Electrical impedance tomography system for controlling hydrocephalus shunting and storage medium

Abstract

The invention relates to an electrical impedance tomography system for controlling hydrocephalus shunting and a storage medium, the electrical impedance tomography system for controlling hydrocephalus shunting comprises a brain impedance evaluation model module, an electrical impedance data acquisition module, a control module, a pressure-adjustable valve and a group of electrodes annularly distributed on the head of a human body; the brain impedance evaluation model module is used for generating a local area standard impedance range based on the physiological characteristic parameters of the patient; the local regions are a plurality of regions divided by the brain impedance evaluation model module into the whole brain; the electrical impedance data acquisition module is used for acquiring real-time local impedance sent by the electrodes; the real-time local impedance corresponds to a local area where the hydrocephalus position of the patient is located; and the control module is used for adjusting the pressure value of the pressure-adjustable valve based on the real-time local impedance and the local area standard impedance range. According to the invention, the problem of poor timeliness of hydrocephalus shunting is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of electrical impedance tomography, and in particular to an electrical impedance tomography system for controlling hydrocephalus shunt and a storage medium. BACKGROUND

[0002] Hydrocephalus is a neurological disease caused by imbalance of cerebrospinal fluid dynamics, which leads to abnormal expansion of the ventricular system. In clinical practice, ventriculo-peritoneal shunt (V-P Shunt) is often used for treatment. This surgery uses a pressure-adjustable valve to regulate cerebrospinal fluid drainage. After the surgery, doctors can adjust the opening pressure of the valve externally and non-invasively to control the flow rate, thereby achieving an ideal shunt effect. Electrical impedance tomography (EIT) is a non-invasive medical functional imaging technology that can reconstruct the electrical impedance distribution in the body by collecting signals from body surface electrodes. Based on the fact that the electrical conductivity of cerebrospinal fluid is much higher than that of surrounding brain tissue, it can identify the ventricular expansion area and provide technical support for hydrocephalus assessment. However, in the related art, the pressure parameter adjustment of the pressure-adjustable valve relies on manual setting by doctors after clinical evaluation, which cannot dynamically respond to the patient's real-time condition and has the problem of poor adjustment timeliness, which may lead to delayed drainage or excessive drainage risk.

[0003] Currently, there is no effective solution to the problem of poor timeliness of hydrocephalus shunt in the related art. SUMMARY

[0004] The embodiments of the present application provide an electrical impedance tomography system for controlling hydrocephalus shunt and a storage medium to at least solve the problem of poor timeliness of hydrocephalus shunt in the related art.

[0005] In a first aspect, the embodiments of the present application provide an electrical impedance tomography system for controlling hydrocephalus shunt, which comprises: a brain impedance evaluation model module, an electrical impedance data acquisition module, a control module, a pressure-adjustable valve, and a set of ring-shaped electrodes distributed around the head of a human body.

[0006] The brain impedance evaluation model module is configured to generate a local region standard impedance range based on physiological characteristic parameters of a patient. The local region is a plurality of regions into which the brain impedance evaluation model module divides the whole brain.

[0007] The electrical impedance data acquisition module is configured to acquire real-time local impedance sent by the electrodes. The real-time local impedance corresponds to a local region where the patient's hydrocephalus is located.

[0008] The control module is configured to adjust the pressure value of the pressure-adjustable valve based on the real-time local impedance and the local region standard impedance range.

[0009] In some embodiments, the control module is further configured to decrease the pressure value of the adjustable pressure valve when the real-time local impedance is lower than the local region standard impedance range.

[0010] In some embodiments, the control module is further configured to decrease the pressure value of the adjustable pressure valve according to a preset gear based on a deviation value between the real-time local impedance and a lower limit of the local region standard impedance range.

[0011] In some embodiments, the control module is further configured to increase the pressure value of the adjustable pressure valve when the real-time local impedance is higher than the local region standard impedance range.

[0012] In some embodiments, the control module is further configured to increase the pressure value of the adjustable pressure valve according to a preset gear based on a deviation value between the real-time local impedance and an upper limit of the local region standard impedance range.

[0013] In some embodiments, the electrical impedance data acquisition module is further configured to acquire real-time whole brain impedance sent by the electrode;

[0014] The brain impedance evaluation model module is further configured to generate a whole brain standard impedance range based on a body mass index and a head circumference of the patient.

[0015] The control module is further configured to adjust the pressure value of the adjustable pressure valve based on the real-time local impedance, the local region standard impedance range, the real-time whole brain impedance, and the whole brain standard impedance range.

[0016] In some embodiments, the control module is further configured to send an alarm information to a preset terminal when the real-time local impedance is within the local region standard impedance range and the real-time whole brain impedance is outside the whole brain standard impedance range.

[0017] In some embodiments, the control module is further configured to send an alarm information to a preset terminal when the real-time local impedance is within the local region standard impedance range and the real-time whole brain impedance is outside the whole brain standard impedance range.

[0018] In some embodiments, the system further comprises a storage module.

[0019] The storage module is configured to store real-time local impedance data, adjustable pressure valve data, and alarm information during monitoring and send them to a preset terminal.

[0020] In some embodiments, the physiological characteristic parameters include a body mass index and a head circumference.

[0021] The brain impedance evaluation model module is further configured to input the body mass index and the head circumference of the patient into the trained brain impedance evaluation model for processing to generate the local region standard impedance range.

[0022] In a second aspect, the embodiments of the present application provide a storage medium having a computer program stored thereon, which, when executed by a processor, implements the working of the electrical impedance tomography system for controlling shunt of hydrocephalus as described in the first aspect.

[0023] Compared with the related art, the electrical impedance tomography system for controlling shunt of hydrocephalus and the storage medium provided by the embodiments of the present application, wherein the system comprises: a brain impedance evaluation model module, an electrical impedance data acquisition module, a control module, an adjustable pressure valve, and a set of ring-shaped electrodes distributed around the head of a human body; the brain impedance evaluation model module is configured to generate a local region standard impedance range based on physiological characteristic parameters of a patient; a local region is a plurality of regions into which the brain impedance evaluation model module divides the whole brain; the electrical impedance data acquisition module is configured to acquire real-time local impedance sent by the electrodes; the real-time local impedance corresponds to a local region where a hydrocephalus position of the patient is located; and the control module is configured to adjust a pressure value of the adjustable pressure valve based on the real-time local impedance and the local region standard impedance range, thereby solving the problem of poor timeliness in shunt of hydrocephalus.

[0024] The details of one or more embodiments of the present application are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the present application will be apparent from the description of the embodiments and from the claims. BRIEF DESCRIPTION OF DRAWINGS

[0025] The accompanying drawings, which are included to provide a further understanding of the present application and are incorporated in and constitute a part of this application, illustrate embodiments of the present application and together with the description serve to explain the present application. In the drawings:

[0026] Figure 1 FIG. 1 is a hardware structure block diagram of a terminal of an electrical impedance tomography system for controlling shunt of hydrocephalus according to an embodiment of the present application;

[0027] Figure 2 FIG. 2 is a structure block diagram of an electrical impedance tomography system for controlling shunt of hydrocephalus according to an embodiment of the present application;

[0028] Figure 3 FIG. 3 is a whole brain division schematic diagram according to an embodiment of the present application;

[0029] Figure 4 FIG. 4 is a flowchart of hydrocephalus monitoring and regulation according to an embodiment of the present application. DETAILED DESCRIPTION

[0030] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be described and explained below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application and should not be used to limit the present application. Based on the embodiments provided by the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of the present application. In addition, it should be understood that, although the efforts made in this development process can be complex and lengthy, some design, manufacture or production changes made on the basis of the technical content disclosed in the present application by those of ordinary skill in the art related to the content disclosed in the present application are only routine technical means and should not be understood as insufficient disclosure of the present application.

[0031] In the present application, the term "embodiment" means that the specific features, structures or properties described in conjunction with the embodiment can be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment to other embodiments. Those of ordinary skill in the art explicitly and implicitly understand that the embodiments described in the present application can be combined with other embodiments without conflict.

[0032] Unless otherwise defined, the technical terms or scientific terms involved in the present application should be understood as the usual meaning understood by those of ordinary skill in the art to which the present application belongs. The terms "one", "a", "an", "the", and the like similar words involved in the present application do not represent quantity limitation, but can represent singular or plural. The terms "include", "contain", "have", and any variations thereof involved in the present application are intended to cover non-exclusive inclusion; for example, a process, method, system, product or device including a series of steps or modules (units) is not limited to the listed steps or units, but can also include steps or units not listed, or can also include other steps or units inherent to these processes, methods, products or devices. The terms "connected", "connected", "coupled" and the like similar words involved in the present application are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. The term "multiple" involved in the present application means greater than or equal to two. The term "and / or" describes the association between the associated objects, which means that there can be three relationships, for example, "A and / or B" can represent three cases: A exists alone, A and B exist together, and B exists alone. The terms "first", "second", "third" and the like involved in the present application are only to distinguish similar objects, and do not represent a specific order for the objects.

[0033] The method embodiments provided by the present embodiment can be executed in a terminal, a computer or a similar computing device. Taking the case of running on a terminal,Figure 1 is a hardware structure block diagram of a terminal of a control hydrocephalus shunt electrical impedance tomography system according to an embodiment of the present application. As shown in Figure 1 , the terminal can include one or more (only one is shown in Figure 1 ) processor 102 (the processor 102 can include but not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data, optionally, the above terminal can also include a transmission device 106 for communication function and an input and output device 108. Those skilled in the art can understand that Figure 1 the structure shown is only schematic, which does not limit the structure of the above terminal. For example, the terminal can also include more or less components than those shown in Figure 1 , or have a different configuration from Figure 1 .

[0034] The memory 104 can be used to store computer programs, for example, software programs of application software and modules, such as the computer program corresponding to the control hydrocephalus shunt electrical impedance tomography system in the embodiments of the present application. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, implements the above method. The memory 104 can include a high-speed random access memory, and can also include a non-volatile memory, such as one or more magnetic storage devices, flash memories, or other non-volatile solid-state memories. In some examples, the memory 104 can further include a memory remotely arranged with respect to the processor 102, which can be connected to the terminal through a network. Examples of the above network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0035] The transmission device 106 is used to receive or send data via a network. The specific examples of the above network can include a wireless network provided by the communication provider of the terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, NIC) which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (Radio Frequency, RF) module which is used to communicate with the Internet in a wireless manner.

[0036] Hydrocephalus is a neurological disease caused by the imbalance of cerebrospinal fluid (CSF) dynamics, leading to abnormal expansion of the ventricular system. The core problem is the excessive accumulation of intracranial cerebrospinal fluid, which may cause intracranial pressure to rise, nerve function to be damaged, and other serious consequences. Therefore, timely intervention is required to avoid disease deterioration. At present, ventriculo-peritoneal shunt (V-P Shunt) is a mature and mainstream solution for treating hydrocephalus. This surgery constructs a cerebrospinal fluid drainage pathway by implanting a pressure-adjustable valve. After the surgery, doctors can adjust the opening pressure of the valve externally and non-invasively to individualize the control of cerebrospinal fluid flow, which can theoretically achieve a shunt effect that meets the individual needs of patients.

[0037] Electrical impedance tomography (EIT) is a new non-invasive medical functional imaging technology that provides important technical support for the evaluation of hydrocephalus. Its working principle is to arrange an electrode array on the surface of the human body, inject a safe current, and measure the surface voltage between the electrodes. The impedance distribution and changes in the body are reconstructed by combining the correlation between voltage and current. Because the electrical conductivity of cerebrospinal fluid is much higher than that of surrounding brain tissue, EIT can accurately identify the area of ventricular expansion (i.e., cerebrospinal fluid accumulation), directly reflect the location and range of hydrocephalus, and has the advantages of no ionizing radiation, repeatable measurement, fast imaging speed, and significant potential in real-time monitoring of dynamic changes in organ function.

[0038] However, there are still key technical bottlenecks in the clinical application of ventriculo-peritoneal shunt. The main problem lies in the pressure regulation of the adjustable pressure valve. In traditional technology, the adjustment of the valve pressure parameter completely depends on the doctor's assessment or clinical symptom judgment, and cannot be dynamically adjusted based on the patient's real-time condition. This "manual adjustment" mode has obvious time defects. When the amount of intracranial cerebrospinal fluid changes (e.g., increased cerebrospinal fluid accumulation requires increased drainage, and excessive drainage requires reduced drainage), doctors are difficult to capture the changes in the patient's condition and adjust the valve parameters in a timely manner, which may lead to a sudden rise in intracranial pressure due to delayed drainage or complications such as subdural hematoma and low intracranial pressure due to excessive drainage.

[0039] At the same time, traditional technology lacks long-term and continuous monitoring of the patient's postoperative brain state. In clinical practice, complications such as shunt tube blockage and valve dysfunction are common postoperative risks, and traditional monitoring methods (such as regular imaging) cannot achieve real-time warning, often requiring the patient to have obvious clinical symptoms such as headache, vomiting, and abnormal consciousness before the problem is discovered, delaying the intervention opportunity and increasing the patient's treatment risk and medical burden.

[0040] To solve the above problems, the present embodiment provides an electrical impedance tomography system for controlling hydrocephalus shunt, Figure 2is a structural block diagram of a control hydrocephalus shunt electrical impedance tomography system according to an embodiment of the present application, as shown in the figure, the system comprises: a brain impedance evaluation model module 21, an electrical impedance data acquisition module 22, a control module 23, an adjustable pressure valve 24 and a set of ring-shaped electrodes 25 distributed on the head of the human body; Figure 2

[0041] The brain impedance evaluation model module 21 is used to generate a local area standard impedance range based on the physiological characteristic parameters of the patient; the local area is a plurality of areas into which the brain impedance evaluation model module 21 divides the whole brain;

[0042] The electrical impedance data acquisition module 22 is used to acquire real-time local impedance sent by the electrodes 25; the real-time local impedance corresponds to the local area where the hydrocephalus of the patient is located;

[0043] The control module 23 is used to adjust the pressure value of the adjustable pressure valve 24 based on the real-time local impedance and the local area standard impedance range.

[0044] The brain impedance evaluation model module 21 is the core of the system to realize personalized standard generation, and its core function is to construct a local area standard impedance range suitable for the patient based on the physiological characteristic parameters of the individual patient. The local area standard impedance range refers to the impedance normal fluctuation interval corresponding to the local area where the hydrocephalus of the patient is located, which is generated by the brain impedance evaluation model after the whole brain is divided into a plurality of areas based on the physiological characteristic parameters of the patient. In actual application, the module will first divide the whole brain of the patient into a plurality of independent local areas according to the preset zoning logic (which can be 4-zone, 6-zone or 8-zone division mode, such as division according to the anatomical positions of the left, right, front and back of the brain), to ensure that the subsequent monitoring can accurately locate to the area where the hydrocephalus is located; then, the module receives the physiological characteristic parameters of the patient (mainly including the body mass index BMI and the head circumference, wherein the BMI is calculated by “weight (kg) / height² (m²)”, and the head circumference is the measured value of the circumference of the head of the patient), and combines the brain impedance evaluation model trained through machine learning (the model is constructed based on a large number of brain impedance data, BMI and head circumference parameters of normal people and patients with confirmed hydrocephalus, and has the ability to match the corresponding impedance standard according to the individual physiological characteristics), to finally generate the standard impedance range corresponding to each local area. This range is not a universal threshold, but a “personalized reference” highly adapted to the physiological characteristics of the individual patient, which provides a key reference for subsequent judgment of the hydrocephalus drainage state.

[0045] ​The electrical impedance data acquisition module 22 assumes the role of real-time data entry, focusing on accurately obtaining real-time local impedance data transmitted by the electrode 25, and the data must strictly correspond to the local area where the patient's hydrocephalus is located. During system operation, a set of ring-shaped electrodes 25 (such as 16 electrodes) distributed around the head of the human body directly contact the skin of the head, convert intracranial impedance changes into transmittable electrical signals by injecting a safe current and measuring the voltage between electrodes; After receiving these raw electrical signals, the electrical impedance data acquisition module 22 will first perform signal amplification, filtering and other preprocessing operations to eliminate invalid data caused by environmental noise or skin contact interference, and then accurately extract real-time impedance data (i.e. real-time local impedance) of the local area corresponding to the hydrocephalus location confirmed by CT / MRI (computed tomography / magnetic resonance imaging) before surgery, ensuring that the collected data can directly reflect the current state of the hydrocephalus area, providing real and effective real-time data support for subsequent decision-making.

[0046] The control module 23 serves as the decision-making center of the system, and its core role is to dynamically adjust the pressure value of the adjustable pressure valve 24 based on the comparison results of real-time local impedance and local area standard impedance range, to realize intelligent regulation and control of hydrocephalus drainage. In specific operation, the control module 23 will synchronously receive two types of key data: one is the real-time local impedance (reflecting the impedance state of the current hydrocephalus area) transmitted by the electrical impedance data acquisition module 22, and the other is the corresponding local area standard impedance range (reflecting the normal impedance interval of this patient in this area) generated by the brain impedance evaluation model module 21; Subsequently, the control module 23 compares the real-time local impedance with the standard impedance range to determine whether the current hydrocephalus drainage is in a reasonable state. If the real-time local impedance is lower than the standard impedance range, it indicates that there is too much accumulation of cerebrospinal fluid in the hydrocephalus area (because the electrical conductivity of cerebrospinal fluid is higher than that of brain tissue, too much cerebrospinal fluid will cause the local impedance to decrease), at this time the control module 23 will generate an instruction to "lower the adjustable pressure valve pressure value", by reducing the opening pressure of the adjustable pressure valve 24, to speed up the cerebrospinal fluid drainage speed and reduce intracranial fluid accumulation; If the real-time local impedance is higher than the standard impedance range, it indicates that the cerebrospinal fluid drainage is excessive (the proportion of brain tissue increases, and the impedance rises accordingly), and the control module 23 will generate an instruction to "raise the adjustable pressure valve pressure value", by increasing the opening pressure of the adjustable pressure valve 24, to slow down the drainage speed and avoid complications such as low intracranial pressure and subdural hematoma caused by excessive drainage. The entire adjustment process does not require human intervention and is completely automated based on the comparison of real-time data and individualized standards, effectively solving the problem of poor timeliness in traditional manual adjustment.

[0047] The adjustable pressure valve 24 and a set of ring-shaped electrodes 25 distributed around the head of the patient serve as the execution end and signal collection end of the system, and are closely matched with the control module 23 and the electrical impedance data acquisition module 22, respectively: the adjustable pressure valve 24 receives the pressure adjustment instruction from the control module 23, changes the opening pressure of the adjustable pressure valve 24 through an extracorporeal non-invasive method (without the need for a second operation), and directly regulates the cerebrospinal fluid flow; the electrodes 25 are precisely arranged in a ring shape to ensure that the impedance signals of the local area where the hydrocephalus is located can be collected, and provide high-quality raw data for the electrical impedance data acquisition module 22, both of which together constitute an important support for the system to realize the "real-time monitoring-dynamic regulation" closed loop.

[0048] In the above embodiment, the system generates the local area standard impedance range of the individual (the whole brain needs to be divided into multiple areas) based on the physiological characteristic parameters (such as body mass index, head circumference) of the patient through the brain impedance evaluation model module 21, combines the real-time local impedance data of the electrodes corresponding to the patient's hydrocephalus position obtained by the electrical impedance data acquisition module 22, and then automatically adjusts the pressure value of the adjustable pressure valve 24 by comparing the real-time local impedance with the local area standard impedance range through the control module 23. On the one hand, it solves the time efficiency problem of the traditional ventriculo-peritoneal shunt relying on manual adjustment of the valve pressure by the doctor, can dynamically respond based on the real-time condition of the patient, and avoids the risk of delayed or excessive drainage; on the other hand, it precisely locates the local area where the hydrocephalus is located, and regulates based on the personalized standard impedance range, improving the accuracy and adaptability of hydrocephalus drainage; on the other hand, it integrates non-invasive electrical impedance signal acquisition and automatic valve regulation, realizes continuous monitoring and dynamic intervention, and does not need invasive operation, taking into account the safety and convenience of treatment, effectively making up for the defects of the traditional scheme that can only treat but cannot be monitored and automatically regulated in real time for a long time.

[0049] In some embodiments, the control module is further configured to reduce the pressure value of the adjustable pressure valve when the real-time local impedance is lower than the local area standard impedance range.

[0050] Specifically, when the control module synchronously receives the real-time local impedance corresponding to the local area where the patient's hydrocephalus is located transmitted by the electrical impedance data acquisition module, and the standard impedance range of the local area generated by the brain impedance evaluation model module, it will judge whether the real-time local impedance is within the standard range through data comparison; if it is found that the real-time local impedance is lower than the standard impedance range of the local area, combined with the physiological characteristics that the conductivity of cerebrospinal fluid is much higher than that of surrounding brain tissue (the accumulation of cerebrospinal fluid will cause the local impedance to decrease), it can be determined that there is an excessive accumulation of cerebrospinal fluid in the current patient's hydrocephalus area. At this time, the control module will automatically generate a control instruction of "reducing the pressure value of the adjustable pressure valve", which is transmitted to the adjustable pressure valve through the extracorporeal non-invasive control link, so as to reduce the opening pressure of the valve and thus accelerate the drainage speed of cerebrospinal fluid, reduce the amount of intracranial fluid, and make the local impedance of the hydrocephalus area gradually return to the standard range. The whole process does not need manual intervention, and realizes dynamic and timely response to the accumulation of cerebrospinal fluid.

[0051] The above embodiment first effectively solves the time-consuming problem of the traditional ventriculo-peritoneal shunt relying on manual adjustment of the valve pressure by the doctor. In the traditional technology, the doctor needs to adjust the parameters after judging the condition through clinical evaluation or image examination, which is easy to cause the accumulation of cerebrospinal fluid to be aggravated due to the delayed response. However, the function can automatically trigger the pressure reduction control based on real-time impedance data, greatly shortening the time from "finding excessive fluid accumulation" to "executing drainage adjustment", and reducing the risk of sudden increase of intracranial pressure. Secondly, the function takes "real-time local impedance lower than the standard range" as the clear control trigger condition, combined with the personalized local area standard impedance range of the patient (generated by the brain impedance evaluation model module based on physiological characteristic parameters such as body mass index and head circumference), which avoids the problem of insufficient adaptability of the general control threshold, so that the pressure adjustment is more suitable for the individual condition of the patient, and reduces the poor drainage effect caused by insufficient control accuracy. At the same time, the function replaces manual operation through automatic control, reduces the repetitive labor of medical staff, and the control process is based on non-invasive electrical impedance monitoring data, without additional invasive examination, which balances the treatment convenience and patient safety.

[0052] In some embodiments, the control module is further configured to reduce the pressure value of the adjustable pressure valve according to a preset gear based on the deviation value of the real-time local impedance from the lower limit of the local area standard impedance range.

[0053] Specifically, when the control module determines that the real-time local impedance is lower than the local region standard impedance range through comparison, instead of adopting a fixed amplitude pressure adjustment, it first calculates the deviation value between the real-time local impedance and the lower limit of the local region standard impedance range (i.e. the difference value of "standard range lower limit-real-time local impedance"), and then calls the system preset gear adjustment rule (which is set based on a large amount of clinical data and a pre-trained impedance change-drainage effect correlation model, for example, a deviation value of 0-5Ω corresponds to 1 gear pressure reduction, 5-10Ω corresponds to 2 gear pressure reduction, etc., and the specific gear division can be adapted to different patient physiological characteristics); then, the control module matches the corresponding pressure reduction gear according to the calculated deviation value, generates a precise pressure adjustment instruction and transmits it to the adjustable pressure valve, so that the valve pressure value is reduced in steps according to the preset gear, the larger the deviation value, the higher the corresponding pressure reduction gear, the more obvious the drainage speed improvement, ensuring that when there is a large amount of cerebrospinal fluid accumulation, it can be quickly drained, and when the accumulation is small, it is slowly adjusted to avoid excessive drainage caused by sudden pressure drop.

[0054] In the above embodiments, this sub-gear control function first significantly improves the accuracy of valve pressure adjustment. Compared with fixed amplitude pressure reduction, its design of matching gears based on deviation values can dynamically adapt the pressure reduction degree according to the degree of cerebrospinal fluid accumulation, for example, when the real-time local impedance is slightly lower than the lower limit of the standard range (small deviation value), a small amplitude pressure reduction through low gear can avoid excessive drainage, and when the deviation value is large (more cerebrospinal fluid accumulation), a large amplitude pressure reduction through high gear can quickly relieve fluid accumulation problems, solving the possible control deficiency or excessive control defects of traditional single control amplitude; secondly, this function further enhances the individual adaptation ability of the system, combined with the patient individualized local region standard impedance range generated by the brain impedance evaluation model module (based on physiological parameters such as body mass index and head circumference), the deviation value calculation and gear matching are carried out around the patient's individual situation, avoiding the problem of insufficient adaptability of the general control strategy to different patients, making the drainage control more in line with the patient's actual condition; at the same time, the stepwise gear adjustment can reduce the impact of sudden changes in valve pressure on the intracranial environment, reduce the risk of complications such as low intracranial pressure and subdural hematoma caused by excessive pressure fluctuations, and form a closed loop of "accurate perception-graded response-safe control" with real-time impedance monitoring, further improving the clinical practicability and safety of the system.

[0055] In some embodiments, the control module is further configured to increase the pressure value of the adjustable pressure valve when the real-time local impedance is higher than the local region standard impedance range.

[0056] Specifically, when the control module synchronously receives the real-time local impedance corresponding to the local area where the patient's hydrocephalus is located transmitted by the electrical impedance data acquisition module, and the standard impedance range of the local area generated by the brain impedance evaluation model module, it will judge whether the real-time local impedance is within the standard range through data comparison; if it is monitored that the real-time local impedance is higher than the standard impedance range of the local area, combined with the characteristic that the electrical conductivity of cerebrospinal fluid is much higher than that of the surrounding brain tissue (cerebrospinal fluid reduction will lead to an increase in the proportion of local brain tissue, and then the impedance value will rise), it can be determined that the current patient's hydrocephalus region has an over-drainage of cerebrospinal fluid; at this time, the control module automatically generates a control instruction to "raise the pressure value of the adjustable pressure valve" without human intervention, and transmits it to the adjustable pressure valve through the extracorporeal non-invasive control link, prompting the valve to open and the pressure to rise. After the pressure rises, the cerebrospinal fluid drainage resistance increases and the drainage speed slows down, and then the intracranial cerebrospinal fluid volume gradually recovers to a reasonable level, promoting the real-time local impedance of the hydrocephalus region to return to the standard range, forming an automatic response closed loop of "monitoring-judgment-regulation".

[0057] The above embodiment first effectively solves the clinical risk of "over-drainage" in traditional ventriculo-peritoneal shunt (V-P Shunt), and through real-time impedance monitoring and automatic pressure regulation, it can quickly respond in the early stage of over-drainage to avoid further development of the disease. Secondly, this function continues the core advantage of "personalized adaptation" of the system, and the standard impedance range of the local area is generated based on the patient's individual BMI and head circumference parameters, rather than a universal threshold, so that the judgment of "real-time local impedance higher than the standard range" is more in line with the patient's actual physiological state, and the pressure regulation is more targeted, avoiding misjudgment or inaccurate regulation caused by universal standard deviation. At the same time, this function and the mechanism of "lowering the pressure when the real-time local impedance is lower than the standard range" form a complement to each other, together covering the two abnormal scenarios of over-drainage and under-drainage of cerebrospinal fluid, improving the system's dynamic balance ability of intracranial cerebrospinal fluid volume, and further implementing the design goal of precise monitoring and shunt regulation of hydrocephalus through impedance imaging, and improving the safety and reliability of the system in clinical application.

[0058] In some embodiments, the control module is further configured to raise the pressure value of the adjustable pressure valve according to a preset gear based on the deviation value of the real-time local impedance from the upper limit of the standard impedance range of the local area.

[0059] Specifically, when the control module determines that the real-time local impedance is higher than the local area standard impedance range, instead of directly adopting a fixed amplitude boost, the control module first calculates the deviation value of the real-time local impedance from the upper limit of the standard impedance range (i.e., the difference between the real-time local impedance and the upper limit of the standard impedance range), and then calls a system preset gear adjustment rule (the rule is set based on a large amount of clinical data and a pre-trained impedance change-drainage effect correlation model, such as a deviation value of 0-5Ω corresponding to a 1-gear boost, a deviation value of 5-10Ω corresponding to a 2-gear boost, etc., and the gear amplitude can be adapted to the individual condition of the patient); subsequently, the control module matches the corresponding boost gear according to the deviation value, generates a precise pressure adjustment instruction, and transmits the instruction to the adjustable pressure valve, so that the valve pressure is increased in a stepwise manner according to the preset gear, the larger the deviation value, the higher the corresponding boost gear, the more significant the improvement of the drainage resistance, and when the over-drainage of cerebrospinal fluid is more serious, the drainage speed can be quickly slowed down, and when the over-drainage is slight, the pressure is adjusted slightly, so as to avoid a large fluctuation of intracranial pressure caused by a sudden increase in pressure.

[0060] The above embodiment first greatly improves the accuracy and safety of drainage control. Compared with fixed amplitude boost, the design of dynamically matching gears based on the deviation value can adapt the boost pressure to the degree of over-drainage of cerebrospinal fluid, for example, when the real-time local impedance is slightly higher than the upper limit of the standard range (small deviation value), a low-gear small-amplitude boost can avoid a sudden increase in intracranial pressure, and when the deviation value is large (serious over-drainage), a high-gear large-amplitude boost can quickly restore the cerebrospinal fluid volume, solving the defects of "insufficient control" (unable to timely alleviate over-drainage) or "excessive control" (causing a sudden increase in intracranial pressure) that may exist in traditional single control amplitude. Secondly, the function further enhances the individual adaptation ability of the system. Combined with the patient's individual standard impedance range generated by the brain impedance evaluation model module, the deviation value calculation and gear matching are carried out around the individual physiological characteristics of the patient, avoiding the problem of insufficient adaptability of the general control strategy to patients with different BMI and head circumference. At the same time, the stepwise gear adjustment can smoothly control the recovery process of the intracranial cerebrospinal fluid volume, reduce the impact on the brain tissue, and reduce the risk of nerve function damage caused by pressure fluctuation. In combination with real-time impedance monitoring, a closed loop of "accurate perception-graded response-smooth control" is formed, further improving the reliability of the system in clinical application, and effectively making up for the deficiency of traditional manual adjustment relying on experience and being difficult to accurately adapt to individual differences.

[0061] In some embodiments, the electrical impedance data acquisition module is further configured to acquire real-time whole brain impedance sent by the electrodes;

[0062] The brain impedance evaluation model module is further configured to generate a whole brain standard impedance range based on the body mass index and the head circumference of the patient.

[0063] The control module is further configured to adjust the pressure value of the adjustable pressure valve based on the real-time local impedance, the local area standard impedance range, the real-time whole brain impedance, and the whole brain standard impedance range.

[0064] Specifically, the electrical impedance data acquisition module can not only obtain the real-time local impedance corresponding to the local area where the patient's hydrocephalus is located sent by the electrode, but also synchronously obtain the real-time whole brain impedance collected by the electrode, realizing the dual coverage of "local precise monitoring + whole brain monitoring" of brain impedance data; the brain impedance evaluation model module also generates the whole brain standard impedance range based on the patient's physiological characteristic parameters to generate the local area standard impedance range (dividing the whole brain into multiple areas), combines the patient's body mass index and head circumference, which are two core physiological parameters, and generates the whole brain standard impedance range through the trained brain impedance evaluation model, forming the dual-dimension standard benchmark of "local + whole brain"; the control module not only depends on the real-time local impedance and the local area standard impedance range, but also compares the real-time local impedance and the local area standard impedance range (judging the hydrocephalus target area state) and the real-time whole brain impedance and the whole brain standard impedance range (judging the whole brain impedance level), and when both point to the same regulation requirement (for example, the real-time local impedance is lower than the local standard range and the real-time whole brain impedance is lower than the whole brain standard range, both indicating that there is too much cerebrospinal fluid accumulation), the pressure adjustment instruction of the pressure-adjustable valve is generated, ensuring that the regulation decision focuses on the core problem of hydrocephalus and takes into account the whole brain state.

[0065] The above embodiment first greatly improves the accuracy and reliability of system regulation. Through the auxiliary verification of whole brain impedance data, the control module makes a more comprehensive judgment on the intracranial cerebrospinal fluid state, reducing the situation of "only local abnormality but misadjustment of the valve" or "local normality but unawareness of whole brain abnormality"; secondly, the whole brain standard impedance range is generated based on the patient's individual BMI and head circumference, continuing the core advantage of "personalized adaptation" of the system, avoiding the problem of insufficient adaptability of the general whole brain impedance standard to different individuals, and making the dual-dimension monitoring and regulation more suitable for the actual physiological characteristics of the patient; at the same time, the clinical practicability of the system is improved, providing the doctor with dual impedance data reference of "local target area + whole brain", supporting precise shunt regulation and timely checking of potential abnormalities in the whole brain, effectively making up for the defects of the traditional scheme that only focuses on the local drainage state, and further reducing the risk of delayed drainage, excessive drainage or missed judgment of whole brain abnormalities.

[0066] In some embodiments, the control module is further configured to send an alarm information to a preset terminal when the real-time local impedance is within the local area standard impedance range and the real-time whole brain impedance is outside the whole brain standard impedance range.

[0067] And / or, the control module is further configured to send an alarm information to a preset terminal if the real-time local impedance obtained by the electrical impedance data acquisition module is still outside the local area standard impedance range after a preset time after the adjustment of the pressure value of the pressure-adjustable valve is completed.

[0068] Specifically, when the control module finds through data comparison that the real-time local impedance is within the corresponding local region standard impedance range (indicating that the cerebrospinal fluid drainage state of the target region of hydrocephalus is normal), but the real-time whole brain impedance exceeds the whole brain standard impedance range (suggesting that there may be brain tissue lesions, other region fluid accumulation or impedance abnormalities in the non-target region), an alarm logic is triggered immediately, and alarm information is sent to a preset terminal (such as a monitoring APP) through a preset communication link. The alarm content can include the real-time whole brain impedance value, the amplitude of deviation from the standard range, and the current timestamp, so that medical personnel can promptly investigate potential abnormalities at the whole brain level.

[0069] After the control module completes the adjustment of the pressure value of the adjustable pressure valve based on the comparison result of the real-time local impedance and the local region standard impedance range, a preset time counting is started (the preset time can be set based on clinical experience, such as 30 minutes or 1 hour, to ensure sufficient time to observe the adjustment effect); during the counting period, the control module continuously receives real-time local impedance data updated by the electrical impedance data acquisition module and compares it with the local region standard impedance range in real time; if the real-time local impedance still does not return to the local region standard impedance range after the preset time (indicating that the current valve pressure adjustment has not achieved the expected effect, and there may be problems such as shunt blockage, valve dysfunction, or changes in the disease), the control module will trigger an alarm and send alarm information to the preset terminal. The information can include the impedance change curve before and after adjustment, the valve adjustment gear, and the duration of continuous abnormality, providing a basis for medical personnel to intervene.

[0070] In the above embodiments, the design of the two types of alarm mechanisms first effectively addresses the shortcomings of traditional hydrocephalus monitoring schemes that "only focus on the local drainage state and are difficult to detect whole brain abnormalities or ineffective adjustments in a timely manner". The traditional scheme relies on periodic evaluation by doctors, which can easily miss non-target region lesions or delay the intervention opportunity when adjustment is ineffective. However, the system can notify medical personnel in the first time when an abnormality occurs through automated alarm, significantly reducing response time. Second, the alarm mechanism further improves the closed-loop regulation capability of the system. The alarm function as a supplementary response after "adjustment-monitoring" forms a complete link of "adjustment-monitoring-alarm-intervention", ensuring that both potential risks of local normal but whole brain abnormality and explicit problems of ineffective adjustment can be captured in a timely manner. At the same time, the detailed data (such as impedance values, change curves, and abnormal duration) attached to the alarm information provide accurate diagnostic references for medical personnel, avoiding blind investigation, improving intervention efficiency, further reducing the risk of intracranial pressure surge and nerve function damage due to failure to handle abnormalities in a timely manner, and strengthening the safety and reliability of the system in clinical application.

[0071] In some embodiments, the system further includes a storage module;

[0072] A storage module is configured to store real-time local impedance data, adjustable pressure valve data and alarm information during monitoring and send them to a preset terminal.

[0073] Specifically, the system further comprises a storage module, which receives and stores three categories of key data in real time during system operation. The first category is real-time local impedance data corresponding to the local region where the patient's hydrocephalus is located, which is obtained by the electrical impedance data acquisition module (including impedance values and change curves at different time nodes, which correspond to the local regions divided by the brain impedance evaluation model module). The second category is adjustable pressure valve data (including pressure adjustment instructions of the valve by the control module, pressure values before and after adjustment, adjustment time and corresponding gear, and complete valve control history). The third category is alarm information triggered by the control module (including alarm type, alarm occurrence time, abnormal data specific value and deviation range from the standard range). At the same time, the storage module will synchronize the stored historical data and real-time updated data to the preset terminal (such as a monitoring APP) according to a preset period (such as every hour or every day) or on demand, to ensure that medical staff can retrieve data for disease backtracking analysis and diagnosis and treatment reference at any time.

[0074] In the above embodiments, firstly, the problem of "no data retention and difficult to backtracking analysis" in the traditional hydrocephalus monitoring scheme is solved. The traditional scheme relies on doctors to record adjustment information manually, which is easy to miss or error. However, the module can completely retain real-time local impedance, valve control and alarm data, and provide accurate data support for medical staff to review patient condition changes (such as impedance curve long-term trend and valve adjustment effect). Secondly, the data transmission function to the preset terminal realizes convenient sharing and remote access of monitoring data. Medical staff can obtain complete monitoring records of patients without on-site equipment inspection, improving diagnosis and treatment efficiency. At the same time, complete data storage also provides a clinical data basis for subsequent optimization of brain impedance evaluation model and improvement of valve control algorithm, helping system iteration and upgrading, further strengthening the practicality and reliability of the system in hydrocephalus evaluation and shunt control, and reducing the risk of diagnosis and treatment decision deviation caused by data loss.

[0075] In some embodiments, the physiological characteristic parameters include body mass index and head circumference.

[0076] The brain impedance evaluation model module is further configured to input the body mass index and head circumference of the patient into the trained brain impedance evaluation model for processing to generate a local region standard impedance range.

[0077] Specifically, the brain impedance assessment model module inputs two individual physiological parameters, BMI and head circumference, into a pre-trained brain impedance assessment model trained via machine learning. The model's training data comes from a large amount of brain impedance data, BMI, and head circumference parameters from normal individuals and patients diagnosed with hydrocephalus, and it has the ability to match corresponding impedance standards based on individual physiological characteristics. When processing the input BMI and head circumference, the model first divides the whole brain into multiple local regions (e.g., 4, 6, or 8 regions) according to preset rules. Figure 3 As shown in the diagram, the whole brain is divided into 8 regions V1-V8. Then, by combining the impedance distribution patterns of people with similar physiological characteristics in the training data, a standard impedance range suitable for the patient is generated for each local region. This ensures that the generated standard impedance range for the local region is not a universal threshold, but a personalized benchmark that is highly consistent with the individual physiological characteristics of the patient.

[0078] The above embodiments firstly address the problem of insufficient adaptability of universal impedance standards in traditional hydrocephalus monitoring. Traditional methods often use fixed impedance ranges as the basis for judgment, which are difficult to adapt to individual differences in patients with different BMIs and head circumferences. This function generates personalized local area standard impedance ranges by inputting the patient's BMI and head circumference into the training model, making the impedance judgment benchmark more closely match the patient's actual physiological state and significantly improving the accuracy of subsequent impedance comparison and valve adjustment. Secondly, this function provides key support for precise local monitoring of the system. Personalized local area standard impedance ranges can more accurately judge the state of the target area of ​​hydrocephalus (such as whether there is excessive fluid accumulation or excessive drainage), avoiding misjudgments caused by standard deviation. At the same time, this function is built based on machine learning models and clinical data, ensuring the scientific validity and reliability of local area standard impedance ranges. This provides a precise basis for the control module to adjust the pressure value of adjustable valves based on the comparison between real-time local impedance and standard range, further improving the closed-loop logic of "personalized monitoring-precise control" of the system and reducing the risk of untimely or excessive drainage caused by inappropriate standards.

[0079] Figure 4 This is a flowchart illustrating a hydrocephalus shunt monitoring and regulation method according to an embodiment of this application, such as... Figure 4 As shown, the process includes the following steps:

[0080] Step S401: Confirm the patient's hydrocephalus status using computed tomography / magnetic resonance imaging.

[0081] Step S402: Input the patient's physiological parameters into the brain impedance assessment model to obtain the impedance range of the patient's whole brain and local areas.

[0082] Step S403: Real-time monitoring of the patient's whole brain impedance and local impedance at the site of hydrocephalus.

[0083] Step S404, if the impedance of the water accumulation site is too low, the pressure value of the adjustable pressure valve is reduced; if the impedance of the water accumulation site is too high, the pressure value of the adjustable pressure valve is increased.

[0084] Step S405, after adjusting the pressure value of the adjustable pressure valve, if the corresponding impedance curve tends to be normal, the data is recorded normally; if the corresponding impedance curve tends to be abnormal after a period of time, it is prompted that the shunt effect of hydrocephalus is poor and needs to be handled in time.

[0085] Step S406, upload the event and data record to the preset terminal, and perform data analysis for reference by doctors.

[0086] In the process of evaluating hydrocephalus based on bioelectrical impedance tomography technology, long-term monitoring of brain electrical impedance is required, and the impedance changes in the hydrocephalus region are observed and plotted into an impedance change curve. Combined with the curve trend and the personalized normal impedance range of the patient (generated by the brain impedance evaluation model based on physiological characteristic parameters such as body mass index and head circumference), the disease condition can be judged: if the curve remains stable at the beginning and then continuously decreases, it indicates that the disease is worsening and the hydrocephalus is increasing; if the overall curve is stable but the impedance value is lower than the normal range, it indicates that the hydrocephalus is not further increased and shows recovery potential; if the curve continuously rises and the impedance value approaches the normal range from the abnormally low value, it indicates that the brain is recovering and needs to be closely observed for the subsequent trend; if the curve is always stable within the normal range, it indicates that the brain state is stable and normal.

[0087] In addition, in combination with the electrical impedance tomography system for controlling hydrocephalus shunt in the above-mentioned embodiments, the present application can provide a storage medium for implementation. The storage medium has a computer program stored thereon; the computer program is executed by a processor to realize the working of any one of the electrical impedance tomography systems for controlling hydrocephalus shunt in the above-mentioned embodiments.

[0088] It should be noted that the user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or authorized by all parties.

[0089] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the processes of the above-mentioned embodiments of the methods can be included. Any reference to memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (Read-Only Memory, ROM), magnetic tape, floppy disk, flash memory, optical storage, high-density embedded non-volatile memory, resistive memory (ReRAM), magnetoresistive random access memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric memory (Ferroelectric Random Access Memory, FRAM), phase change memory (Phase Change Memory, PCM), graphene memory, etc. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, etc. As an illustration but not limitation, RAM can be in various forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), etc. The database involved in the embodiments provided in the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on a block chain, etc., without being limited thereto. The processor involved in the embodiments provided in the present application can be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., without being limited thereto.

[0090] Those skilled in the art should understand that any combination of the technical features of the above-mentioned embodiments can be made. In order to make the description simple, all possible combinations of the technical features in the above-mentioned embodiments are not described, however, as long as the combination of the technical features does not exist contradictory, it should be considered as the scope of the present application.

[0091] The above-mentioned embodiments only express several implementation manners of the present application, and the description is more specific and detailed, but it should not be understood as a limitation on the scope of the patent. It should be pointed out that for those skilled in the art, without departing from the concept of the present application, some modifications and improvements can be made, which are all within the scope of protection of the present application. Therefore, the scope of protection of the patent of the present application should be subject to the appended claims.

Claims

1. An electrical impedance tomography system for controlling a shunt for hydrocephalus, characterized in that, The system comprises a brain impedance evaluation model module, an electrical impedance data acquisition module, a control module, an adjustable pressure valve and a set of ring-shaped electrodes distributed on the head of a human body. The brain impedance evaluation model module is configured to generate a local region standard impedance range based on physiological characteristic parameters of a patient; the local region is a plurality of regions into which the brain impedance evaluation model module divides the whole brain. The electrical impedance data acquisition module is configured to acquire real-time local impedance sent by the electrodes; the real-time local impedance corresponds to a local region where a hydrocephalus position of the patient is located. The control module is configured to adjust a pressure value of the adjustable pressure valve based on the real-time local impedance and the local region standard impedance range.

2. The electrical impedance tomography system for controlling a hydrocephalus shunt according to claim 1, wherein, The control module is further configured to reduce the pressure value of the adjustable pressure valve in a case where the real-time local impedance is lower than the local region standard impedance range.

3. The electrical impedance tomography system for controlling a hydrocephalus shunt according to claim 2, wherein, The control module is further configured to reduce the pressure value of the adjustable pressure valve according to a preset gear based on a deviation value of the real-time local impedance from a lower limit of the local region standard impedance range.

4. The electrical impedance tomography system for controlling a hydrocephalus shunt of claim 1, wherein, The control module is further configured to increase the pressure value of the adjustable pressure valve in a case where the real-time local impedance is higher than the local region standard impedance range.

5. The electrical impedance tomography system for controlling a hydrocephalus shunt according to claim 4, wherein, The control module is further configured to increase the pressure value of the adjustable pressure valve according to a preset gear based on a deviation value of the real-time local impedance from an upper limit of the local region standard impedance range.

6. The electrical impedance tomography system for controlling a hydrocephalus shunt of claim 1, wherein, The electrical impedance data acquisition module is further configured to acquire real-time whole brain impedance sent by the electrodes. The brain impedance evaluation model module is further configured to generate a whole brain standard impedance range based on a body mass index and a head circumference of the patient. The control module is further configured to adjust the pressure value of the adjustable pressure valve based on the real-time local impedance, the local region standard impedance range, the real-time whole brain impedance and the whole brain standard impedance range.

7. The electrical impedance tomography system for controlling a hydrocephalus shunt according to claim 6, wherein, The control module is further configured to send alarm information to a preset terminal in a case where the real-time local impedance is within the local region standard impedance range and the real-time whole brain impedance is outside the whole brain standard impedance range. The control module is further configured to send alarm information to a preset terminal if the real-time local impedance acquired by the electrical impedance data acquisition module is still outside the local region standard impedance range after a preset time elapses after the adjustment of the pressure value of the adjustable pressure valve is completed.

8. The electrical impedance tomography system for controlling a hydrocephalus shunt according to claim 7, wherein, The system further comprises a storage module. The storage module is configured to store real-time local impedance data, adjustable pressure valve data and alarm information in a monitoring process and send the data to a preset terminal.

9. The electrical impedance tomography system for controlling a hydrocephalus shunt according to any one of claims 1 to 8, characterized in that, The physiological characteristic parameters comprise a body mass index and a head circumference. The brain impedance evaluation model module is further configured to input the body mass index and the head circumference of the patient into a trained brain impedance evaluation model for processing to generate the local region standard impedance range.

10. A storage medium, characterized by The storage medium stores a computer program, wherein the computer program is configured to execute the work of the electrical impedance tomography system for controlling hydrocephalus shunt as claimed in any one of claims 1 to 9 when running.

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