sent by the warning terminal, adjust each vital sign characteristic data included in the first warning information.

[0096] Optionally, in response to receiving the first warning information sent by the warning terminal, the handheld terminal adjusts each vital sign characteristic data included in the first warning information, including: The first step is to display the first warning information in a pop-up window.

[0097] In the second step, in response to determining that the handheld terminal user clicks on the pop-up window, the vital sign status of each vital sign feature data included in the first warning information is determined to obtain the vital sign status.

[0098] The handheld terminal user may refer to a user who operates the handheld terminal. For example, the handheld terminal user may refer to a medical worker. The vital sign status may refer to the health status of a patient's vital signs, for example, the vital sign status may refer to a normal state of a patient's vital signs and an abnormal state of a patient's vital signs.

[0099] In the third step, in response to determining that the above-mentioned vital sign status represents an abnormal vital sign status, parameter detection is performed on the above-mentioned each vital sign characteristic data to generate a parameter detection result set.

[0100] As an example, the handheld terminal determines the vital sign parameters of each of the aforementioned vital sign feature data to generate a parameter detection result set. The vital sign parameters may include, but are not limited to, at least one of the following: a heart rate parameter and a blood oxygen saturation parameter. For example, the handheld terminal may remotely detect the heart rate parameter of an electrocardiogram monitor. The handheld terminal may also remotely detect the blood oxygen saturation parameter of an oximeter.

[0101] In the fourth step, parameter adjustment is performed on the vital sign characteristic data corresponding to at least one parameter detection result representing an abnormal parameter result in the parameter detection result set to obtain an adjusted vital sign characteristic data set.

[0102] As an example, the handheld terminal adjusts the vital sign characteristic data corresponding to at least one parameter detection result representing an abnormal parameter result in the parameter detection result set by remotely adjusting the electrocardiogram monitor and the oximeter to obtain an adjusted vital sign characteristic data set.

[0103] Step 207: The medical adjustment device is configured to: in response to receiving the second warning information sent by the warning terminal, adjust each vital sign characteristic data included in the second warning information.

[0104] In some embodiments, the medical adjustment device is configured to: in response to receiving the second warning information sent by the warning terminal, adjust each vital sign characteristic data included in the second warning information.

[0105] Optionally, in response to receiving the second warning information sent by the warning terminal, the medical adjustment device adjusts each vital sign characteristic data included in the second warning information, including: In the first step, for each vital sign characteristic data included in the second warning information, the following steps are performed: The first sub-step is, in response to determining that the vital sign characteristic data is respiratory rate data, adjusting the respiratory rate parameters of the vital sign characteristic data to generate adjusted respiratory rate characteristic data.

[0106] As an example, in response to determining that the vital sign characteristic data is respiratory rate data, a respiratory rate parameter is adjusted on the vital sign characteristic data using a ventilator to generate adjusted respiratory rate characteristic data.

[0107] The second sub-step is, in response to determining that the vital sign characteristic data is infusion rate data of an infusion pump, adjusting the infusion rate parameters of the vital sign characteristic data to generate adjusted infusion rate characteristic data.

[0108] As an example, in response to determining that the vital sign characteristic data is infusion rate data of an infusion pump, the infusion pump is used to adjust the infusion rate parameters of the vital sign characteristic data to generate adjusted infusion rate characteristic data.

[0109] The third sub-step is, in response to determining that the vital sign characteristic data is blood oxygen saturation data, adjusting the blood oxygen saturation parameters of the vital sign characteristic data to generate adjusted blood oxygen saturation characteristic data.

[0110] As an example, in response to determining that the vital sign characteristic data is blood oxygen saturation data, the blood oxygen saturation parameter of the vital sign characteristic data is adjusted using a blood oximeter to generate adjusted blood oxygen saturation characteristic data.

[0111] The fourth sub-step is, in response to determining that the vital sign characteristic data is heart rate data, adjusting the heart rate parameters of the vital sign characteristic data to generate adjusted heart rate characteristic data.

[0112] As an example, in response to determining that the vital sign characteristic data is heart rate data, the heart rate parameters of the vital sign characteristic data are adjusted using an electrocardiogram monitor to generate adjusted heart rate characteristic data.

[0113] In the second step, the obtained adjusted respiratory rate feature data set, adjusted infusion rate feature data set, adjusted blood oxygen saturation feature data set and adjusted heart rate feature data set are determined as the adjusted vital sign feature data set.

[0114] Reference below Figure 3 , which shows a schematic structural diagram of an electronic device (such as a computing device) suitable for implementing some embodiments of the present disclosure. Figure 3 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure. Figure 3 As shown, the computer device includes a processor, a memory and a network interface connected via a system bus, wherein the memory may include a non-volatile storage medium and an internal memory. The non-volatile storage medium can store an operating system and a computer program. The computer program includes program instructions, which, when executed, can enable the processor to execute any of the above-mentioned systems. The processor is used to provide computing and control capabilities to support the operation of the entire computer device. The internal memory provides an environment for the operation of the computer program in the non-volatile storage medium, which, when executed by the processor, can enable the processor to execute any of the above-mentioned systems. The network interface is used for network communication, such as sending assigned tasks, etc. Those skilled in the art will understand that Figure 3 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present disclosure, and does not constitute a limitation on the computer device to which the solution of the present disclosure is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0115] It should be understood that the processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0116] In one embodiment, the processor is configured to run a computer program stored in a memory to implement the following steps: the monitor device is configured to collect a vital sign data set and send the vital sign data set to a central processing unit; the central processing unit is configured to generate a vital sign feature data set based on the received vital sign data set and send the vital sign feature data set to a level detection device; the level detection device is configured to perform level information detection on the received vital sign feature data set to generate a vital sign feature data level information set and send the vital sign feature data level information set to a level processing device; the level processing device is configured to generate a level report on the received vital sign feature data level information set to generate a vital sign feature data level information set. The above-mentioned vital signs characteristic data level information group set is sent to the early warning terminal, wherein the above-mentioned vital signs characteristic data level information group set is a collection of a preset number of vital signs characteristic data level information groups of different levels; the above-mentioned early warning terminal is configured to: generate a first early warning message and a second early warning message according to the received vital signs characteristic data level information group set, and send the above-mentioned first early warning message to the handheld terminal, and send the above-mentioned second early warning message to the medical adjustment device; the above-mentioned handheld terminal is configured to: in response to receiving the first early warning message sent by the above-mentioned early warning terminal, adjust the various vital signs characteristic data included in the above-mentioned first early warning message; the above-mentioned medical adjustment device is configured to: in response to receiving the second early warning message sent by the above-mentioned early warning terminal, adjust the various vital signs characteristic data included in the above-mentioned second early warning message.

[0117] An embodiment of the present disclosure also provides a computer-readable storage medium, on which a computer program is stored. The computer program includes program instructions. The system implemented when the program instructions are executed can refer to the various embodiments of the graded warning system based on multi-parameter vital sign detection described above in the present disclosure.

[0118] The computer-readable storage medium may be an internal storage unit of the computer device described in the aforementioned embodiment, such as a hard disk or memory of the computer device. The computer-readable storage medium may also be an external storage device of the computer device, such as a plug-in hard disk, a SmartMedia Card (SMC), a Secure Digital (SD) card, a flash memory card, etc., provided on the computer device.

[0119] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, system, article, or system comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, system, article, or system. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, system, article, or system comprising the element.

[0120] The above descriptions are merely some preferred embodiments of the present disclosure and illustrate the underlying technical principles. Those skilled in the art should understand that the scope of the invention encompassed by the embodiments of the present disclosure is not limited to technical solutions formed by specific combinations of the aforementioned technical features. It also encompasses other technical solutions formed by any combination of the aforementioned technical features or their equivalents, without departing from the aforementioned inventive concept. For example, a technical solution formed by replacing the aforementioned features with (but not limited to) technical features with similar functions disclosed in the embodiments of the present disclosure.

Claims

1. A hierarchical early warning system based on multi-parameter vital signs detection, characterized in that: The hierarchical warning system includes: a monitor device, a central processing unit, a level detection device, a level processing device, a warning terminal, a handheld terminal and a medical adjustment device, wherein: The monitor device is configured to: collect a vital sign data set, and send the vital sign data set to a central processing unit; The central processing unit is configured to: generate a vital sign feature data set based on the received vital sign data set, and send the vital sign feature data set to the level detection device; The level detection device is configured to: perform level information detection on the received vital sign feature data set to generate a vital sign feature data level information set, and send the vital sign feature data level information set to the level processing device; The level processing device is configured to: generate a level report for the received vital sign feature data level information set to generate a vital sign feature data level information group set, and send the vital sign feature data level information group set to the early warning terminal, wherein the vital sign feature data level information group set is a collection of a preset number of vital sign feature data level information groups of different levels; The early warning terminal is configured to: generate first early warning information and second early warning information according to the received vital sign characteristic data level information set, and send the first early warning information to the handheld terminal, and send the second early warning information to the medical adjustment device; The handheld terminal is configured to: in response to receiving the first warning information sent by the warning terminal, adjust each vital sign characteristic data included in the first warning information; The medical adjustment device is configured to adjust each vital sign characteristic data included in the second warning information in response to receiving the second warning information sent by the warning terminal.

2. The hierarchical warning system according to claim 1, characterized in that: The level detection device is further configured to: According to preset data level conditions, each vital sign feature data in the vital sign feature data set is graded to generate vital sign feature data grade information, thereby obtaining a vital sign feature data grade information set.

3. The hierarchical warning system according to claim 1, characterized in that: The early warning terminal is further configured to: Generating early warning information for the vital sign characteristic data level information groups that meet the preset first level conditions, to obtain first early warning information; Early warning information is generated for the vital sign characteristic data level information groups that meet the preset second level conditions, to obtain second early warning information.

4. The hierarchical warning system according to claim 1, characterized in that: The central processing unit is further configured to: performing filtering processing on the vital sign data set to generate a filtered vital sign data set; performing data denoising on the filtered vital sign dataset to generate a denoised vital sign dataset; performing data normalization on the denoised vital sign dataset to generate a standardized vital sign dataset; Feature extraction is performed on the standardized vital sign dataset to generate a vital sign feature dataset.

5. The hierarchical warning system according to claim 1, characterized in that: The handheld terminal is further configured to: Displaying the first warning information in a pop-up window; In response to determining that the handheld terminal user clicks on the pop-up window, determining the vital sign status of each vital sign feature data included in the first warning information to obtain the vital sign status; In response to determining that the vital sign state represents an abnormal vital sign state, performing parameter detection on each vital sign characteristic data to generate a parameter detection result set; Parameter adjustment is performed on vital sign feature data corresponding to at least one parameter detection result representing an abnormal parameter result in the parameter detection result set to obtain an adjusted vital sign feature data set.

6. The hierarchical warning system according to claim 1, characterized in that: The medical adjustment device is further configured to: For each vital sign feature data included in the second warning information, perform the following steps: In response to determining that the vital sign characteristic data is respiratory rate data, performing respiratory rate parameter adjustment on the vital sign characteristic data to generate adjusted respiratory rate characteristic data; In response to determining that the vital sign characteristic data is infusion rate data of an infusion pump, adjusting an infusion rate parameter of the vital sign characteristic data to generate adjusted infusion rate characteristic data; In response to determining that the vital sign characteristic data is blood oxygen saturation data, adjusting the blood oxygen saturation parameter of the vital sign characteristic data to generate adjusted blood oxygen saturation characteristic data; In response to determining that the vital sign characteristic data is heart rate data, performing heart rate parameter adjustment on the vital sign characteristic data to generate adjusted heart rate characteristic data; The obtained adjusted respiratory rate feature data set, adjusted infusion rate feature data set, adjusted blood oxygen saturation feature data set, and adjusted heart rate feature data set are determined as the adjusted vital sign feature data set.

7. An electronic device, characterized in that: include: one or more processors; a storage device having one or more programs stored thereon; When the one or more programs are executed by the one or more processors, the one or more processors implement the hierarchical warning system according to any one of claims 1 to 6.

8. A computer-readable medium, characterized in that A computer program is stored thereon, wherein when the computer program is executed by a processor, the hierarchical warning system according to any one of claims 1 to 6 is implemented.

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