Brain state monitoring method and device, computer equipment and storage medium

Abstract

The invention relates to a brain state monitoring method and device, computer equipment and a storage medium. The method comprises the following steps: in response to a monitoring instruction, acquiring an initial head weight at the beginning of the monitoring instruction through a head weight measuring device; obtaining weight monitoring data continuously measured by the head weight measuring device; obtaining state change data of the head weight according to the initial head weight and the weight monitoring data; if the state change data of the head weight is greater than a preset weight change threshold, generating an early warning result of brain state change; wherein the weight change threshold value is determined according to a preset state change relation between the head weight and the brain weight. By adopting the method, the evaluation precision of the brain state change can be improved.

Description

Technical Field

[0001] This application relates to the technical field of brain injury monitoring, and particularly to a method, device, computer device, and storage medium for monitoring the brain state. Background Art

[0002] With the development of the medical technology field, it has a significant impact on the improvement of medical standards. Brain edema is a common complication of diseases such as craniocerebral injury, stroke, brain tumor, or intracranial infection. Its main manifestation is an increase in the water content of brain tissue, resulting in changes in brain volume and mass. The severity of brain edema directly affects the prognosis of patients. Therefore, early detection, dynamic monitoring, and evaluation of treatment effects of brain edema are key links in clinical treatment.

[0003] In related technologies, the state changes of brain edema are indirectly evaluated through intracranial pressure (ICP) monitoring or imaging methods (such as CT, MRI).

[0004] However, the applicant found in the real-time process that related technologies at least have the problem of low accuracy in evaluating the brain state. Summary of the Invention

[0005] Based on this, the purpose of this application aims to at least solve one of the above technical defects, especially the technical defect of low accuracy in evaluating the brain state in the prior art. This application provides a method, device, computer device, and storage medium for monitoring the brain state.

[0006] In a first aspect, this application provides a method for monitoring the brain state, which is applied to a brain state monitoring device. The brain state monitoring device is used to connect to a head weight measurement device. The head weight measurement device is installed in the head placement area of the person to be monitored and is used to monitor the weight of the head of the person to be monitored in the lying state. The method includes:

[0007] In response to a monitoring instruction, obtain the initial head weight at the start of the monitoring instruction through the head weight measurement device;

[0008] Obtain the weight monitoring data continuously measured by the head weight measurement device;

[0009] According to the initial head weight and the weight monitoring data, obtain the state change data of the head weight;

[0010] If the state change data of the head weight is greater than a preset weight change threshold, generate a warning result for the change in the brain state; wherein, the weight change threshold is determined by a preset state change relationship between the head weight and the brain weight.

[0011] In one embodiment, generating a warning result for the change in the brain state includes:

[0012] Determine the duration of the data change corresponding to the status change data;

[0013] If the duration is greater than or equal to the time threshold, generate a warning result for the brain status change based on the status change data.

[0014] In one embodiment, after generating the warning result for the brain status change, it further includes:

[0015] Display the warning result on the brain status monitoring device;

[0016] And / or, send the warning result to the monitoring terminal connected to the brain status monitoring device;

[0017] Receive the warning feedback result fed back by the brain status monitoring device and / or the monitoring terminal;

[0018] If the warning feedback result indicates that the warning result is correct, record the warning result;

[0019] If the warning feedback result indicates that the warning result is incorrect, eliminate the warning result.

[0020] In one embodiment, the method further includes:

[0021] In response to the nursing confirmation instruction, determine the weight change data corresponding to the nursing confirmation instruction;

[0022] Based on the weight change data, correct the status change data of the head weight.

[0023] In one embodiment, the method further includes:

[0024] In response to the nursing confirmation instruction, determine the head weight after the end of the nursing corresponding to the nursing confirmation instruction;

[0025] Use the head weight after the end of the nursing as the updated initial head weight.

[0026] In one embodiment, the brain status monitoring device is further used to connect to an angle sensor, and the angle sensor is used to measure the head elevation angle formed between the head and the horizontal direction in the lying state;

[0027] Obtain the weight monitoring data continuously measured by the head weight measuring device, including:

[0028] Obtain the head elevation angle measured by the angle sensor;

[0029] Based on the head elevation angle, correct the weight measurement data directly measured by the head weight measuring device to obtain the weight monitoring data.

[0030] In one embodiment, the method further includes:

[0031] When the state change data of the head weight is greater than a preset weight change threshold, obtain the brain state corresponding to the state change data of the head weight as the brain state sample data;

[0032] Input the state change data into a pre-constructed and to-be-trained brain state determination model, and through the brain state determination model, output the brain state prediction data;

[0033] Based on the brain state sample data and the brain state prediction data, train the brain state determination model to obtain a trained brain state determination model; wherein, the brain state determination model is used to determine the brain state through the state change data of the head weight.

[0034] In a second aspect, the present application provides a monitoring device for brain states, which is applied to a brain state monitoring device. The brain state monitoring device is used to connect to a head weight measuring device. The head weight measuring device is installed in the head placement area of the person to be monitored and is used to monitor the weight of the head of the person to be monitored in the lying state. The device includes:

[0035] A monitoring instruction corresponding module, which is used to respond to a monitoring instruction and obtain the initial head weight at the start of the monitoring instruction through the head weight measuring device;

[0036] A monitoring data acquisition module, which is used to acquire the weight monitoring data continuously measured by the head weight measuring device;

[0037] A change data determination module, which is used to obtain the state change data of the head weight according to the initial head weight and the weight monitoring data;

[0038] An early warning generation module, which is used to generate an early warning result of a brain state change if the state change data of the head weight is greater than a preset weight change threshold; wherein, the weight change threshold is determined through a preset state change relationship between the head weight and the brain weight.

[0039] In a third aspect, the present application provides a computer device, which includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the steps of the above method.

[0040] In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the steps of the above method.

[0041] It can be seen from the above technical solutions that the embodiments of the present application have the following advantages:

[0042] The brain state monitoring method, device, computer device, and storage medium provided by this application achieve brain state monitoring through a brain state monitoring device. Specifically, the brain state monitoring device is connected to a head weight measurement device, and the head weight measurement device is used to monitor the weight of the person to be monitored in the lying state. In this way, when the brain state monitoring device responds to a monitoring instruction, the initial head weight at the start of the monitoring instruction can be obtained. Furthermore, based on the initial head weight and the weight data continuously monitored in real time, the state change data of the head weight can be determined. Thus, the change in the brain state can be further judged according to the state change data. Therefore, when the state change data of the head weight is greater than a preset weight change threshold, a warning result of the brain state change can be effectively generated. Compared with the traditional technology, this application directly judges the change in brain weight through the head weight, thereby improving the evaluation accuracy of the change in brain state. At the same time, this application monitors the change in brain weight in a non-invasive manner, which is safer than the invasive method of measuring intracranial pressure in the traditional technology to estimate brain weight. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of this application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0044] Figure 1 Schematic diagram of the application environment of the brain state monitoring method provided by the embodiment of this application;

[0045] Figure 2 Flow chart of the brain state monitoring method provided by the embodiment of this application Figure 1 ;

[0046] Figure 3 Flow chart of a brain state monitoring method provided by the embodiment of this application Figure 2 ;

[0047] Figure 4 Flow chart of a brain state monitoring method provided by the embodiment of this application Figure 3 ;

[0048] Figure 5 Schematic diagram of the structure of a brain state monitoring device provided by the embodiment of this application;

[0049] Figure 6 Schematic diagram of the internal structure of a computer device provided by the embodiment of this application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0050] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative efforts shall fall within the protection scope of the present application.

[0051] With the development of the medical technology field, it has a significant impact on the improvement of the medical level. Brain edema is a common complication of diseases such as craniocerebral injury, stroke, brain tumor, or intracranial infection. Its main manifestation is an increase in the water content of brain tissue, resulting in changes in brain volume and mass. The severity of brain edema directly affects the prognosis of patients. Therefore, the early detection, dynamic monitoring, and evaluation of the treatment effect of brain edema are key links in clinical treatment.

[0052] In the related art, the state change of brain edema is indirectly evaluated through intracranial pressure (ICP) monitoring or imaging methods (such as CT, MRI). However, traditional intracranial pressure (ICP) monitoring and imaging methods (such as CT, MRI) cannot directly measure brain mass and can only indirectly evaluate the changes in intracranial pressure or brain volume. The applicant found in the real-time process that the accuracy of the brain mass estimation method based on volume or intracranial pressure is low and cannot reflect the real-time dynamic changes of brain weight.

[0053] Based on this, the present application provides a monitoring method, device, computer device, and storage medium for brain state. When the brain state monitoring device responds to a monitoring instruction, it obtains the initial head weight at the start of the monitoring instruction. Further, based on the initial head weight and the weight data continuously monitored in real time, the state change data of the head weight can be determined. In this way, the change in the brain state can be further judged according to the state change data. Thus, when the state change data of the head weight is greater than a preset weight change threshold, a warning result of the brain state change can be effectively generated. Compared with the traditional technology, the present application directly judges the change in brain weight through the head weight, thereby improving the evaluation accuracy of the change in brain state. At the same time, the present application monitors the change in brain weight in a non-invasive manner, which is safer than the invasive method of measuring intracranial pressure in the traditional technology to estimate brain weight.

[0054] The monitoring method for brain state provided by the embodiments of the present application can be applied to the application environment as shown. As Figure 1 shown, the brain state monitoring device 101 is used to connect to the head weight measuring device 102. The head weight measuring device is installed in the head placement area of the person to be monitored and is used to monitor the weight of the head of the person to be monitored in the lying state. The brain state monitoring device can also be connected to the user terminal and can send the monitored brain state change and the warning result of the brain state change to the user terminal.

[0055] In an exemplary embodiment, Figure 2 is a flowchart of the method for monitoring the brain state provided by the embodiments of the present application Figure 1 , as Figure 2 shown, a method for monitoring the brain state is provided. In this embodiment, taking the application of this method to a brain state monitoring device as an example, it can be understood that this method can also be applied to a server, and can also be applied to a system including a terminal and a server, and is implemented through the interaction between the terminal and the server. In this embodiment, the method includes the following S201 to S204. Among them:

[0056] S201. In response to a monitoring instruction, obtain the initial head weight at the start of the monitoring instruction through a head weight measurement device.

[0057] Among them, the brain state monitoring device can be a terminal device, which can be used to execute the method for monitoring the brain state provided by the present application. The brain state monitoring device can have functions such as a display function and a sound playback function, so that the brain state monitoring device can realize early warning prompts for changes in the brain state through graphic texts or sounds, etc.

[0058] The head weight measurement device can refer to a device for measuring weight. For example, it can be a weighing sensor. The head weight measurement device can be set in the head placement area of the patient to realize the measurement of the head weight; for example, the head weight measurement device is set in the pillow on the hospital bed, and the head weight of the person to be monitored can be measured in real time when the patient pads the pillow.

[0059] The monitoring instruction refers to an instruction initiated by the user in the brain state monitoring device for monitoring the head weight of the patient. For example, for a certain hospital bed, when the patient uses it, a monitoring instruction can be initiated in the brain state monitoring device corresponding to the hospital bed.

[0060] The initial head weight can refer to the head weight at the beginning of the monitoring.

[0061] Exemplarily, the user can initiate a monitoring instruction in the brain state monitoring device. The brain state monitoring device can respond to the monitoring instruction and activate the head weight measurement device to obtain the head weight measured by the head weight measurement device at the start of the monitoring instruction as the initial head weight. In this way, the state change of the head weight during the monitoring process can be further obtained through the initial head weight. Further, the state change of the brain weight can be determined through the corresponding relationship between the head weight and the brain weight. As an example, generally, the head weight reflects the brain weight. When cerebral edema occurs in the brain, the increase in the edema weight will cause the head weight to increase, and when the brain weight does not change, the head weight generally does not change either.

[0062] S202. Obtain the weight monitoring data continuously measured by the head weight measurement device.

[0063] Among them, the weight monitoring data can refer to the weight measured in real time. After the brain state monitoring device responds to the monitoring instruction, the weight of the patient's head can be measured in real time.

[0064] Exemplarily, after the brain state monitoring device responds to the monitoring instruction, the weight monitoring data measured in real time by the head weight measurement device can be continuously obtained. In this way, the weight change of the head can be monitored in real time, so as to reflect the weight change of the brain. The present application can realize the measurement of the brain weight through a non-invasive weight measurement method, and then judge the state change of the patient's brain edema and other conditions through the change of the brain weight.

[0065] Optionally, the head weight measurement device can be a sensor, and a strain gauge sensor or a piezoelectric sensor can be selected, with a sensitivity of up to ±0.1 g. An analog-to-digital converter (ADC) is integrated inside the module to digitize the weight data and transmit it to the data processing module.

[0066] S203. Obtain the state change data of the head weight according to the initial head weight and the weight monitoring data.

[0067] Among them, the state change data can refer to the data characterizing the weight change. For example, it can be a weight change curve.

[0068] Exemplarily, when the brain state monitoring device responds to the monitoring, it can generate a state change curve of the head weight through the weight monitoring data and the initial head weight obtained in real time, and can reflect the weight change of the brain through this state change, and judge whether the brain state deteriorates. For example, if the brain state indicates that the brain weight continues to increase, then it may be that the edema continues to increase, and there is a risk of deterioration of brain edema.

[0069] S204. If the state change data of the head weight is greater than the preset weight change threshold, generate a warning result of the brain state change; among them, the weight change threshold is determined by the preset state change relationship between the head weight and the brain weight.

[0070] Among them, the weight change threshold may refer to a threshold preset for the weight change of the head. If this threshold is exceeded, it indicates that there may be a risk of disease deterioration. The weight change threshold can be determined based on the state change of the corresponding brain weight when the disease deteriorates. For example, the state change between the normal brain weight and the brain weight during cerebral edema can be determined, and thus the state change between the normal head weight and the head weight during cerebral edema can be determined. In this way, the weight change threshold can be set based on the head weight during cerebral edema.

[0071] The weight change threshold may include multiple thresholds. For example, different thresholds can be set according to different severities of cerebral edema.

[0072] Exemplarily, if the brain state monitoring device monitors that the state change data of the head weight is greater than the preset weight change threshold, an early warning result of the brain state change can be generated based on the above monitoring result to inform medical staff that the patient being monitored is at risk of disease deterioration. In this way, the present application can directly measure the minute change of the head weight and reflect the change of the brain tissue mass in real time, which is beneficial to accurately reflecting the change state of the brain mass, thereby improving the evaluation accuracy of the brain state.

[0073] In this embodiment, the monitoring of the brain state is realized through the brain state monitoring device. Specifically, the brain state monitoring device is connected to the head weight measuring device, and the head weight measuring device is used to monitor the weight of the head of the person to be monitored in the lying state. In this way, the brain state monitoring device can obtain the initial head weight at the start of the monitoring instruction in response to the monitoring instruction. Further, based on the initial head weight and the weight data continuously monitored in real time, the state change data of the head weight can be determined. In this way, the change of the brain state can be further judged according to the state change data, and thus an early warning result of the brain state change can be effectively generated when the state change data of the head weight is greater than the preset weight change threshold. Compared with the traditional technology, the present application directly judges the change of the brain weight through the head weight, thereby improving the evaluation accuracy of the change of the brain state. At the same time, the present application monitors the change of the brain weight in a non-invasive manner, which is safer than the invasive method of measuring intracranial pressure in the traditional technology to estimate the brain weight.

[0074] In an exemplary embodiment, Figure 3 is a schematic flow chart of a method for monitoring the brain state provided by an embodiment of the present application Figure 2 As Figure 3 shown, on the basis of Figure 2 , a further exemplary description of the method for monitoring the brain state is made. Among them, in the step of S204, generating an early warning result of the brain state change includes S301 and S302:

[0075] S301. Determine the duration of the data change corresponding to the status change data.

[0076] S302. If the duration is greater than or equal to the time threshold, generate a warning result for the brain status change based on the status change data.

[0077] Among them, the duration can be the time when the weight continuously increases. The time threshold can refer to the threshold set for the duration.

[0078] Exemplarily, when the brain status monitoring device detects that the status change data of the head weight is greater than the preset weight change threshold, it can judge the duration when the head weight change is mainly caused. If the duration is greater than or equal to the time threshold, it can indicate that the head weight is continuously increasing, which can further indicate that the brain weight is continuously increasing, that is, the brain edema may be continuously deteriorating severely. Thus, a warning result for the brain status change can be generated based on the status change data. For example, a result of the severity of brain edema can be generated based on the continuously increasing status data.

[0079] If the duration is less than the time threshold, it indicates that the weight increase may occur instantaneously. It may be due to the patient's turning over action or other action operations during the monitoring process, which cause the instantaneous measurement value of the head weight measuring device to increase, resulting in a relatively large measurement error, rather than an increase in brain weight. Therefore, the detected status change data this time can be ignored, and there is no need to generate a warning result for the brain status change.

[0080] In this embodiment, by judging the duration of the status data change, it is determined whether the duration is greater than or equal to the time threshold. If so, a warning result for the brain status change is generated. If not, the result of this status data change is ignored, thereby ensuring the accuracy of the warning during the monitoring process.

[0081] In an exemplary embodiment, Figure 4 is a schematic flowchart of a method for monitoring the brain status provided by an embodiment of this application. Figure 3 , as Figure 4 shown, on the basis of Figure 2 , a further exemplary description of the method for monitoring the brain status is made. Among them, in the step of S204, after generating a warning result for the brain status change, it further includes S401 to S405, where:

[0082] S401. Display the warning result on the brain status monitoring device;

[0083] S402. And / or, send the warning result to the monitoring terminal connected to the brain status monitoring device;

[0084] S403. Receive the early warning feedback result fed back by the brain state monitoring device and / or the monitoring terminal;

[0085] S404. If the early warning feedback result indicates that the early warning result is correct, record the early warning result;

[0086] S405. If the early warning feedback result indicates that the early warning result is incorrect, eliminate the early warning result.

[0087] Exemplarily, the early warning result can be displayed in the brain state monitoring device, or the early warning result can be sent to the user's monitoring terminal. In this way, medical staff can determine whether the early warning result is correct in the brain state monitoring device or the monitoring terminal, and the brain state monitoring device can perform different actions after receiving the early warning feedback result. If the early warning feedback result indicates that the early warning result is correct, the brain state monitoring device can record the early warning result and upload the early warning result to the database for subsequent data use. If the early warning feedback result indicates that the early warning result is incorrect, the brain state monitoring device can ignore and eliminate the early warning result to achieve early warning correction.

[0088] In this embodiment, after the early warning result is generated, the error correction of the early warning result can be realized through the man-machine interaction method, which can ensure the accuracy of the monitoring data and thus improve the evaluation accuracy of the brain state change.

[0089] In an exemplary embodiment, the method further includes:

[0090] Respond to the nursing confirmation instruction and determine the weight change data corresponding to the nursing confirmation instruction;

[0091] Based on the weight change data, correct the state change data of the head weight.

[0092] Among them, the nursing confirmation instruction can refer to the instruction generated by the required nursing action. For example, if nursing operations such as changing the gauze on the patient's head are required, then after changing the nursing item, the weight may change.

[0093] Exemplarily, if the brain state monitoring device receives the nursing confirmation instruction, it can determine the weight change data generated corresponding to the nursing confirmation instruction. For example, it may be the change data of weight increase or weight decrease. The brain state monitoring device can correct the state change data of the head weight according to the weight change data. For example, if the weight of the nursing item increases by n grams, then after the nursing action ends, the head weight also increases by n grams, which can indicate that the head weight has not changed.

[0094] Optionally, the weight change data may be data input through a brain state monitoring device. For example, medical staff can input the weight change data of nursing articles when performing nursing actions. In this way, the weight change data can be accurately determined.

[0095] In this embodiment, by responding to the nursing confirmation instruction, the weight change data corresponding to the nursing confirmation instruction can be determined; and by correcting the state change data of the head weight based on the weight change data, it is beneficial to correct the weight error caused by nursing and other actions, and further improve the accuracy of monitoring the head weight. Moreover, in this embodiment, by correcting the error, the initial head weight is always maintained for monitoring, which is more conducive to monitoring the state change in the initial state and can further improve the monitoring accuracy.

[0096] In an exemplary embodiment, the method further includes:

[0097] Responding to the nursing confirmation instruction to determine the head weight after the end of the nursing corresponding to the nursing confirmation instruction;

[0098] Taking the head weight after the end of the nursing as the updated initial head weight.

[0099] Exemplarily, if the brain state monitoring device receives a nursing confirmation instruction, after the nursing action corresponding to the nursing confirmation instruction ends, the initial weight of the head is re-determined, and re-monitoring can be performed with the updated initial head weight. In this way, the weight error caused by the nursing action can also be corrected.

[0100] In an exemplary embodiment, the brain state monitoring device is further used to connect to an angle sensor, and the angle sensor is used to measure the head elevation angle formed between the head and the horizontal direction in the lying state; in the step of S202, the weight monitoring data continuously measured by the head weight measuring device is obtained, including:

[0101] Obtaining the head elevation angle measured by the angle sensor;

[0102] Based on the head elevation angle, correcting the weight measurement data directly measured by the head weight measuring device to obtain the weight monitoring data.

[0103] Exemplarily, during the treatment process of the patient, the head elevation angle of the hospital bed is often adjusted (such as lying flat, 30°, 45°), which will cause the change of the head weight distribution and thus affect the measurement accuracy. In this application, by integrating the angle sensor module and measuring the head elevation angle of the patient's hospital bed in real time, the weight deviation caused by the angle change can be eliminated by combining the correction algorithm to ensure the measurement accuracy.

[0104] Optionally, the change in the headboard angle can be detected by using a 6-axis inertial measurement unit (IMU) in combination with a gyroscope and an accelerometer.

[0105] Optionally, the weight measurement data can be corrected by the following expression:

[0106] W corrected =W measured ×cos(θ)

[0107] where W measured is the weight measured by the head weight measurement device; Wcorrected is the corrected weight monitoring data; and θ is the raised angle of the headboard.

[0108] In this embodiment, by using the raised angle of the head, the weight measurement data is corrected, so as to further improve the accuracy of head weight monitoring, and further improve the accuracy of brain state assessment.

[0109] In an exemplary embodiment, the method further includes:

[0110] When the state change data of the head weight is greater than a preset weight change threshold, obtaining the brain state corresponding to the state change data of the head weight as brain state sample data;

[0111] Inputting the state change data into a pre-constructed and to-be-trained brain state determination model, and outputting brain state prediction data through the brain state determination model;

[0112] Training the brain state determination model based on the brain state sample data and the brain state prediction data to obtain a trained brain state determination model; wherein, the brain state determination model is used to determine the brain state through the state change data of the head weight.

[0113] Exemplarily, when the state change data of the head weight is greater than a preset weight change threshold, the symptom severity of the brain state corresponding to the state change data of the head weight can be determined, and this can be used as the sample data of the brain state severity.

[0114] The state change data can be input into the brain state determination model to be trained, and through this brain state determination model, the prediction data of the brain state can be predicted. And the brain state determination model can be trained through the brain state sample data and the brain state prediction data to obtain a brain state determination model with accurate prediction of the brain state severity. In this way, subsequently, by inputting the state change data of the head weight into the brain state determination model, the symptom severity of the brain state can be directly obtained, thereby improving the monitoring efficiency of the brain state and timely discovering the disease risks existing in the patient.

[0115] In some specific embodiments, the present application directly captures minute changes in head weight through brain weight measurement. The elevation angle of the head of the bed is monitored in real time through angle correction to correct measurement errors caused by body position changes. Through data processing and display, the weight and angle data are fused and processed, and the corrected weight change trend is output. The present application can achieve a portable design of the brain state monitoring device, making the device compact and suitable for ICU, postoperative management, and first aid scenarios.

[0116] Optionally, the present application can achieve real-time display of the corrected weight change through a display and storage module, supporting data storage and trend analysis. For example, an LCD or OLED display screen can be used to display the current brain weight and change curve. The historical data can also be recorded through a data storage module using an SD card or an internal storage chip, supporting export and analysis.

[0117] Optionally, the present application also provides a head fixation module, which can ensure the stability of the patient's head at the measurement position and avoid data errors caused by slight head movement. For example, a flexible material (such as a silicone support pad) can be used to form a stable contact between the patient's head and the weight sensor. An adjustable bracket is equipped to adapt to different head shapes and body positions.

[0118] It should be understood that although the steps in the flowcharts involved in the above embodiments are sequentially shown according to the indications of the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same moment, but can be executed at different moments. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least a part of other steps or steps or stages in other steps.

[0119] The monitoring device for brain state provided by the embodiments of the present application will be described below. The monitoring device for brain state has the same inventive concept as the above-mentioned monitoring method for brain state. The implementation solutions provided by this device to solve problems are similar to the implementation solutions recorded in the above method. Therefore, the specific limitations in one or more embodiments of the monitoring device for brain state provided below can refer to the limitations on the monitoring method for brain state in the above text. The monitoring device for brain state described below and the monitoring method for brain state described above can be correspondingly referred to each other, and will not be repeated here.

[0120] In an exemplary embodiment, Figure 5The following is a schematic structural diagram of a brain state monitoring device provided by an embodiment of the present application. As Figure 5 shown, this device is applied to a brain state monitoring device, which is used to connect a head weight measurement device. The head weight measurement device is installed in the head placement area of the person to be monitored and is used to monitor the weight of the head of the person to be monitored in the lying state. The brain state monitoring device 50 includes: a monitoring instruction response module 510, a monitoring data acquisition module 520, a change data determination module 530, and a warning generation module 540, where:

[0121] The monitoring instruction response module 510 is configured to respond to a monitoring instruction and obtain the initial head weight at the start of the monitoring instruction through the head weight measurement device.

[0122] The monitoring data acquisition module 520 is configured to acquire the weight monitoring data continuously measured by the head weight measurement device.

[0123] The change data determination module 530 is configured to obtain the state change data of the head weight based on the initial head weight and the weight monitoring data.

[0124] The warning generation module 540 is configured to generate a warning result of a brain state change if the state change data of the head weight is greater than a preset weight change threshold; wherein, the weight change threshold is determined by a preset state change relationship between the head weight and the brain weight.

[0125] In an exemplary embodiment, the warning generation module is configured to determine the duration of the data change corresponding to the state change data; if the duration is greater than or equal to a time threshold, a warning result of a brain state change is generated based on the state change data.

[0126] In an exemplary embodiment, the warning generation module is further configured to display a warning result on the brain state monitoring device; and / or, send a warning result to a monitoring terminal connected to the brain state monitoring device; receive a warning feedback result fed back by the brain state monitoring device and / or the monitoring terminal; if the warning feedback result indicates that the warning result is correct, record the warning result; if the warning feedback result indicates that the warning result is incorrect, eliminate the warning result.

[0127] In an exemplary embodiment, the change data determination module is further configured to respond to a care confirmation instruction, determine the weight change data corresponding to the care confirmation instruction; and correct the state change data of the head weight based on the weight change data.

[0128] In an exemplary embodiment, the change data determination module is further configured to respond to a care confirmation instruction, determine the head weight after the end of the care corresponding to the care confirmation instruction; and use the head weight after the end of the care as the updated initial head weight.

[0129] In an exemplary embodiment, the brain state monitoring device is further configured to connect to an angle sensor, which is used to measure the head elevation angle formed between the head and the horizontal direction in the lying state.

[0130] The monitoring data acquisition module is configured to acquire the head elevation angle measured by the angle sensor; and based on the head elevation angle, correct the weight measurement data directly measured by the head weight measurement device to obtain the weight monitoring data.

[0131] In an exemplary embodiment, the device further includes a model construction module. The model construction module is configured to, when the state change data of the head weight is greater than a preset weight change threshold, acquire the brain state corresponding to the state change data of the head weight as the brain state sample data; input the state change data into a pre-constructed and to-be-trained brain state determination model, and output the brain state prediction data through the brain state determination model; and based on the brain state sample data and the brain state prediction data, train the brain state determination model to obtain a trained brain state determination model; wherein, the brain state determination model is configured to determine the brain state through the state change data of the head weight.

[0132] In an exemplary embodiment, the present application further provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by one or more processors, the one or more processors are caused to execute the steps of the brain state monitoring method according to any one of the above embodiments.

[0133] In an exemplary embodiment, the present application further provides a computer device, in which a computer program is stored. When the computer-readable instructions are executed by one or more processors, the one or more processors are caused to execute the steps of the brain state monitoring method according to any one of the above embodiments.

[0134] In an exemplary embodiment, the present application further provides a computer program product, including a computer program, which when executed by a processor, implements the steps of the brain state monitoring method according to any one of the above embodiments.

[0135] Schematically, as Figure 6 shown, Figure 6 is an internal structural schematic diagram of a computer device provided by an embodiment of the present application. The computer device 600 can be provided as a server. Referring to Figure 6, the computer device 600 includes a processing component 602, which further includes one or more processors, and memory resources represented by a memory 601 for storing instructions executable by the processing component 602, such as application programs. The application programs stored in the memory 601 may include one or more modules each corresponding to a set of instructions. In addition, the processing component 602 is configured to execute instructions to perform the text recognition method of any of the above embodiments.

[0136] The computer device 600 may further include a power component 603 configured to perform power management of the computer device 600, a wired or wireless network interface 604 configured to connect the computer device 600 to a network, and an input / output (I / O) interface 605. The computer device 600 may operate based on an operating system stored in the memory 601, such as Windows Server TM, Mac OS XTM, Unix TM, Linux TM, Free BSDTM or the like.

[0137] Those skilled in the art can understand that Figure 6 the structure shown in

[0138] is only a block diagram of some structures related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different component arrangement.

[0139] Finally, it should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, article or device including the element.

[0140] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The various embodiments can be combined as needed, and the same or similar parts can be referred to each other.

[0141] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for monitoring brain status, characterized in that: Applied to a brain state monitoring device, the brain state monitoring device is used to connect to a head weight measuring device, the head weight measuring device is installed in the head placement area of ​​the monitored person, and is used to monitor the head weight of the monitored person in a lying state; the method comprises: In response to the monitoring instruction, obtaining, by the head weight measuring device, an initial head weight at the start of the monitoring instruction; Acquiring weight monitoring data continuously measured by the head weight measuring device; Obtaining state change data of the head weight according to the initial head weight and the weight monitoring data; If the state change data of the head weight is greater than a preset weight change threshold, an early warning result of a brain state change is generated; wherein the weight change threshold is determined by a preset state change relationship between the head weight and the brain weight.

2. The method according to claim 1, characterized in that The generating of the early warning result of the brain state change includes: Determining the duration of the data change corresponding to the state change data; If the duration is greater than or equal to the time threshold, a warning result of the brain state change is generated based on the state change data.

3. The method according to claim 1 or 2, characterized in that: After generating the early warning result of the brain state change, the method further includes: Displaying the warning result on the brain status monitoring device; and / or, sending the early warning result to a monitoring terminal connected to the brain status monitoring device; Receiving early warning feedback results fed back by the brain state monitoring device and / or the monitoring terminal; If the warning feedback result indicates that the warning result is correct, then the warning result is recorded; If the warning feedback result indicates that the warning result is wrong, the warning result is discarded.

4. The method according to claim 1, characterized in that The method further comprises: In response to a nursing confirmation instruction, determining weight change data corresponding to the nursing confirmation instruction; Based on the weight change data, the state change data of the head weight is corrected.

5. The method according to claim 1 or 4, characterized in that: The method further comprises: In response to the nursing confirmation instruction, determining the head weight after the nursing corresponding to the nursing confirmation instruction is completed; The head weight after the treatment was completed was used as the updated initial head weight.

6. The method according to claim 1, characterized in that The brain state monitoring device is also used to connect to an angle sensor, and the angle sensor is used to measure the head shaking angle formed between the head and the horizontal direction when the head is lying down; The obtaining of the head weight continuously measured by the head weight measuring device comprises: Obtaining the head shaking angle measured by the angle sensor; Based on the head tilt angle, the weight measurement data directly measured by the head weight measurement device is corrected to obtain the weight monitoring data.

7. The method according to claim 1, characterized in that The method further comprises: When the state change data of the head weight is greater than a preset weight change threshold, obtaining the brain state corresponding to the state change data of the head weight as the brain state sample data; Inputting the state change data into a pre-built and to-be-trained brain state determination model, and outputting brain state prediction data through the brain state determination model; Based on the brain state sample data and the brain state prediction data, the brain state determination model is trained to obtain a trained brain state determination model; wherein the brain state determination model is used to determine the brain state through the state change data of the head weight.

8. A device for monitoring brain status, characterized in that: Applicable to a brain state monitoring device, the brain state monitoring device is used to connect to a head weight measuring device, the head weight measuring device is installed in the head placement area of ​​the monitored person, and is used to monitor the head weight of the monitored person in a lying state; the device comprises: A monitoring instruction corresponding module, used for obtaining the initial head weight at the start of the monitoring instruction through the head weight measuring device in response to the monitoring instruction; A monitoring data acquisition module, used to acquire weight monitoring data continuously measured by the head weight measurement device; A change data determination module, used to obtain state change data of the head weight according to the weight monitoring data; The warning generation module is used to generate a warning result of brain state change if the state change data of the head weight is greater than a preset weight change threshold; wherein the weight change threshold is determined by a preset state change relationship between the head weight and the brain weight.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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