Wireless remote patient health state monitoring system for infectious disease department

Abstract

The invention provides a wireless remote infection department patient health state monitoring system. The system is composed of a data acquisition module, a positioning module, a data transmission module, a server, a positioning alarm module and a vital sign alarm module. The data acquisition module acquires heart rate, blood pressure, oxyhemoglobin saturation and body temperature data of a critically ill patient; the positioning module obtains the real-time position of a critical patient; the data transmission module uploads the data to a server; the server analyzes the data and identifies abnormal conditions; and the positioning alarm module and the vital sign alarm module respectively send alarm signals to the critically ill patient and the medical staff. The system provides comprehensive health monitoring through the modules, ensures comprehensiveness and accuracy of data acquisition, positions the critically ill patient in real time, and reduces the treatment risk. And the server processes and analyzes the data, quickly identifies abnormal conditions, judges whether the critically ill patient exceeds an activity range in combination with the positioning data, and gives an alarm in time. The timeliness and accuracy of medical monitoring are improved, and the safety of critically ill patients is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of medical monitoring, and particularly to a wireless remote health status monitoring system for patients in the infectious disease department. Background Art

[0002] In the modern medical system, the infectious disease department, as a key department for dealing with infectious diseases, undertakes important diagnosis, treatment, and nursing tasks. Due to the special nature of their conditions, critically ill patients in the infectious disease department often need to stay in the hospital for a long time for close observation and necessary medical interventions. However, long-term hospitalization brings many inconveniences and psychological pressures to critically ill patients. On the one hand, critically ill patients are eager to engage in appropriate activities when their physical conditions permit, such as taking a short walk out of the ward to promote blood circulation and relieve psychological pressure, or going to medical technology departments for necessary examinations such as CT scans. These activities are of positive significance for improving the physical and mental health of critically ill patients and accelerating the recovery process. On the other hand, long-term bed rest may not only lead to physiological problems such as muscle atrophy and poor blood circulation, but also exacerbate the loneliness and anxiety of critically ill patients, which are not conducive to the stability and recovery of the condition. Therefore, on the premise of ensuring safety, appropriately increasing the autonomous activity time of critically ill patients has become an important way to improve the treatment experience and treatment effect.

[0003] However, the traditional medical monitoring mode faces significant challenges when dealing with the activities of critically ill patients in the infectious disease department outside the ward area. Once a critically ill patient leaves the ward area, it is often difficult for medical staff to grasp the health status of the critically ill patient, including but not limited to the fluctuations of vital signs (such as heart rate, blood pressure, blood oxygen saturation, etc.). At the same time, the lack of location information of critically ill patients also makes it difficult to respond quickly in case of emergencies, increasing medical risks. In addition, due to the lack of continuous monitoring of the activity status of critically ill patients, it is difficult for medical staff to evaluate the physical load, emotional changes of critically ill patients, and whether they follow medical advice for activities, and these factors are crucial for formulating and adjusting treatment plans. Summary of the Invention

[0004] The present invention aims to at least solve the technical problem that it is often difficult for medical staff to grasp the health status of critically ill patients after they leave the ward area in the prior art, and particularly innovatively provides a wireless remote health status monitoring system for patients in the infectious disease department.

[0005] To achieve the above object of the present invention, the present invention provides a wireless remote health status monitoring system for patients in the infectious disease department, and the system includes:

[0006] A data acquisition module, which is set on the critically ill patient and is used to collect the heart rate data, blood pressure data, blood oxygen saturation data, and body temperature data of the critically ill patient;

[0007] A positioning module, which is set on critically ill patients and is used to obtain the positioning data of critically ill patients in real time;

[0008] A data transmission module, which is connected to the data acquisition module and the positioning module, and is used to upload the positioning data, heart rate data, blood pressure data, blood oxygen saturation data and body temperature data to the server;

[0009] A server, which is wirelessly communicatively connected to the data acquisition module and the positioning module, and is used to analyze the vital sign data of critically ill patients based on the heart rate data, blood pressure data, blood oxygen saturation data and body temperature data, and identify abnormal conditions based on the vital sign data; The server is also used to set the activity range of critically ill patients, and use the positioning data and the activity range to judge whether the critically ill patients exceed the set activity range, and if so, send an alarm;

[0010] A positioning alarm module, which is connected to the server, and is used to send alarm signals to critically ill patients and medical staff respectively when the critically ill patients exceed the set activity range;

[0011] A vital sign alarm module, which is connected to the server, and is used to send alarm information to medical staff when the server identifies an abnormal condition.

[0012] As an optional embodiment of the present invention, optionally, the system further includes a call module, and the call module is used to perform a remote call function with medical staff.

[0013] As an optional embodiment of the present invention, optionally, the system further includes an encryption module, and the encryption module is used to perform encryption processing on the positioning data, heart rate data, blood pressure data, blood oxygen saturation data and body temperature data.

[0014] As an optional embodiment of the present invention, optionally, the encryption module uses an encryption algorithm for the transmitted data;

[0015] The encryption algorithm includes:

[0016] S1. Use the key generation algorithm of the multilinear mapping e: to generate a public-private key pair (pk, sk), where the public key the private key sk = x, x represents the private key factor, G1, G2, G T represents a cyclic group, g represents a generator, and e(g, g) represents the output of the multilinear mapping e under a specific input, represents repeating the generator g n times;

[0017] S2. Divide the plaintext M into m plaintext blocks M1, M2,..., M m , and each plaintext block M irepresented as an element in the cyclic group G1; preprocess the plaintext block using the mapping function f to obtain a new plaintext block M i ′ = f(M i );

[0018] S3. Encrypt the preprocessed plaintext block using the multi - linear mapping and the private key to obtain the ciphertext C;

[0019] S4. Decrypt the ciphertext C using the private key sk = x and part of the information in the public key.

[0020] As an alternative embodiment of the present invention, optionally, the expression for encrypting the preprocessed plaintext block using the multi - linear mapping and the private key is:

[0021]

[0022] where e(·,·) represents the multi - linear mapping function, M i ′ represents the preprocessed plaintext block, represents the multi - variable operation in the multi - linear mapping, represents multiplying the x - th powers of M1′, M2′, …, M n ′ in the cyclic group G1, h represents a random element in G2, and r represents a random number used to increase the randomness of the ciphertext;

[0023] The expression for decrypting the ciphertext C using the private key sk = x and part of the information in the public key is:

[0024]

[0025] As an alternative embodiment of the present invention, optionally, the server analyzes the vital sign data of critically ill patients using the trained data analysis model for the heart rate data, blood pressure data, blood oxygen saturation data, and body temperature data;

[0026] Based on the vital sign data, determine whether the critically ill patient is in a normal state;

[0027] If the judgment result is that the critically ill patient is in an abnormal state, trigger the alarm mechanism and send the abnormal information and the location information of the critically ill patient to the medical staff through the vital sign alarm module.

[0028] As an alternative embodiment of the present invention, optionally, the analysis of the heart rate data, blood pressure data, blood oxygen saturation data, and body temperature data by the data analysis model includes:

[0029] Preprocess the heart rate data, blood pressure data, blood oxygen saturation data, and body temperature data respectively;

[0030] Extract the time - series data features of the heart rate data, blood pressure data, blood oxygen saturation data, and body temperature data;

[0031] Use the LSTM layer of the data analysis model to reconstruct the test data and calculate the reconstruction error;

[0032] Set a threshold based on the distribution of the reconstruction error. When the reconstruction error exceeds the threshold, the data segment is abnormal.

[0033] As an optional embodiment of the present invention, optionally, the expression for calculating the reconstruction error is:

[0034] h t = LSTM(X t ,h t-1 )

[0035] y t = W o h t + b o

[0036]

[0037] where h t represents the hidden state of the LSTM layer at time step t, X t represents the input feature vector at time step t, y t represents the predicted output of the LSTM layer at time step t, W o represents the weight of the output layer, b o represents the bias of the output layer, e t represents the reconstruction error, represents the reconstruction output at time step t.

[0038] As an optional embodiment of the present invention, optionally, the data acquisition module includes:

[0039] A heart rate monitoring bracelet, which is set on the wrist of a critically ill patient and is used to monitor the heart rate data of the critically ill patient in real - time;

[0040] A blood pressure monitoring cuff, which is set on the upper arm or wrist of a critically ill patient and is used to monitor the blood pressure data of the critically ill patient in real - time;

[0041] A blood oxygen saturation finger clip, which is set on the finger of a critically ill patient and is used to monitor the blood oxygen saturation data in real - time;

[0042] An intelligent thermometer, which is set on the finger of a critically ill patient and is used to measure the body temperature data of the critically ill patient in real - time.

[0043] As an optional embodiment of the present invention, optionally, the heart rate monitoring bracelet includes:

[0044] A bracelet body, which is set on the wrist of a critically ill patient;

[0045] An adjustment strap, which is set on the bracelet body;

[0046] A heart rate monitoring sensor, which is set on the inner side of the bracelet body and is used for collecting the heart rate data of a critically ill patient in real time;

[0047] The blood pressure monitoring cuff includes:

[0048] A cuff body;

[0049] A blood pressure monitor, which is set on the cuff body;

[0050] The blood oxygen saturation finger clip includes:

[0051] A lower clip;

[0052] An upper clip, which is movably connected to the lower clip and is used for clamping the finger of a critically ill patient;

[0053] A blood oxygen monitoring sensor, which is set between the upper clip and the lower clip and is used for collecting the blood oxygen saturation data of a critically ill patient in real time;

[0054] A pressure sensor, which is set on the lower clip and is used for obtaining a pressure signal;

[0055] An alarm, which is set on the upper clip and is connected to the pressure sensor. When the pressure sensor obtains the pressure signal, a control signal is sent to the alarm, and the alarm sends out sound and light signals;

[0056] The intelligent thermometer includes:

[0057] A heat preservation finger sleeve, which is set on the finger of a critically ill patient;

[0058] A temperature sensor, which is set on the heat preservation finger sleeve and is used for measuring the body temperature data of a critically ill patient in real time;

[0059] The data transmission module includes:

[0060] Four wireless transmission units, which are respectively set in the heart rate monitoring bracelet, the blood pressure monitoring cuff, the blood oxygen saturation finger clip and the intelligent thermometer and are used for wirelessly transmitting the data collected by each of them to the server.

[0061] The beneficial effects of the present invention are:

[0062] This system provides all-round health status monitoring for critically ill patients in the infectious disease department by integrating data collection, real-time positioning, data encryption and transmission, as well as intelligent analysis and alarm functions. First of all, the data collection module can comprehensively and accurately obtain key vital sign data of critically ill patients, such as heart rate, blood pressure, blood oxygen saturation and body temperature, providing a solid foundation for subsequent analysis by medical staff. The introduction of the positioning module enables medical staff to real-time master the location information of critically ill patients, effectively avoiding potential safety hazards that may occur when critically ill patients go out for activities, thereby reducing the treatment risk.

[0063] The efficient operation of the data transmission module ensures that all data can be transmitted to the server in a timely and secure manner. As the core of data processing and analysis, the server can not only quickly identify abnormal conditions based on vital sign data, but also combine positioning data to determine whether critically ill patients have exceeded the preset activity range, so as to issue an alarm in a timely manner. This function greatly improves the timeliness and accuracy of medical monitoring, providing a strong guarantee for the safety of critically ill patients.

[0064] In addition, the present invention innovatively adds a call module, enabling remote calls between critically ill patients and medical staff, further enhancing the communication and interaction between doctors and patients, and at the same time further ensuring the safety of critically ill patients. The addition of the encryption module is a comprehensive upgrade of data security, encrypting data through advanced encryption algorithms to effectively prevent potential risks such as data leakage.

[0065] Additional aspects and advantages of the present invention will be given in part in the following description, become apparent in part from the following description, or be learned by practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] The above and / or additional aspects and advantages of the present invention will become apparent and be readily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0067] Figure 1 is a structural diagram of the wireless remote health status monitoring system for critically ill patients in the infectious disease department of the present invention.

[0068] Figure 2 is a schematic structural diagram of the heart rate monitoring bracelet of the present invention.

[0069] Figure 3 is a schematic structural diagram of the blood pressure monitoring cuff of the present invention.

[0070] Figure 4 is a schematic structural diagram of the blood oxygen saturation finger clip of the present invention.

[0071] Figure 5 is a schematic structural diagram of the intelligent thermometer of the present invention.

[0072] In the figure: 1, bracelet body; 2, adjusting strap; 3, cuff body; 4, blood pressure monitor; 5, lower clip; 6, upper clip; 7, pressure sensor; 8, alarm; 9, heat preservation finger cot; 10, temperature sensor. Specific implementation mode

[0073] The embodiments of the present invention will be described in detail below. The examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals represent the same or similar elements or elements with the same or similar functions from beginning to end. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention and should not be construed as a limitation of the present invention.

[0074] As Figure 1 shown, a wireless remote health status monitoring system for infectious disease patients includes:

[0075] A data acquisition module, which is arranged on critically ill patients and is used to acquire the heart rate data, blood pressure data, blood oxygen saturation data and body temperature data of critically ill patients;

[0076] As Figures 2 to 5 shown, in this embodiment, the data acquisition module includes a heart rate monitoring bracelet, a blood pressure monitoring cuff, a blood oxygen saturation finger clip and an intelligent thermometer. These acquisition devices are respectively installed on the wrists, upper arms or wrists, and fingers of critically ill patients, and can monitor and acquire the key vital sign data such as the heart rate, blood pressure, blood oxygen saturation and body temperature of critically ill patients in real time. These data are transmitted to the server in real time through the built-in wireless transmission unit, ensuring the timeliness and accuracy of the data.

[0077] A positioning module, which is arranged on critically ill patients and is used to obtain the positioning data of critically ill patients in real time;

[0078] The specific implementation mode of the positioning module can be a GPS locator. The GPS locator is small in size and light in weight, which is convenient for critically ill patients to carry. The GPS locator can obtain the longitude and latitude coordinates of critically ill patients in real time and transmit this information to the server through wireless signals, enabling medical staff to master the specific location of critically ill patients at any time. This function is particularly important when critically ill patients go out for activities or receive special treatments, as it can help medical staff find critically ill patients in time and ensure the safety and treatment effect of critically ill patients. The GPS locator can also be integrated into devices such as a heart rate monitoring bracelet, a blood pressure monitoring cuff, a blood oxygen saturation finger clip or an intelligent thermometer, etc., to achieve multi-functional integration and improve the portability and practicality of the device.

[0079] A data transmission module, which is connected to the data acquisition module and the positioning module and is used to upload the positioning data, heart rate data, blood pressure data, blood oxygen saturation data and body temperature data to the server;

[0080] In this embodiment, the data transmission module includes four wireless transmission sub-modules and a communication general module. The four wireless transmission sub-modules are respectively embedded inside a heart rate monitoring bracelet, a blood pressure monitoring cuff, a blood oxygen saturation finger clip, and a smart thermometer. They are responsible for wirelessly sending the data collected by their respective devices (including heart rate data, blood pressure data, blood oxygen saturation data, and body temperature data) to the communication general module. As the center of data transmission, the communication general module not only receives data from the four wireless transmission sub-modules, but also integrates these data and uploads them to a remote server through a secure communication protocol. Such a design ensures the real-time, integrity, and security of the data, providing medical staff with immediate and accurate health status information of critically ill patients. For the positioning module, when the positioning module is integrated with the data acquisition module, a wireless transmission unit can be shared, or a separate wireless transmission unit can be set up to transmit the positioning data to the communication general module. Such a design not only simplifies the system structure but also improves the efficiency of data transmission.

[0081] A server, wirelessly communicatively connected to the data acquisition module and the positioning module, is used for analyzing the vital sign data of a critically ill patient based on the heart rate data, blood pressure data, blood oxygen saturation data, and body temperature data, and identifying an abnormal condition based on the vital sign data; the server is further used for setting the activity range of the critically ill patient, and using the positioning data and the activity range to determine whether the critically ill patient exceeds the set activity range, and if so, issuing an alarm;

[0082] As Figure 1 shown, specifically, as the core of data processing and analysis, the server not only receives the heart rate data, blood pressure data, blood oxygen saturation data, and body temperature data from the data acquisition module, but also obtains the real-time position information of the critically ill patient through the positioning module. The server is built with an advanced data analysis model, which can quickly identify whether there is an abnormality in the health status of the critically ill patient based on the received vital sign data. For example, when the heart rate data exceeds the normal range, the blood pressure abnormally rises or drops, the blood oxygen saturation is low, or the body temperature is too high, the data analysis model can immediately issue an alarm to prompt medical staff to pay attention to the health status of the critically ill patient.

[0083] Meanwhile, the server also has the function of setting the activity range of the critically ill patient. Medical staff can preset a reasonable activity range on the server according to the specific conditions and treatment needs of the critically ill patient. When the positioning data of the critically ill patient shows that his / her position exceeds this range, the server will also issue an alarm to remind medical staff to pay attention to the whereabouts of the critically ill patient, ensuring the safety and treatment effect of the critically ill patient.

[0084] In addition, the server also undertakes the important tasks of data encryption and storage. To ensure the security of the data of critically ill patients, the server adopts advanced encryption algorithms to encrypt all the received data, effectively preventing potential risks such as data leakage. At the same time, the server also has strong data storage capabilities, capable of storing the historical data of critically ill patients for a long time, providing strong data support for the subsequent analysis and treatment by medical staff.

[0085] The positioning and alarm module, connected to the server, is used to send alarm signals to the critically ill patient and medical staff respectively when the critically ill patient exceeds the set activity range;

[0086] The positioning and alarm module includes an alarm for the critically ill patient and an alarm for medical staff. The alarm for the critically ill patient can be integrated with the data acquisition module. When the critically ill patient exceeds the range set by the server, first the server sends an alarm signal to the alarm for the critically ill patient through the data transmission module, and the alarm for the critically ill patient starts to alarm to remind the critically ill patient to pay attention to their own position and avoid exceeding the preset activity range. At the same time, the alarm for medical staff will also receive the alarm signal, and medical staff can immediately view the specific position information of the critically ill patient and take necessary measures to ensure the safety of the critically ill patient. This two-way alarm mechanism not only enhances the safety awareness of critically ill patients but also improves the timeliness and accuracy of medical staff's monitoring of critically ill patients.

[0087] The vital sign alarm module, connected to the server, is used to send alarm information to medical staff when the server identifies an abnormal condition.

[0088] It should be noted that the vital sign alarm module is closely connected to the server and constantly monitors the vital sign data of critically ill patients analyzed by the server. Once the server identifies through its built-in data analysis model that there are abnormalities in the vital signs of critically ill patients, such as too fast heart rate, too high blood pressure, too low blood oxygen saturation or abnormal body temperature, etc., the vital sign alarm module will be immediately activated. It will quickly send alarm information to medical staff, and this information details the abnormal data of critically ill patients and possible health risks, enabling medical staff to understand the critical condition of critically ill patients in the first time. Such a design greatly shortens the response time of medical staff to the abnormal conditions of critically ill patients, winning precious time for them to take timely treatment measures, thus effectively ensuring the life safety of critically ill patients.

[0089] The monitoring system of this embodiment further includes a display module, which is set at the medical staff side and is used to display the vital sign data, positioning information and alarm information of critically ill patients in real time. The display module can display various data of critically ill patients in an intuitive and clear manner, including key vital signs such as heart rate, blood pressure, blood oxygen saturation, body temperature, etc., as well as the real-time position information of critically ill patients. When the server identifies an abnormal situation or the critically ill patient exceeds the set activity range, the display module will also prominently display the alarm information to remind the medical staff to pay attention immediately and take corresponding measures. Such a design enables the medical staff to quickly master the health status of critically ill patients and ensure that critically ill patients receive timely and effective monitoring and treatment.

[0090] As Figure 1 shown, in summary, the wireless remote health status monitoring system for critically ill patients in the infectious disease department of this embodiment first collects key vital sign data such as heart rate, blood pressure, blood oxygen saturation and body temperature of critically ill patients in real time through the data collection module. These data are important indicators for evaluating the health status of critically ill patients; then, the positioning module is used to obtain the position information of critically ill patients in real time to ensure that critically ill patients are within a safe activity range; next, the data transmission module wirelessly transmits these vital sign data and positioning data to the server. As the core of data processing and analysis, the server quickly identifies abnormal situations and judges whether the critically ill patient has exceeded the preset activity range; once an abnormal or out-of-range situation is identified, the positioning alarm module and the vital sign alarm module will be immediately activated to send alarm signals to the critically ill patient and the medical staff respectively, ensuring that the critically ill patient can receive timely attention and treatment.

[0091] As an optional embodiment of the present invention, optionally, the system further includes a call module, and the call module is used for the remote call function with the medical staff.

[0092] As Figure 1As shown in the figure, the call module includes a call device for critically ill patients and a call device for medical staff. The call device for critically ill patients can be integrated with the data acquisition module and is set on the critically ill patients to facilitate direct communication between the critically ill patients and medical staff when needed. The call device for medical staff is set on the hospital or the mobile device of medical staff and is used to receive and initiate call requests. The call module adopts advanced communication technology to ensure the clarity and stability of calls, and can maintain smooth communication even in an environment with poor signals. This function not only enhances the interaction between critically ill patients and medical staff, but also provides timely medical consultation and psychological support for critically ill patients, further improving the treatment experience and safety of critically ill patients. Specifically, when a critically ill patient feels unwell or needs consultation, a call request can be initiated through the call device for critically ill patients, and the call device for medical staff will immediately receive a prompt, and medical staff can quickly answer and conduct a remote call with the critically ill patient. During the call, medical staff can understand in detail the symptoms, medical history and current environmental conditions of the critically ill patient, and provide targeted medical advice and psychological comfort for the critically ill patient. At the same time, medical staff can also adjust the treatment plan or take necessary rescue measures in a timely manner according to the information obtained during the call to ensure that the critically ill patient receives timely and effective treatment.

[0093] As an optional embodiment of the present invention, optionally, the system further includes an encryption module, and the encryption module is used to encrypt the positioning data, heart rate data, blood pressure data, blood oxygen saturation data and body temperature data.

[0094] It should be noted that the encryption module is set between the data acquisition module, the positioning module, the data transmission module and the server to ensure the security during data transmission and storage. The encryption module adopts encryption algorithms such as AES or RSA to encrypt the positioning data, heart rate data, blood pressure data, blood oxygen saturation data and body temperature data, effectively preventing the risk of data being intercepted or tampered with during transmission. At the same time, the encryption module also has a key management function and can update the key regularly to further improve the data security. Such a design not only protects the privacy of critically ill patients, but also ensures the accuracy and reliability of medical data, providing strong support for the diagnosis and treatment of medical staff.

[0095] As an optional embodiment of the present invention, optionally, the encryption module uses an encryption algorithm for the transmitted data;

[0096] The encryption algorithms include:

[0097] S1. Use the key generation algorithm of the multilinear mapping e: to generate a public-private key pair (pk, sk), where the public key The private key sk = x, where x represents the private key factor, G1, G2, G T represent cyclic groups, g represents the generator, and e(g, g) represents the output of the multilinear map e for a specific input, denotes repeating the generator g n times;

[0098] S2. Divide the plaintext M into m plaintext blocks M1, M2, …, M m , and each plaintext block M i is represented as an element in the cyclic group G1; use the mapping function f to preprocess the plaintext block to obtain a new plaintext block M i ′ = f(M i );

[0099] S3. Encrypt the preprocessed plaintext block using the multilinear map and the private key to obtain the ciphertext C;

[0100] S4. Decrypt the ciphertext C using the private key sk = x and part of the public key.

[0101] As an alternative embodiment of the present invention, optionally, the expression for encrypting the preprocessed plaintext block using the multilinear map and the private key is:

[0102]

[0103] where e(·, ·) represents the multilinear mapping function, M i ′ represents the preprocessed plaintext block, denotes the multivariate operation in the multilinear map, denotes multiplying the x - th powers of M1′, M2′, …, M n ′ in the cyclic group G1, h represents a random element in G2, and r represents a random number used to increase the randomness of the ciphertext;

[0104] The expression for decrypting the ciphertext C using the private key sk = x and part of the public key is:

[0105]

[0106] As an alternative embodiment of the present invention, optionally, the server analyzes the vital sign data of critically ill patients for the heart rate data, blood pressure data, blood oxygen saturation data, and body temperature data through a trained data analysis model;

[0107] Based on the vital sign data, determine whether the critically ill patient is in a normal state;

[0108] If the judgment result is that the critically ill patient is in an abnormal state, an alarm mechanism is triggered, and abnormal information and the location information of the critically ill patient are sent to the medical staff through the vital sign alarm module.

[0109] It should be noted that in this embodiment, the method for training the data analysis model is as follows: First, a large amount of vital sign data of critically ill patients is collected as training samples, and these data cover various normal and abnormal situations. Then, machine learning algorithms such as support vector machines, neural networks, or random forests are used to learn and analyze these training samples to identify the normal range and abnormal patterns of vital sign data. Through continuous iteration and optimization, a trained data analysis model is finally obtained. This model can accurately analyze data such as the heart rate, blood pressure, blood oxygen saturation, and body temperature of critically ill patients to determine whether the critically ill patient is in a normal state. When the model identifies that the critically ill patient is in an abnormal state, it will immediately trigger the alarm mechanism and send detailed abnormal information and the location information of the critically ill patient to the medical staff through the vital sign alarm module. Such a design enables the medical staff to quickly understand the critical condition of the critically ill patient and take timely treatment measures, thus effectively ensuring the life safety of the critically ill patient. At the same time, with the continuous accumulation of data and the continuous optimization of the model, the accuracy and reliability of the data analysis model will be further improved.

[0110] As an alternative embodiment of the present invention, optionally, the analysis of the heart rate data, blood pressure data, blood oxygen saturation data, and body temperature data by the data analysis model includes:

[0111] Preprocess the heart rate data, blood pressure data, blood oxygen saturation data, and body temperature data respectively;

[0112] It should be noted that the preprocessing steps include operations such as cleaning, denoising, and standardizing the original data to improve the accuracy and efficiency of data analysis. The cleaning step is mainly to remove invalid or abnormal data points to ensure the integrity and consistency of the data; the denoising step is to reduce the random fluctuations and interferences in the data to make the data smoother and more stable; the standardizing step is to convert the data to the same scale for subsequent analysis and comparison. The preprocessed data will be input into the data analysis model, and the model will conduct in-depth analysis and mining on these data to extract useful information and features to provide strong support for the diagnosis and treatment of medical staff. Such a preprocessing process not only improves the accuracy and reliability of data analysis but also lays a solid foundation for subsequent data mining and model training.

[0113] Extract the time series data features of the heart rate data, blood pressure data, blood oxygen saturation data, and body temperature data;

[0114] It should be noted that the characteristics of time series data refer to the laws and trends of data such as heart rate, blood pressure, blood oxygen saturation, and body temperature changing over time. By extracting these characteristics, this embodiment can gain a deeper understanding of the health status of critically ill patients and predict possible abnormal situations. For example, changes in heart rate can reflect the exercise state, emotional changes, or changes in cardiac function of critically ill patients; fluctuations in blood pressure can reveal the vascular health status and blood flow conditions of critically ill patients; changes in blood oxygen saturation can reflect the respiratory function and lung health status of critically ill patients; and changes in body temperature can indicate whether there are problems such as infection or inflammation in critically ill patients. The extraction and analysis of these time series data characteristics provide richer information and basis for the diagnosis and treatment of medical staff, enabling them to more accurately judge the condition of critically ill patients and formulate more effective treatment plans.

[0115] Use the LSTM layer of the data analysis model to reconstruct the test data and calculate the reconstruction error;

[0116] It should be noted that the reconstruction error refers to the degree of difference between the reconstructed data and the original data after using the LSTM layer (long short-term memory network layer) of the data analysis model to reconstruct the test data. By calculating the reconstruction error, this embodiment can evaluate the accuracy and generalization ability of the model. When the reconstruction error is small, it indicates that the model can well fit the original data and has high accuracy and reliability; while when the reconstruction error is large, it may mean that there are problems such as overfitting or underfitting in the model, and further optimization and adjustment are needed. Through such a reconstruction and error calculation process, this embodiment can not only further verify and optimize the performance of the data analysis model, but also provide more accurate and reliable support for the diagnosis and treatment of medical staff.

[0117] Set a threshold based on the distribution of the reconstruction error. When the reconstruction error exceeds the threshold, the data segment is abnormal.

[0118] It should be noted that setting a threshold is an important step in data analysis, which can help the system accurately identify abnormal data segments. In this embodiment, based on the distribution of the reconstruction error, a statistical method or empirical rule is used to set a reasonable threshold in this embodiment. When the reconstruction error of a certain data segment exceeds this threshold, the system determines that this data segment is abnormal, which usually means that there are significant changes or fluctuations in the vital sign data of critically ill patients, and may indicate a certain health risk or the onset of a disease. Once an abnormal data segment is identified, the system will immediately trigger an alarm mechanism and send detailed abnormal information and the location information of the critically ill patient to the medical staff through the vital sign alarm module. In this way, the medical staff can quickly understand the critical condition of the critically ill patient and take necessary treatment measures, thus effectively ensuring the life safety of the critically ill patient. At the same time, the identification and analysis of abnormal data segments also provide an important reference basis for the subsequent diagnosis and treatment of medical staff.

[0119] As an alternative embodiment of the present invention, optionally, the expression for calculating the reconstruction error is:

[0120] h t = LSTM(X t , h t-1 )

[0121] y t = W o h t + b o

[0122]

[0123] Wherein, h t represents the hidden state of the LSTM layer at time step t;

[0124] X t represents the input feature vector at time step t;

[0125] y t represents the predicted output of the LSTM layer at time step t;

[0126] W o represents the weight of the output layer;

[0127] b o represents the bias of the output layer;

[0128] e t represents the reconstruction error;

[0129] represents the reconstruction output at time step t.

[0130] As an alternative embodiment of the present invention, optionally, the data acquisition module includes:

[0131] A heart rate monitoring bracelet, which is set on the wrist of a critically ill patient and is used to monitor the heart rate data of the critically ill patient in real time;

[0132] As Figure 2 shown, when in use, the heart rate monitoring bracelet monitors the heart rate changes of the critically ill patient in real time through the built-in sensor, and transmits the collected heart rate data to the data transmission module wirelessly. The bracelet is designed to be lightweight and comfortable to wear, ensuring that the critically ill patient can continuously and accurately monitor the heart rate data during daily activities.

[0133] A blood pressure monitoring cuff, which is set on the upper arm or wrist of a critically ill patient and is used to monitor the blood pressure data of the critically ill patient in real time;

[0134] As Figure 3 shown, when in use, the blood pressure monitoring cuff monitors the blood pressure changes of the critically ill patient in real time through the built-in blood pressure sensor, and sends the collected blood pressure data to the data transmission module wirelessly as well. The cuff is reasonably designed and can fit closely to the skin of the critically ill patient, ensuring the accuracy and stability of the blood pressure data, and at the same time not causing too much discomfort to the critically ill patient. In this embodiment, it is set to detect the blood pressure data of the critically ill patient once every ten minutes to ensure the real-time and reliability of the data, providing strong support for the subsequent diagnosis and treatment of medical staff.

[0135] A blood oxygen saturation finger clip, which is set on the finger of a critically ill patient and is used to monitor the blood oxygen saturation data in real time;

[0136] As Figure 4 shown, when in use, the blood oxygen saturation finger clip is installed on the finger of the critically ill patient, monitors the blood oxygen saturation changes of the critically ill patient in real time through the built-in blood oxygen sensor, and transmits the collected blood oxygen saturation data to the data transmission module wirelessly.

[0137] An intelligent thermometer, which is set on the finger of a critically ill patient and is used to measure the body temperature data of the critically ill patient in real time.

[0138] As Figure 5 shown, when in use, the intelligent thermometer is installed on the finger of the critically ill patient, measures the body temperature changes of the critically ill patient in real time through the built-in temperature sensor, and transmits the collected body temperature data to the data transmission module wirelessly.

[0139] It should be noted that after critically ill patients return to the ward from going out, medical staff can remove the data acquisition module installed on the body of the critically ill patient according to the physical condition of the critically ill patient. After removal, disinfect the data acquisition module for use when the critically ill patient goes out next time to ensure its hygiene and safety. At the same time, the design of the data acquisition module fully considers the comfort and convenience of critically ill patients, enabling critically ill patients to wear it easily during daily activities without causing too much interference to their lives.

[0140] As an optional embodiment of the present invention, optionally, the heart rate monitoring bracelet includes:

[0141] A bracelet body 1, which is set on the wrist of a critically ill patient;

[0142] As Figure 2 shown, the bracelet body 1 is circular, made of a light, soft and skin-friendly material to ensure the comfort of critically ill patients wearing it for a long time. A wireless communication unit is provided on the bracelet body 1, and the wireless communication unit can transmit the collected heart rate data to the server in real time for subsequent data analysis and processing. A power module is also provided on the bracelet body 1 to provide stable power support for the bracelet to ensure the continuity of heart rate monitoring.

[0143] An adjustment strap 2, which is set on the bracelet body 1;

[0144] As Figure 2 shown, the adjustment strap 2 is used to adjust the tightness of the heart rate monitoring bracelet worn on the hand of a critically ill patient to ensure that the bracelet can fit closely to the wrist of the critically ill patient, and at the same time, it will not cause too much pressure on the critically ill patient. Multiple buckle holes are provided on the adjustment strap 2, and users can choose a suitable buckle hole for fixation according to the size of their own wrists, making the wearing of the bracelet more personalized and comfortable.

[0145] A heart rate monitoring sensor, which is set on the inner side of the bracelet body 1 and is used to collect the heart rate data of critically ill patients in real time;

[0146] The heart rate monitoring sensor is installed at the inner side position of the bracelet body 1, and this position can fit closely to the wrist skin of the critically ill patient to ensure the accuracy and stability of the heart rate data. The sensor adopts advanced bioelectric signal acquisition technology, can monitor the heart rate changes of critically ill patients in real time, and transmit the collected heart rate data to the server through the wireless communication unit on the bracelet body 1 in real time. In this way, medical staff can always master the heart rate condition of critically ill patients and provide strong support for subsequent diagnosis and treatment. At the same time, the design of the heart rate monitoring sensor fully considers the comfort and convenience of critically ill patients to ensure that critically ill patients can wear it easily during daily activities without causing too much interference to their lives.

[0147] The blood pressure monitoring cuff includes:

[0148] A cuff body 3;

[0149] As Figure 3 shown, the cuff body 3 is a long strip-shaped structure. When in use, it is installed on the upper arm of critically ill patients to bind the arms of critically ill patients so that the blood pressure monitoring sensor can accurately collect the blood pressure data of critically ill patients. The cuff body 3 is made of a soft and moderately elastic material to ensure the comfort of critically ill patients when wearing. A wireless communication unit is also provided on the cuff body 3, which can transmit the collected blood pressure data to the server in real time for subsequent data analysis and processing.

[0150] A blood pressure monitor 4, which is arranged on the cuff body 3;

[0151] As Figure 3 shown, the blood pressure monitor 4 is used to monitor and analyze the blood pressure data of critically ill patients. The blood pressure monitor 4 is internally provided with a blood pressure sensor and a data processing unit. The blood pressure sensor can monitor the blood pressure changes of critically ill patients in real time and send the collected blood pressure data to the data processing unit for processing and analysis. The data processing unit then processes the blood pressure data, such as filtering and amplifying, to improve the accuracy and stability of the data. Then, the processed blood pressure data is transmitted to the server in real time through the wireless communication unit on the cuff body 3 for subsequent data analysis and processing. Such a design makes blood pressure monitoring more accurate and convenient, providing strong support for the diagnosis and treatment of medical staff. At the same time, the design of the blood pressure monitoring cuff also fully considers the comfort and convenience of critically ill patients, so that critically ill patients will not feel too much discomfort when wearing and can easily carry out daily activities.

[0152] The blood oxygen saturation finger clip includes:

[0153] A lower clip 5;

[0154] An upper clip 6, which is movably connected to the lower clip 5 and is used to clamp the finger of a critically ill patient;

[0155] A blood oxygen monitoring sensor, which is arranged between the upper clip and the lower clip and is used to collect the blood oxygen saturation data of critically ill patients in real time;

[0156] A pressure sensor 7, which is arranged on the lower clip 5 and is used to obtain a pressure signal;

[0157] An alarm 8, which is arranged on the upper clip 6 and is connected to the pressure sensor. When the pressure sensor obtains the pressure signal, it sends a control signal to the alarm 8, and the alarm 8 sends out sound and light signals;

[0158] As Figure 4As shown in the figure, when using the blood oxygen saturation finger clip, open the lower clip 5 and the upper clip 6, place the finger of the critically ill patient between the lower clip 5 and the upper clip 6, and then close the clips so that the blood oxygen monitoring sensor closely fits the finger of the critically ill patient. The blood oxygen monitoring sensor measures the blood oxygen saturation of the critically ill patient by emitting light of a specific wavelength and receiving the transmitted or reflected light, and according to the change in the degree of light absorption.

[0159] During the use of the blood oxygen saturation finger clip, if the blood oxygen saturation finger clip suddenly slips off the finger of the critically ill patient, since the pressure sensor is installed on the lower clip 5, the upper clip 6 will give a pressure signal to the pressure sensor 7. At this time, the pressure sensor 7 sends a control signal to the alarm 8, and the alarm 8 is immediately activated to send out an alarm signal, reminding the critically ill patient to pay attention to the use status of the blood oxygen saturation finger clip and preventing the influence on the accuracy and continuity of data collection due to the slipping of the finger clip. The form of the alarm signal can include various ways such as sound and light flashing to ensure that the critically ill patient can be effectively reminded in a noisy or dimly lit environment. At the same time, the design of the alarm 8 also fully considers the use experience of the critically ill patient, avoiding generating overly harsh or dazzling alarm signals so as not to bring unnecessary panic and discomfort to the critically ill patient.

[0160] The described intelligent thermometer includes:

[0161] A heat preservation finger sleeve 9, which is set on the finger of the critically ill patient;

[0162] As Figure 5 shown in the figure, the heat preservation finger sleeve 9 is fixed on the finger of the critically ill patient by pasting when in use. The heat preservation finger sleeve 9 is made of a material with good heat preservation performance to ensure that the thermometer can accurately measure the body temperature data of the critically ill patient. The design of the heat preservation finger sleeve 9 not only ensures the close contact between the thermometer and the finger of the critically ill patient, but also improves the accuracy and stability of the measurement. At the same time, the material of the heat preservation finger sleeve 9 is soft and skin-friendly, ensuring the comfort of the critically ill patient during long-term wearing.

[0163] A temperature sensor 10, which is set on the heat preservation finger sleeve 9 and is used to measure the body temperature data of the critically ill patient in real time;

[0164] As Figure 5 shown in the figure, the temperature sensor 10 is installed inside the heat preservation finger sleeve 9, can sense the temperature change of the finger of the critically ill patient in real time, and sends the collected body temperature data to the data transmission module wirelessly. The temperature sensor 10 uses a high-precision and high-sensitivity temperature measurement element to ensure the accuracy and stability of body temperature measurement. At the same time, the design of the temperature sensor 10 also fully considers the comfort and convenience of the critically ill patient, enabling the critically ill patient to wear it easily during activities without causing too much interference to their life.

[0165] The data transmission module includes:

[0166] Four wireless transmission units, which are respectively arranged in the heart rate monitoring bracelet, blood pressure monitoring cuff, blood oxygen saturation finger clip and intelligent thermometer, and are used for wirelessly transmitting the data collected by each of them to the server;

[0167] It should be noted that the wireless transmission unit is a low-power and high-performance wireless communication network card. Adopting advanced wireless communication technology, it can transmit the vital sign data collected by the data acquisition module to the server in real time and accurately. The design of the wireless transmission unit fully considers the stability and security of the data, and adopts an encrypted transmission method to ensure that the data is not stolen or tampered with during the transmission process. At the same time, the wireless transmission unit also has the characteristic of low power consumption, which can extend the battery life of the data acquisition module and reduce the replacement of the battery

[0168] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principle and spirit of the present invention. The scope of the present invention is defined by the claims and their equivalents.

Claims

1. A wireless remote health status monitoring system for patients in the infectious disease department, characterized in that, The system includes: A data acquisition module, which is set on the critically ill patient and is used to collect the heart rate data, blood pressure data, blood oxygen saturation data and body temperature data of the critically ill patient; A positioning module, which is set on the critically ill patient and is used to obtain the positioning data of the critically ill patient in real time; A data transmission module, which is connected to the data acquisition module and the positioning module, and is used to upload the positioning data, heart rate data, blood pressure data, blood oxygen saturation data and body temperature data to the server; A server, which is wirelessly communicatively connected to the data acquisition module and the positioning module, and is used to analyze the vital sign data of the critically ill patient according to the heart rate data, blood pressure data, blood oxygen saturation data and body temperature data, and identify abnormal conditions based on the vital sign data; the server is also used to set the activity range of the critically ill patient, and use the positioning data and the activity range to judge whether the critically ill patient exceeds the set activity range, and if so, issue an alarm; A positioning alarm module, which is connected to the server and is used to send alarm signals to the critically ill patient and medical staff respectively when the critically ill patient exceeds the set activity range; A vital sign alarm module, which is connected to the server and is used to send alarm information to medical staff when the server identifies an abnormal condition.

2. The wireless remote health status monitoring system for infectious disease patients according to claim 1, wherein The system further includes a call module, and the call module is used for the remote call function with medical staff.

3. A wireless remote health status monitoring system for patients in the infectious disease department according to claim 1, characterized in that, The system further includes an encryption module, and the encryption module is used to perform encryption processing on the positioning data, heart rate data, blood pressure data, blood oxygen saturation data and body temperature data.

4. The wireless remote health status monitoring system for infectious disease patients according to claim 3, wherein The encryption module uses an encryption algorithm for the transmitted data; The encryption algorithm includes: S1. Generate a public-private key pair (pk, sk) using the key generation algorithm of . Among them, the public key and the private key sk = x, where x represents the private key factor, G1, G2, G T represent cyclic groups, g represents the generator, and e(g, g) represents the output of the multilinear map e under specific inputs. represents repeating the generator g n times; S2. Divide the plaintext M into m plaintext blocks M1, M2, …, M m , where each plaintext block M i is represented as an element in the cyclic group G1; preprocess the plaintext block using the mapping function f to obtain a new plaintext block M i ′ = f(M i ); S3. Use the multilinear mapping and the private key to encrypt the preprocessed plaintext block to obtain the ciphertext C; S4. Use the private key sk = x and part of the information in the public key to decrypt the ciphertext C.

5. The wireless remote health status monitoring system for infectious disease department patients according to claim 4, wherein The expression for encrypting the preprocessed plaintext block using the multilinear mapping and the private key is: Among them, e(·,·) represents a multilinear mapping function, M i ′ represents the preprocessed plaintext block, represents the multivariate operation in the multilinear mapping, represents multiplying the x-th powers of M1′, M2′,..., M n ′ in the cyclic group G1, h represents a random element in G2, and r represents a random number used to increase the randomness of the ciphertext; The expression for decrypting the ciphertext C using the private key sk = x and part of the information in the public key is:

6. The wireless remote health status monitoring system for infectious disease patients according to claim 1, characterized in that, The server analyzes the vital sign data of the critically ill patient through a trained data analysis model for the heart rate data, blood pressure data, blood oxygen saturation data and body temperature data; Judge whether the critically ill patient is in a normal state based on the vital sign data; If the judgment result is that the critically ill patient is in an abnormal state, trigger the alarm mechanism, and send the abnormal information and the location information of the critically ill patient to the medical staff through the vital sign alarm module.

7. The wireless remote health status monitoring system for patients in the infectious disease department according to claim 6, wherein The analysis of the heart rate data, blood pressure data, blood oxygen saturation data and body temperature data by the data analysis model includes: Preprocess the heart rate data, blood pressure data, blood oxygen saturation data and body temperature data respectively; Extract the time series data features of the heart rate data, blood pressure data, blood oxygen saturation data and body temperature data; Use the LSTM layer of the data analysis model to reconstruct the test data and calculate the reconstruction error; Set a threshold based on the distribution of the reconstruction error, and when the reconstruction error exceeds the threshold, the data segment is abnormal.

8. The wireless remote health status monitoring system for infectious disease department patients according to claim 7, characterized in that The expression for calculating the reconstruction error is: h t = LSTM(X t , h t-1 ) y t = W o h t + b o Among them, h t represents the hidden state of the LSTM layer at time step t, X t represents the input feature vector at time step t, y t represents the predicted output of the LSTM layer at time step t, W o represents the weight of the output layer, b o represents the bias of the output layer, e t represents the reconstruction error, represents the reconstruction output at time step t.

9. The wireless remote health status monitoring system for infectious disease patients according to claim 1, wherein, The data acquisition module includes: A heart rate monitoring bracelet, which is set on the wrist of a critically ill patient and is used to monitor the heart rate data of the critically ill patient in real time; A blood pressure monitoring cuff, which is set on the upper arm or wrist of a critically ill patient and is used to monitor the blood pressure data of the critically ill patient in real time; A blood oxygen saturation finger clip, which is set on the finger of a critically ill patient and is used to monitor the blood oxygen saturation data in real time; An intelligent thermometer, which is set on the finger of a critically ill patient and is used to measure the body temperature data of the critically ill patient in real time.

10. A wireless remote health status monitoring system for infectious disease patients as described in claim 9, characterized in that, The heart rate monitoring bracelet includes: A bracelet body (1), which is set on the wrist of a critically ill patient; An adjusting strap (2), which is set on the bracelet body (1); A heart rate monitoring sensor, which is set on the inner side of the bracelet body (1) and is used to collect the heart rate data of the critically ill patient in real time; The blood pressure monitoring cuff includes: A cuff body (3); A blood pressure monitor (4), which is set on the cuff body (3); The blood oxygen saturation finger clip includes: A lower clip (5); An upper clip (6), which is movably connected to the lower clip (5) and is used to clamp the finger of a critically ill patient; A blood oxygen monitoring sensor, which is set between the upper clip and the lower clip and is used to collect the blood oxygen saturation data of the critically ill patient in real time; A pressure sensor (7), which is set on the lower clip (5) and is used to obtain a pressure signal; An alarm (8), which is set on the upper clip (6) and is connected to the pressure sensor. When the pressure sensor obtains the pressure signal, it sends a control signal to the alarm (8), and the alarm (8) sends out an audible and visual signal; The intelligent thermometer includes: A heat preservation finger sleeve (9), which is set on the finger of a critically ill patient; A temperature sensor (10), which is set on the heat preservation finger sleeve (9) and is used to measure the body temperature data of the critically ill patient in real time; The data transmission module includes: Four wireless transmission units, which are respectively set in the heart rate monitoring bracelet, the blood pressure monitoring cuff, the blood oxygen saturation finger clip and the intelligent thermometer and are used to wirelessly transmit the collected data to the server.

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