Remote real-time monitoring method based on life support system

Abstract

The invention discloses a remote real-time monitoring method based on a life support system, and relates to the technical field of data monitoring, and the method comprises the steps that life support equipment carries out the real-time collection and evaluation of the physical condition of a patient, and obtains state collection data and a corresponding first evaluation result; the remote control end counts the real-time state acquisition data according to the time data, determines the receiving frequency of the data, compares the acquisition frequency with the receiving frequency, and determines the running state of the life support equipment; if the running state of the life support equipment is a working state, performing physical state evaluation on the current state data to obtain a second state evaluation result, comparing the second state evaluation result with the first evaluation result, and if it is judged that the life support equipment has a problem in data processing, performing physical state evaluation on the life support equipment. If not, comparing the data processing logic of the life support equipment with the data processing logic of the remote control end, and if the processing scheme is not accurate, outputting an alarm signal. The method has the effect of improving the monitoring accuracy.

Description

Technical Field

[0001] This application relates to the field of data monitoring technology, and in particular to a remote real-time monitoring method based on a life support system. Background Technology

[0002] Life support equipment refers to a systematic architecture that integrates various elements and technologies to provide the resources, conditions, and safeguards necessary for the survival of organisms (including humans, animals, and plants) or specific environments. Life support equipment includes aviation life support equipment, diving life support equipment, and medical life support equipment. In medical life support equipment, traditional monitoring technologies often rely on manual inspections or local alarms, which suffer from problems such as response delays and limited coverage, making it difficult to meet the real-time and intelligent demands of modern medicine. With the development of the Internet and telemedicine technologies, life support equipment based on remote real-time monitoring has become a research hotspot.

[0003] In related technologies, the focus of remote real-time monitoring of life support equipment is mainly on ensuring the security and accuracy of data during transmission, i.e., judging the correctness of the monitored data itself, without considering the impact of the monitored data, i.e., how the monitored data reflects the status of life support equipment and patients. This reduces the real-time effect of remote real-time monitoring and cannot effectively solve the problem of high latency, so there is room for improvement. Summary of the Invention

[0004] To improve the accuracy of remote real-time monitoring, this application provides a remote real-time monitoring method based on a life support system.

[0005] This application provides a remote real-time monitoring method based on a life support system, which adopts the following technical solution: A remote real-time monitoring method based on a life support system includes: Step S1: The life support device collects the patient's physical condition in real time to obtain status data, assesses the physical condition based on the status data, obtains a first assessment result and a corresponding treatment plan under the first assessment result, and sends the status data, the first assessment result and the treatment plan to a remote control terminal in real time. Step S2: The remote control terminal receives real-time status acquisition data, the first evaluation result and the processing plan. It performs statistics on the real-time status acquisition data based on the time data, marks the status acquisition data received at the current time point as the current status data, and marks the status acquisition data received at other times points as historical status data. Step S3: The remote control terminal performs statistics on the status acquisition data, determines the receiving frequency of the status acquisition data, and compares the preset acquisition frequency with the receiving frequency to determine the operating status of the life support equipment; if the operating status of the life support equipment is determined to be non-working, then the life support equipment is determined to have a startup fault and an alarm signal is output. Step S4: If the life support device is in working state, then perform a physical status assessment on the current status data to obtain a second status assessment result. Compare the second status assessment result with the first assessment result to determine whether there is a problem with the data processing of the life support device. Step S5: If it is determined that there is no problem with the life support device in data processing, the remote control terminal constructs the patient's medical record model based on historical status data and preset patient information, and judges the correctness of the current status data according to the medical record model. It determines whether the current status data meets the changes in the medical record model. If it meets the changes in the medical record model, the current status data is determined to be correct. If it does not meet the changes in the medical record model, the current status data is determined to be incorrect, and an alarm signal is output. Step S6: If it is determined that there is a problem with the data processing of the life support device, the data processing logic of the life support device and the data processing logic of the remote control terminal are compared, and the accuracy of the processing plan is determined based on the comparison result. If it is determined that the processing plan is not accurate, an alarm signal is output.

[0006] Preferably, the received status acquisition data is statistically analyzed based on time data to determine whether the remote control terminal receives the status acquisition data periodically. If periodicity is determined, the life support device is determined to be in working condition; otherwise, if periodicity is determined, the life support device is determined to be in non-working condition, and an alarm signal is output. After determining that the life support equipment is in working condition, the receiving frequency is obtained by calculating the receiving frequency of the status acquisition data from the remote control terminal; The system acquires the frequency at which the life support device collects data on the patient's physical condition and compares the acquisition frequency with the receiving frequency. If the receiving frequency and the acquisition frequency are not equal, the system determines that the status acquisition data received by the remote control terminal is inaccurate and outputs an alarm signal. If the receiving frequency is equal to the acquisition frequency, then the status acquisition data received by the remote control terminal is determined to be accurate.

[0007] Preferably, the second state assessment result is compared with the first assessment result. If the second state assessment result is the same as the first assessment result, it is determined that there is no problem with the life support device in data processing. If the second assessment result differs from the first assessment result, it is determined that there is a problem with the life support device in data processing.

[0008] Preferably, when it is determined that there is a problem with the life support device in data processing, the data processing logic of the life support device when processing the current state data to obtain the first evaluation result is obtained, and the data processing logic is marked as the first logic; Obtain the data processing logic of the remote control terminal when it processes the current status data to obtain the second evaluation result, and mark the data processing logic as the second logic; The first logic is compared with the second logic. If the first logic is the same as the second logic, the first evaluation result is determined to be inaccurate and an alarm signal is output. If the first logic and the second logic are different, then the differences between the first logic and the second logic are marked to obtain logic mark items; Read data from the logical tag items to obtain the first logical data; Based on the first logical data, the historical state data is read to determine whether there is data with corresponding logical marker items in the historical state data. If the historical status data contains data corresponding to the logical marker item, the first evaluation result is determined to be accurate; otherwise, if the historical status data does not contain data corresponding to the logical marker item, the first evaluation result is determined to be inaccurate and an alarm signal is output.

[0009] Preferably, when the current status data does not meet the changes in the data in the medical record model, the pathological cause is judged based on the medical record model and the current status data to determine the pathological category; If it is determined that there is no pathological category that can cause the current state data of the medical record model to change, then the current state data is determined to be incorrect, and an alarm signal is output. If it is determined that there is a pathological category that can cause the current state data of the medical record model to change, then the functional attributes of the life support device are obtained, and the functional attributes are matched with the pathological category to determine whether the life support device has the ability to regulate the corresponding pathological category. If the matching fails, it is determined that there is no ability to regulate the pathological category, and an alarm signal is output. If the match is successful, the first assessment result is deemed correct, or the life support equipment is remotely controlled based on the input of control signals from the remote control terminal.

[0010] Preferably, after confirming the correctness of the current state data, the processing scheme of the historical state data adjacent to the current state data is read based on the time data to obtain the comparison scheme data; The first evaluation result of the current status data is read, and the first evaluation result is compared with the comparison scheme data to determine whether the first evaluation result conflicts with the comparison scheme data. If the first assessment result is determined to conflict with the data from the comparison scheme, the life support equipment is determined to be faulty and an alarm signal is output.

[0011] Preferably, after determining that the current status data is correct, the remote control terminal dynamically updates the medical record model based on the current status data and historical status data to reflect the development trend of the patient's physical condition; wherein, the updated medical record model is used to subsequently judge the correctness of the real-time status data.

[0012] Preferably, when the remote control terminal inputs a control signal to the life support device, the life support device executes the control signal and generates an execution result, and sends the execution result back to the remote control terminal in real time; The remote control terminal simulates the control results based on the control signals and medical record models to obtain the expected effects; The remote control unit receives the execution result and compares it with the expected effect to determine whether the control is effective. If the control is determined to be ineffective, a secondary alarm signal is output. The secondary alarm signal is used to request manual intervention.

[0013] In summary, this application includes at least one of the following beneficial technical effects: By leveraging the independent operation of life support equipment and the remote control terminal, the remote control terminal can automatically determine the startup failure or abnormal shutdown of the life support equipment by statistically analyzing the received status data, effectively ensuring the reliability of continuous equipment operation and reducing medical risks caused by equipment failure. By comparing the evaluation results of the remote control terminal and the life support equipment, the treatment plan for the life support equipment is validated for the first time. A medical record model is established based on historical status data to ensure the relevance and effectiveness of the medical record model. At the same time, the evaluation results are cross-validated in combination with the medical record model to validate the life support equipment for the second time. Finally, the data processing logic of the remote control terminal and the life support equipment is compared to validate the evaluation results for the third time, so as to further ensure the correctness of the treatment plan for the life support equipment. By comparing the data processing logic of the remote control terminal with that of the life support device, it is determined whether the inconsistency in the evaluation results is caused by the difference in data processing logic. This improves the accuracy of the judgment on the feasibility of the treatment plan for the life support device. When it is determined that the data processing logic is inconsistent, it indicates that the inconsistency in the evaluation results is caused by the inconsistency in data processing logic. Furthermore, by judging the logical confusion of the data processing logic of the life support device, it is determined whether the data processing logic of the life support device is correct, thereby further confirming the correctness of the first evaluation result and improving the effect of remote real-time monitoring. By simulating the current state data using the patient's medical record model, the reasons for the data changes that do not conform to the medical record model are determined. Then, after determining the pathology category, the functional attributes of the life support equipment are judged to determine whether the life support equipment can maintain the life of patients under that pathology category, thereby ensuring the patient's life and health, improving the maintenance effect of the life support equipment, and also improving the real-time treatment effect of the patient's condition, ensuring the accuracy of the life support equipment's treatment plan for the patient. Attached Figure Description

[0014] Figure 1 This is a flowchart of the steps of the remote real-time monitoring method based on life support equipment in this embodiment. Detailed Implementation

[0015] The following is in conjunction with the appendix Figure 1 This application will be described in further detail.

[0016] This application discloses a remote real-time monitoring method based on a life support system.

[0017] Example: Figure 1 As shown, the present invention provides a remote real-time monitoring method based on a life support system, comprising: S1, the life support device collects the patient's physical condition in real time, obtains status data, assesses the physical condition based on the status data, obtains the first assessment result and the corresponding treatment plan under the first assessment result, and sends the status data, the first assessment result and the treatment plan to the remote control terminal in real time. S2, the remote control terminal receives real-time status acquisition data, the first evaluation result and the processing plan, and performs statistics on the real-time status acquisition data according to the time data. The status acquisition data received at the current time point is marked as the current status data, and the status acquisition data received at other times points are marked as historical status data. S3, the remote control terminal performs statistics on the status acquisition data, determines the receiving frequency of the status acquisition data, and compares the preset acquisition frequency with the receiving frequency to determine the operating status of the life support equipment; if the operating status of the life support equipment is determined to be non-working, then the life support equipment is determined to have a startup fault and an alarm signal is output. S4, if the life support device is in working state, then perform a physical status assessment on the current status data to obtain a second status assessment result. Compare the second status assessment result with the first assessment result to determine whether there is a problem with the data processing of the life support device; wherein, S41, compare the second status assessment result with the first assessment result. If the second status assessment result is the same as the first assessment result, then it is determined that there is no problem with the data processing of the life support device; S42, if the second status assessment result is different from the first assessment result, then it is determined that there is a problem with the data processing of the life support device.

[0018] S5. If it is determined that there are no problems with the data processing of the life support equipment, the remote control terminal constructs a medical record model for the patient based on historical status data and preset patient information. It then judges the correctness of the current status data based on the medical record model, determining whether the current status data meets the requirements of the medical record model. If it does, the current status data is considered correct; otherwise, it is considered incorrect, and an alarm signal is output. After determining that the current status data is correct, the remote control terminal dynamically updates the medical record model based on the current and historical status data to reflect the patient's health status development trend. The updated medical record model is used to subsequently judge the correctness of real-time status data.

[0019] S6. If it is determined that there is a problem with the data processing of the life support device, the data processing logic of the life support device and the data processing logic of the remote control terminal are compared, and the accuracy of the processing plan is determined based on the comparison result. If it is determined that the processing plan is not accurate, an alarm signal is output.

[0020] In this embodiment, by utilizing the independent operation between the life support device and the remote control terminal, the remote control terminal can automatically determine the startup failure or abnormal shutdown of the life support device by statistically analyzing the received status data, effectively ensuring the reliability of continuous device operation and reducing medical risks caused by device failure. By comparing the evaluation results of the remote control terminal and the life support device, the treatment plan of the life support device is verified for the first time. A medical record model is established based on historical status data to ensure the relevance and effectiveness of the medical record model. At the same time, the evaluation results are cross-validated in combination with the medical record model to verify the life support device for the second time. Finally, the data processing logic of the remote control terminal and the life support device is compared to verify the evaluation results for the third time, so as to further ensure the correctness of the treatment plan of the life support device.

[0021] For example, a remotely monitorable life support device includes life support equipment for maintaining the patient's life and a remote control terminal for remote control and data monitoring. This remote control terminal can be an application on a patient's family member's mobile device, or a control device on a hospital nurses' station, etc.

[0022] Life support devices monitor and maintain a patient's vital signs. For example, if a patient is hypoxic, oxygen is delivered; if the patient requires a higher oxygen concentration, the life support device increases the delivered oxygen concentration. After collecting data on the patient's physical condition, the life support device sends the results to a remote control for review by relevant personnel. For instance, doctors can review the data to make a preliminary assessment of the patient's condition and provide timely treatment if the patient's condition deteriorates. However, while this method improves patient safety, it increases the workload of doctors, requiring a higher level of focus and consuming considerable energy.

[0023] In this application, after the life support device collects data on the patient's physical condition, it processes the data and formulates a processing plan on its own. At the same time, it sends the collection results and processing plan to the remote control terminal. The remote control terminal uses its own computing power system to re-evaluate the received status data to further determine whether the life support device is working properly. By enabling the life support device and the remote control terminal to operate and process the data independently, the remote control terminal can verify the evaluation results of the life support device, thereby improving the correctness of the life support device's execution plan.

[0024] After receiving status data from the life support device, the remote control terminal determines the receiving frequency of the data to ensure that the data received is real-time, thus guaranteeing the accuracy of the data analysis results. For example, if the life support device collects the patient's physical condition data once per second and inputs this data to the remote control terminal, the remote control terminal should also receive one set of patient status data per second. If the remote control terminal does not receive data once per second, it can be determined that the received data is not real-time, and therefore the analysis results will not be timely.

[0025] Similarly, if the remote control terminal suddenly stops receiving data after receiving data at a specific frequency, it can be determined that the working status of the life support equipment has changed, and can effectively warn of situations where the life support equipment cannot work properly due to a sudden power outage.

[0026] The remote control unit determines the operational status of the life support device by the frequency of the received data. After confirming that the life support device is operational, the remote control unit uses its own computing power system to analyze the received current status data. This allows for a quick determination of whether the results analyzed and evaluated by the remote control unit and the life support device are the same. If they are the same, it indicates that the life support device's assessment is correct. To further ensure its accuracy, the current status data that was initially deemed correct is reassessed. First, a medical record model specific to the patient is constructed based on historical status data. Then, the current status data is simulated using the medical record model to determine whether the current status data reflects changes in the medical record model. If the current status data differs from the changes in the medical record model, it indicates that the data is inaccurate, meaning it exceeds the scope of the life support device's analysis of the patient's condition. Therefore, an alarm is triggered so that relevant personnel can promptly address the patient's condition, ensuring the patient's safety.

[0027] Since life support equipment and remote control are two independently operating devices, and life support equipment directly affects the patient, the life support equipment is used to analyze and assess the patient's condition to maintain life throughout the entire life support process, while the remote control is used to alert staff and assist the life support equipment to achieve real-time, remote monitoring of the patient. Therefore, when analyzing current status data, life support equipment may make a comprehensive assessment based on the patient's overall maintenance status, while the remote control only makes an assessment based on the received current status data. This can lead to differences between the assessment results of life support equipment and remote control. Therefore, by comparing the data processing logic between the two, the accuracy of judgments regarding differing assessment results can be further enhanced, thus improving overall accuracy.

[0028] In step S3, the remote control terminal statistically analyzes the status acquisition data, determines the receiving frequency of the status acquisition data, and compares the preset acquisition frequency with the receiving frequency to determine the operating status of the life support equipment. If the operating status of the life support equipment is determined to be non-working, then the life support equipment is determined to have a startup fault and an alarm signal is output, including the following steps: S31, based on time data, perform time statistics on the received status acquisition data to determine whether the remote control terminal receives the status acquisition data periodically. If it is determined to be periodic, the life support equipment is determined to be in working state; otherwise, if it is determined not to be periodic, the life support equipment is determined to be in non-working state, and an alarm signal is output. S32, after determining that the life support equipment is in working condition, the receiving frequency is obtained by calculating the receiving frequency of the status acquisition data from the remote control terminal; S33: Obtain the collection frequency of the patient's physical condition from the life support device, and compare the collection frequency with the receiving frequency. If the receiving frequency and the collection frequency are not equal, it is determined that the status collection data received by the remote control terminal is inaccurate, and an alarm signal is output. S34. If the receiving frequency is equal to the acquisition frequency, then the status acquisition data received by the remote control terminal is determined to be accurate.

[0029] In this embodiment, by statistically analyzing the data reception status of the remote control terminal, it is possible to determine whether the remote control terminal can normally receive the status acquisition data output by the life support device. The activation status of the life support device can then be determined based on whether the remote control terminal receives the status acquisition data. Furthermore, the reception of status acquisition data by the remote control terminal can effectively identify abnormal power outages of the life support device, improving the monitoring effect of abnormal states of the life support device. Simultaneously, by comparing the data reception frequency of the remote control terminal with the data acquisition frequency of the life support device, the data transmission status between the life support device and the remote control terminal is determined, ensuring that the data on the remote control terminal can display the patient's physical status in real time, thus guaranteeing the effectiveness of the transmitted data.

[0030] For example, since the life support device collects data on the patient's physical condition periodically, such as once per second, the remote control terminal should theoretically also receive data once per second when the life support device transmits data to the remote control terminal in real time. Therefore, when the life support device has a periodic collection period, the remote control terminal also has a periodic reception period. When the reception period of the remote control terminal is broken, it indicates that the transmission periodicity of the life support device is broken, and consequently, the collection periodicity of the life support device may also be broken, meaning the startup state of the life support device may be disrupted. For instance, when the life support device is started, theoretically, it sends a collection signal to the remote control terminal from the start. If the remote control terminal does not receive the corresponding collection signal, it can be directly determined that the life support device has not started normally or that there is a data transmission failure, i.e., the life support device is faulty. During continuous transmission, if the life support device experiences an abnormal power outage, it cannot restart normally and therefore will not collect data on the patient again, thus failing to transmit the patient's physical condition data to the remote control terminal. Therefore, when the remote control terminal suddenly stops receiving the collection signal from the life support device, it indicates that the startup state of the life support device has changed.

[0031] Similarly, by statistically analyzing and comparing the data receiving frequencies at the remote control end, it is possible to effectively determine whether the life support device can transmit the patient's physical condition to the remote control end in real time. When the receiving frequency is different from the acquisition frequency, it indicates that there is a fault in the signal transmission system of the life support device, or that the life support device cannot transmit data in real time, that is, it cannot achieve the effect of remote real-time monitoring, and thus it can be directly determined that the life support device is faulty.

[0032] In step S6, if it is determined that there is a problem with the data processing of the life support device, the data processing logic of the life support device is compared with the data processing logic of the remote control terminal, and the accuracy of the processing plan is determined based on the comparison result. If it is determined that the processing plan is inaccurate, an alarm signal is output, including the following steps: S61, when it is determined that there is a problem with the life support device in data processing, the data processing logic of the life support device when processing the current state data to obtain the first evaluation result is obtained, and the data processing logic is marked as the first logic; S62, obtain the data processing logic of the remote control terminal when it processes the current status data to obtain the second evaluation result, and mark the data processing logic as the second logic; S63, compare the first logic with the second logic. If the first logic and the second logic are the same, determine that the first evaluation result is inaccurate and output an alarm signal. S64, If the first logic and the second logic are different, then mark the differences between the first logic and the second logic to obtain the logic mark item; S65, read data from the logical flag item to obtain the first logical data; S66, based on the first logical data, read the historical state data to determine whether there is data corresponding to the logical tag item in the historical state data; S67, if the historical state data contains data corresponding to the logical marker item, the first evaluation result is determined to be accurate; otherwise, if the historical state data does not contain data corresponding to the logical marker item, the first evaluation result is determined to be inaccurate and an alarm signal is output.

[0033] In this embodiment, by comparing the data processing logic of the remote control terminal with the data processing logic of the life support device, it is determined whether the inconsistency of the evaluation results is caused by the different data processing logic. This improves the accuracy of the judgment on the feasibility of the processing scheme of the life support device. When it is determined that the data processing logic is inconsistent, it indicates that the inconsistency of the evaluation results is caused by the inconsistency of the data processing logic. Then, by judging the logical confusion of the data processing logic of the life support device, it is determined whether the data processing logic of the life support device is correct, thereby further determining the correctness of the first evaluation result and improving the effect of remote real-time monitoring.

[0034] For example, since life support devices and remote control terminals are two independently operating devices, and life support devices are single-purpose (one device is responsible for maintaining the life of only one patient), while remote control terminals may be mobile devices used by relevant personnel, and the data processing terminal of the remote control terminal is often connected to multiple life support devices simultaneously, the data evaluation results from life support devices are more correlated with the patient's physical condition, while the evaluation results from the remote control terminal are only for the current state data and therefore have lower correlation with the patient. Therefore, after determining that there is a problem with the data processing of the life support device, the processing logic of the life support device when processing the current state data can be obtained, and then compared with the data processing logic of the remote control terminal to determine whether the different evaluation results are due to inconsistencies in the data processing logic. When the data processing logic is consistent, it indicates that at least one device between the remote control terminal and the life support equipment has an incorrect assessment result. In order to ensure the patient's safety, an alarm signal needs to be output to remind relevant personnel to take human action.

[0035] When inconsistencies in data processing logic are detected, further investigation is required to avoid erroneous assessment results due to confusion in the life support device's data processing logic. This is achieved by identifying the discrepancies inherent in the data processing logic and matching the data at these discrepancies with historical data. This determines whether the discrepancy is a targeted assessment based on the patient's condition. Since life support devices maintain life for only one patient, any deviations from standard data processing logic should be attributed to changes in the patient's condition. Therefore, the data values ​​at these discrepancies should be historically verifiable. If the data at a discrepancy point is searchable, the life support device's assessment result is correct; otherwise, inconsistencies are attributed to logical confusion, necessitating an alarm to improve accuracy.

[0036] In step S5, if it is determined that there are no problems with the data processing of the life support equipment, the remote control terminal constructs a medical record model for the patient based on historical status data and preset patient information. It then performs a data correctness judgment on the current status data based on the medical record model, determining whether the current status data meets the requirements of the medical record model. If it does, the current status data is deemed correct; otherwise, it is deemed incorrect, and an alarm signal is output. This includes the following steps: S51, when the current status data does not meet the changes in the data in the medical record model, the pathological cause is judged based on the medical record model and the current status data, and the pathological category is determined; S52, if it is determined that there is no pathological category that can cause the current state data of the medical record model to change, then the current state data is determined to be incorrect and an alarm signal is output; S53, if it is determined that there is a pathological category that can cause the current state data of the medical record model to change, then the functional attributes of the life support device are obtained, and the functional attributes are matched with the pathological category to determine whether the life support device has the ability to regulate the corresponding pathological category. S54, if the matching fails, it is determined that there is no ability to regulate the pathological category, and an alarm signal is output; S55, if the matching is successful, the first assessment result is determined to be correct or the life support equipment is remotely controlled based on the input of the control signal from the remote control terminal to the life support equipment.

[0037] In this embodiment, the current state data is simulated using the patient's medical record model to determine the reasons for the data changes that do not conform to the medical record model. Then, after determining the pathology category, the functional attributes of the life support device are judged to determine whether the life support device can maintain the life of the patient under the pathology category, thereby ensuring the patient's life and health, improving the maintenance effect of the life support device, and also improving the real-time processing effect of the patient's condition, ensuring the accuracy of the life support device's treatment plan for the patient.

[0038] For example, the current status data is judged based on the medical record model to determine its correctness. When the current status data meets the data changes in the medical record model, it indicates that the current status data is correct and reasonable; conversely, when the current status data does not meet the medical record model, it indicates that the current status data is abnormal, and further judgment is needed. By using the medical record model to analyze the current status data, the cause of the change in the current status data can be determined. For example, a patient has symptom A, and life support equipment treats the patient's symptom A to maintain the patient's life and health. Symptom A has complication B. When complication B has not occurred, the patient's physical condition data is 'a'; when complication B occurs, the patient's physical condition data is 'b'. If the currently collected current status data is 'b', it is determined that the reason why the patient's physical condition does not meet the data changes in the medical record model is the onset of complication B. Since the patient's complication B has not occurred, the medical record model built based on historical status data only applies to symptom A, and therefore cannot accurately determine when complication B occurs. After identifying the different causes of the current status data, the functional attributes of the life support equipment are matched according to the cause (complication B) to determine whether the life support equipment can handle the patient's life support when complication B occurs. If it can, the corresponding measures are executed; if it cannot, an alarm is triggered to remind relevant personnel to provide emergency treatment to the patient.

[0039] A remote real-time monitoring method based on a life support system further includes the following steps: S71, after confirming that the current state data is correct, based on the time data, read the processing scheme of the historical state data adjacent to the current state data to obtain the comparison scheme data; S72, Read the first evaluation result of the current status data, compare the first evaluation result with the comparison scheme data, and determine whether the first evaluation result conflicts with the comparison scheme data; S73, if the first assessment result is determined to conflict with the comparison scheme data, the life support equipment is determined to be faulty and an alarm signal is output.

[0040] In this embodiment, by utilizing the temporal causality between the treatment plan of the life support device and the current status data, when the patient's symptoms reflected in the current status data contradict the treatment plan taken by the life support device at an adjacent time, it is determined that the life support device is faulty. This improves the accuracy of judging the fault of the life support device itself, ensures the patient's life and health, and improves the effectiveness of remote monitoring.

[0041] For example, since life support devices input data to the remote control terminal, and data is not equivalent to the actual state of the device, for example, the data input by the life support device to the remote control terminal is oxygen supply, but it is unknown whether the life support device actually supplies oxygen. Therefore, it is necessary to evaluate the actual behavior of the life support device based on the collected data to determine whether the life support device itself is faulty.

[0042] For example, if the current time is T, and the patient's condition is determined to be hypoxia (low blood oxygen saturation) after analysis at T, and the patient's condition is still determined to be hypoxia at time T-1, and the treatment plan implemented is to increase the oxygen concentration (e.g., the patient's blood oxygen saturation at time T-1 is 'a', and at time T, the patient's blood oxygen saturation is 'a-10', and the measures taken at time T-1 are to increase the patient's blood oxygen saturation), then the symptoms exhibited by the patient at the current time T conflict with the measures taken by the life support equipment at time T-1. Therefore, it is determined that the life support equipment has a system malfunction, and the remote monitoring effect is ineffective, requiring relevant personnel to handle both the patient and the equipment.

[0043] A remote real-time monitoring method based on a life support system further includes the following steps: S81, when the remote control terminal inputs a control signal to the life support device, the life support device executes the control signal and generates an execution result, which is then sent back to the remote control terminal in real time; S82, the remote control terminal simulates the control results based on the control signals and medical record model to obtain the expected effect; S83, the remote control terminal receives the execution result and compares the execution result with the expected effect to determine whether the control is effective. If the control is determined to be ineffective, a secondary alarm signal is output; the secondary alarm signal is used to request manual intervention.

[0044] For example, when the remote control terminal determines that the life support device's treatment plan is incorrect after judging the current status data, staff or medical personnel send a control signal to the life support device through the remote control terminal to ensure that the result of human control meets the patient's needs reflected in the current status data. After the life support device executes the control signal, it returns the execution result to the remote control terminal. The remote control terminal compares the actual execution result with the expected effect to determine whether the control is effective. When the control is determined to be ineffective, since the execution result is the result of human control, the remote control terminal sent an alarm signal to the relevant personnel or medical personnel before the control was performed. Therefore, when the execution result does not match the expected effect, it indicates that the patient's actual condition does not match the judgment of the relevant personnel or medical personnel. Thus, when an alarm is triggered again, the alarm level is increased to ensure the patient's life safety.

[0045] Compared to existing remote real-time monitoring methods based on life support equipment, this invention improves the accuracy of remote real-time monitoring.

[0046] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

Claims

1. A remote real-time monitoring method based on a life support system, characterized in that, include: Step S1: The life support device collects the patient's physical condition in real time to obtain status data, assesses the physical condition based on the status data, obtains a first assessment result and a corresponding treatment plan under the first assessment result, and sends the status data, the first assessment result and the treatment plan to a remote control terminal in real time. Step S2: The remote control terminal receives real-time status acquisition data, the first evaluation result and the processing plan. It performs statistics on the real-time status acquisition data based on the time data, marks the status acquisition data received at the current time point as the current status data, and marks the status acquisition data received at other times points as historical status data. Step S3: The remote control terminal performs statistics on the status acquisition data, determines the receiving frequency of the status acquisition data, and compares the preset acquisition frequency with the receiving frequency to determine the operating status of the life support equipment. If the life support equipment is determined to be in a non-working state, then the life support equipment is determined to have a startup fault and an alarm signal is output. Step S4: If the life support device is in working state, then perform a physical status assessment on the current status data to obtain a second status assessment result. Compare the second status assessment result with the first assessment result to determine whether there is a problem with the data processing of the life support device. Step S5: If it is determined that there is no problem with the life support device in data processing, the remote control terminal constructs the patient's medical record model based on historical status data and preset patient information, and judges the correctness of the current status data according to the medical record model. It determines whether the current status data meets the changes in the medical record model. If it meets the changes in the medical record model, the current status data is determined to be correct. If it does not meet the changes in the medical record model, the current status data is determined to be incorrect, and an alarm signal is output. Step S6: If it is determined that there is a problem with the data processing of the life support device, the data processing logic of the life support device and the data processing logic of the remote control terminal are compared, and the accuracy of the processing plan is determined based on the comparison result. If it is determined that the processing plan is not accurate, an alarm signal is output.

2. The remote real-time monitoring method based on a life support system according to claim 1, characterized in that: Step S3 includes: Based on time data, the received status acquisition data is statistically analyzed to determine whether the remote control terminal receives the status acquisition data periodically. If periodicity is determined, the life support equipment is determined to be in working condition; otherwise, if periodicity is determined, the life support equipment is determined to be in non-working condition, and an alarm signal is output. After determining that the life support equipment is in working condition, the receiving frequency is obtained by calculating the receiving frequency of the status acquisition data from the remote control terminal; The system acquires the frequency at which the life support device collects data on the patient's physical condition and compares the acquisition frequency with the receiving frequency. If the receiving frequency and the acquisition frequency are not equal, the system determines that the status acquisition data received by the remote control terminal is inaccurate and outputs an alarm signal. If the receiving frequency is equal to the acquisition frequency, then the status acquisition data received by the remote control terminal is determined to be accurate.

3. The remote real-time monitoring method based on a life support system according to claim 1, characterized in that: Step S4 includes: The second state assessment result is compared with the first assessment result. If the second state assessment result is the same as the first assessment result, it is determined that there is no problem with the data processing of the life support device. If the second assessment result differs from the first assessment result, it is determined that there is a problem with the life support device in data processing.

4. The remote real-time monitoring method based on a life support system according to claim 1, characterized in that: Step S6 includes: When it is determined that there is a problem with the life support device in data processing, the data processing logic of the life support device when processing the current state data to obtain the first evaluation result is obtained, and the data processing logic is marked as the first logic; Obtain the data processing logic of the remote control terminal when it processes the current status data to obtain the second evaluation result, and mark the data processing logic as the second logic; The first logic is compared with the second logic. If the first logic is the same as the second logic, the first evaluation result is determined to be inaccurate and an alarm signal is output. If the first logic and the second logic are different, then the differences between the first logic and the second logic are marked to obtain logic mark items; Read data from the logical tag items to obtain the first logical data; Based on the first logical data, the historical state data is read to determine whether there is data with corresponding logical marker items in the historical state data. If the historical status data contains data corresponding to the logical marker item, the first evaluation result is determined to be accurate; otherwise, if the historical status data does not contain data corresponding to the logical marker item, the first evaluation result is determined to be inaccurate and an alarm signal is output.

5. The remote real-time monitoring method based on a life support system according to claim 1, characterized in that: Step S5 includes: When the current status data does not match the changes in the data in the medical record model, the pathological cause is judged based on the medical record model and the current status data to determine the pathological category; If it is determined that there is no pathological category that can cause the current state data of the medical record model to change, then the current state data is determined to be incorrect, and an alarm signal is output. If it is determined that there is a pathological category that can cause the current state data of the medical record model to change, then the functional attributes of the life support device are obtained, and the functional attributes are matched with the pathological category to determine whether the life support device has the ability to regulate the corresponding pathological category. If the matching fails, it is determined that there is no ability to regulate the pathological category, and an alarm signal is output. If the match is successful, the first assessment result is deemed correct, or the life support equipment is remotely controlled based on the input of control signals from the remote control terminal.

6. The remote real-time monitoring method based on a life support system according to claim 1, characterized in that, Also includes: After confirming the correctness of the current state data, the processing schemes for the historical state data adjacent to the current state data are read based on the time data to obtain the comparison scheme data; The first evaluation result of the current status data is read, and the first evaluation result is compared with the comparison scheme data to determine whether the first evaluation result conflicts with the comparison scheme data. If the first assessment result is determined to conflict with the data from the comparison scheme, the life support equipment is determined to be faulty and an alarm signal is output.

7. The remote real-time monitoring method based on a life support system according to claim 1, characterized in that, Also includes: After determining that the current status data is correct, the remote control terminal dynamically updates the medical record model based on the current status data and historical status data to reflect the development trend of the patient's physical condition; the updated medical record model is used to subsequently judge the correctness of the real-time status data.

8. The remote real-time monitoring method based on a life support system according to claim 1, characterized in that, Also includes: When the remote control terminal inputs a control signal to the life support device, the life support device executes the control signal and generates an execution result, which is then sent back to the remote control terminal in real time. The remote control terminal simulates the control results based on the control signals and medical record models to obtain the expected effects; The remote control unit receives the execution result and compares it with the expected effect to determine whether the control is effective. If the control is determined to be ineffective, a secondary alarm signal is output. The secondary alarm signal is used to request manual intervention.

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