CN119034034A

CN119034034A - Intracranial hematoma suction environment intracranial pressure simulation method and system

Info

Publication number: CN119034034A
Application number: CN202411523270.0A
Authority: CN
Inventors: 陈殿生; 张瀚博; 陈凯; 陈权; 张睿杰; 刘文杰; 崔少飞
Original assignee: Beijing Wantefu Medical Devices Co ltd
Current assignee: Beijing Wantefu Medical Devices Co ltd
Priority date: 2024-10-30
Filing date: 2024-10-30
Publication date: 2024-11-29
Anticipated expiration: 2044-10-30
Also published as: CN119034034B

Abstract

The present invention relates to the field of medical technology, and discloses a method and system for simulating intracranial pressure in an intracranial hematoma suction environment, the method comprising: simulating intracranial pressure changes based on each time point according to intracranial pressure physiological parameters, obtaining corresponding time windows and intracranial pressure change trend signals; adjusting the respiratory frequency and shape based on the respiratory cycle window to simulate intracranial pressure changes, generating respiratory pulse signals; simulating instantaneous intracranial pressure changes caused by heartbeats based on each heartbeat cycle, obtaining intracranial pressure change pulse signals for each heartbeat cycle, integrating intracranial pressure change pulse signals, obtaining intracranial pressure pulse sequences; simulating the extraction/injection process at each time point, generating corresponding intracranial pressure change signals in the extraction/injection process; integrating intracranial pressure change trend signals, respiratory pulse signals, intracranial pressure pulse sequences, and intracranial pressure change signals, obtaining total intracranial pressure signals. The present invention can more accurately simulate and analyze the influence of intracranial hematoma suction process on intracranial pressure.

Description

Intracranial hematoma suction environment intracranial pressure simulation method and system

Technical Field

The invention relates to the technical field of medical treatment, in particular to an intracranial pressure simulation method and system for an intracranial hematoma suction environment.

Background

Intracranial pressure (INTRACRANIAL PRESSURE, ICP) is an important physiological index that reflects the pressure of various structures within the cranium (e.g., brain tissue, cerebrospinal fluid, blood) against the cranium. Variations in intracranial pressure are associated with a variety of disease states, such as intracranial hypertension (ICP exceeding 15 mmHg) which can be caused by head trauma, brain tumors, hemorrhage, oedema, etc., and can lead to serious complications and even life threatening. Therefore, the monitoring of intracranial pressure is of great clinical value in the evaluation of conditions and in the treatment of intracranial pressure reduction.

Cerebrovascular disease is one of the leading causes of death worldwide, especially hemorrhagic stroke, which has higher mortality and disability rates than other types of stroke. Hemorrhagic stroke often involves the formation of hematomas, and the placeholder effect of hematomas and their toxic effects on surrounding brain tissue are key factors leading to further brain damage. Therefore, the method can effectively remove hematoma in time, simultaneously reduce surgical injury as much as possible and prevent re-bleeding, and is a key for treating hemorrhagic cerebral apoplexy.

In the neurosurgical field, the treatment and management of intracranial hematomas is an important topic, and precise control of intracranial pressure is critical to hematoma management. At present, some existing intracranial hematoma removal systems realize real-time monitoring of key information of a patient in the intracranial hematoma treatment process through a plurality of modules, so that treatment operation is more controllable and accurate. For example, the intelligent intracranial hematoma removal and drainage system disclosed in publication number CN109663153a achieves this goal through an information input module, an information detection module, an intelligent module, and a hematoma removal and drainage module. However, obtaining high quality clinical data remains a challenge, and therefore there is a strong need for a simulation method that accurately simulates the aspiration process of intracranial hematomas and its effect on intracranial pressure.

Disclosure of Invention

The embodiment of the invention provides an intracranial hematoma suction environment intracranial pressure simulation method and system, which aim to solve the technical problems in the prior art.

The following presents a simplified summary in order to provide a basic understanding of some aspects of the disclosed embodiments. This summary is not an extensive overview and is intended to neither identify key/critical elements nor delineate the scope of such embodiments. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is presented later.

According to a first aspect of an embodiment of the present invention, there is provided an intracranial pressure simulation method for an intracranial hematoma suction environment.

In one embodiment, the intracranial hematoma aspiration environment intracranial pressure analog simulation method comprises:

Simulating intracranial pressure change based on each time point according to the intracranial pressure physiological parameters to obtain a corresponding time window and intracranial pressure change trend signals;

Taking the time window as a respiration period window, adjusting the respiration frequency and the shape based on the respiration period window to simulate intracranial pressure change, and generating respiration pulse signals with equal length as the intracranial pressure change trend signals;

Based on each heartbeat period, adjusting the heartbeat interval, the pulse amplitude and the shape of intracranial pressure change in the heartbeat period to simulate intracranial pressure instantaneous pressure change caused by the heartbeat, obtaining intracranial pressure change pulse signals of each heartbeat period, and integrating the intracranial pressure change pulse signals of each heartbeat period to obtain an intracranial pressure pulse sequence;

Simulating the liquid pumping/injecting process at each time point according to the predetermined hematoma volume, liquid pumping/injecting speed and intracranial pressure change trend signals, and generating intracranial pressure change signals in the corresponding liquid pumping/injecting process;

and integrating the intracranial pressure change trend signal, the respiratory pulse signal, the intracranial pressure pulse sequence and the intracranial pressure change signal to obtain a total intracranial pressure signal.

In one embodiment, simulating intracranial pressure changes based on each time point according to the intracranial pressure physiological parameter, the deriving the corresponding time window and intracranial pressure change trend signal comprises:

Constructing an intracranial pressure physiological model, and collecting intracranial pressure physiological parameters of a patient, wherein the intracranial pressure physiological parameters comprise cerebral blood volume, vascular resistance, arterial blood pressure, intracranial blood flow coefficients and variables, and cerebrospinal fluid dynamic coefficients and variables;

Generating an intracranial pressure physiological vector based on the intracranial pressure physiological model according to the intracranial pressure physiological parameter of the patient, wherein the intracranial pressure physiological vector comprises a cerebrospinal fluid volume, an intracranial pressure and an arterial exchange area;

And simulating intracranial pressure change based on each time point by using a Sigmoid function according to the intracranial pressure physiological vector to obtain a corresponding time window and intracranial pressure change trend signals.

In one embodiment, the intracranial pressure physiological model is a Ursino-Lodi physiological model.

In one embodiment, adjusting the respiratory rate and shape based on the respiratory cycle window to simulate an intracranial pressure change, generating a respiratory pulse signal equal in length to the intracranial pressure change trend signal includes adjusting the respiratory rate and shape based on the respiratory cycle window, simulating an intracranial pressure change using a respiration _signal function, and generating a respiratory pulse signal equal in length to the intracranial pressure change trend signal.

In one embodiment, adjusting the heart beat interval, the pulse amplitude and the shape based on each heart beat period simulates the intracranial pressure instantaneous pressure change caused by the heart beat, and obtaining the intracranial pressure change pulse signal of each heart beat period comprises adjusting the heart beat interval, the pulse amplitude and the shape based on each heart beat period and obtaining the intracranial pressure change pulse signal of each heart beat period by utilizing the intracranial pressure instantaneous pressure change caused by generateICPpulse function heart beat.

In one embodiment, simulating the fluid pumping/injecting process at each time point according to the predetermined hematoma volume, the fluid pumping/injecting rate and the intracranial pressure variation trend signal, and generating the intracranial pressure variation signal corresponding to the fluid pumping/injecting process comprises simulating the fluid pumping/injecting process at each time point by using simulate _process function according to the predetermined hematoma volume, the fluid pumping/injecting rate and the intracranial pressure variation trend signal, and generating the intracranial pressure variation signal corresponding to the fluid pumping/injecting process.

In one embodiment, the intracranial hematoma suction environment intracranial pressure simulation method further comprises the step of carrying out noise distortion and filtering treatment on the total intracranial pressure signal pair to obtain a final intracranial pressure signal.

According to a second aspect of embodiments of the present invention, there is provided an intracranial pressure simulation system for an intracranial hematoma aspiration environment.

In one embodiment, the intracranial hematoma aspiration environment intracranial pressure analog simulation system comprises:

the intracranial pressure-physiological simulation module is used for simulating intracranial pressure change based on each time point according to the intracranial pressure physiological parameters to obtain a corresponding time window and an intracranial pressure change trend signal;

The intracranial pressure-respiration simulation module is used for taking the time window as a respiration period window, adjusting the respiration frequency and the shape based on the respiration period window to simulate intracranial pressure change, and generating a respiration pulse signal with equal length as the intracranial pressure change trend signal;

The intracranial pressure-heartbeat simulation module is used for simulating intracranial pressure instantaneous pressure change caused by heartbeat by adjusting the heartbeat interval, the pulse amplitude and the shape of intracranial pressure change in the heartbeat period based on each heartbeat period to obtain intracranial pressure change pulse signals of each heartbeat period, and integrating the intracranial pressure change pulse signals of each heartbeat period to obtain an intracranial pressure pulse sequence;

The intracranial pressure-hematoma simulation module is used for simulating the liquid pumping/injecting process at each time point according to the predetermined hematoma volume, the liquid pumping/injecting speed and the intracranial pressure change trend signal and generating an intracranial pressure change signal in the corresponding liquid pumping/injecting process;

And the intracranial pressure signal integration module is used for integrating the intracranial pressure change trend signal, the breathing pulse signal, the intracranial pressure pulse sequence and the intracranial pressure change signal to obtain a total intracranial pressure signal.

In one embodiment, the intracranial pressure-physiology simulation module constructs an intracranial pressure physiology model and collects the intracranial pressure physiology parameters of a patient when simulating intracranial pressure change based on each time point according to the intracranial pressure physiology parameters to obtain a corresponding time window and intracranial pressure change trend signals;

the intracranial pressure physiological parameters comprise cerebral blood volume, vascular resistance, arterial blood pressure, intracranial blood flow coefficient and variable, and cerebrospinal fluid dynamic coefficient and variable, and the intracranial pressure physiological vector comprises cerebrospinal fluid volume, intracranial pressure and arterial exchange area.

In one embodiment, the intracranial pressure-respiration simulation module generates a respiration pulse signal equal to the intracranial pressure variation trend signal by adjusting the respiration frequency and the shape based on the respiration cycle window and simulating the intracranial pressure variation by using respiration _signal function when adjusting the respiration frequency and the shape based on the respiration cycle window and simulating the intracranial pressure variation.

In one embodiment, the intracranial pressure-heartbeat simulation module adjusts the heartbeat interval, the pulse amplitude and the shape of the intracranial pressure change in the heartbeat period based on each heartbeat period to simulate the intracranial pressure instantaneous pressure change caused by the heartbeat, and when obtaining the intracranial pressure change pulse signal of each heartbeat period, adjusts the heartbeat interval, the pulse amplitude and the shape based on each heartbeat period, and obtains the intracranial pressure change pulse signal of each heartbeat period by utilizing the intracranial pressure instantaneous pressure change caused by generateICPpulse function heartbeat.

In one embodiment, the intracranial pressure-hematoma simulation module simulates the pumping/injecting process at each time point according to the predetermined hematoma volume, pumping/injecting rate and intracranial pressure change trend signal, and generates an intracranial pressure change signal in the corresponding pumping/injecting process when simulating the pumping/injecting process at each time point according to the predetermined hematoma volume, pumping/injecting rate and intracranial pressure change trend signal and generates an intracranial pressure change signal in the corresponding pumping/injecting process by using simulate _process function.

In one embodiment, the intracranial hematoma suction environment intracranial pressure simulation system further comprises a signal processing module, a processing module and a processing module, wherein the signal processing module is used for carrying out noise distortion and filtering processing on the total intracranial pressure signal pair to obtain a final intracranial pressure signal.

The technical scheme provided by the embodiment of the invention can have the following beneficial effects:

The invention can generate a long-time intracranial pressure trend signal and an influence change signal of respiration, heartbeat and hematoma suction change on intracranial pressure, thereby comprehensively forming an intracranial pressure signal close to the real situation, enhancing the capability of simulating the intracranial pressure change, accurately simulating and analyzing the influence of the intracranial hematoma suction process on intracranial pressure, providing a reference basis for formulating a personalized hematoma removal treatment scheme so as to support the deep study on intracranial hematoma suction and the influence on intracranial pressure, and testing and optimizing different treatment modes and parameters, and reducing the difficulty and risk of clinical test.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention as claimed.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.

FIG. 1 is a flow diagram illustrating a method of simulated intracranial pressure in an intracranial hematoma aspiration environment, according to an exemplary embodiment;

FIG. 2 is a block diagram illustrating a system for simulating intracranial pressure in an intracranial hematoma aspiration environment, according to an exemplary embodiment;

FIG. 3 is a schematic illustration of intracranial pressure generated by a Ursino-Lodi physiological model simulation, shown in accordance with an exemplary embodiment;

FIG. 4 is a graph showing the effect of heart beat on intracranial pressure when the sampling frequency is set to 125Hz and the analog time period is set to 6000s, according to an exemplary embodiment;

FIG. 5 is a schematic diagram showing the effect of heartbeat on intracranial pressure in a short time period when the sampling frequency is set to 20Hz and the analog time period is set to 1000s, in accordance with an exemplary embodiment;

FIG. 6 is a graph showing the effect of respiration on intracranial pressure when the sampling frequency is set to 125Hz and the analog time period is set to 6000s, according to an exemplary embodiment;

FIG. 7 is a schematic diagram showing the effect of respiration on intracranial pressure for a short period of time when the sampling frequency is set to 20Hz with an analog time period of 1000s, in accordance with an exemplary embodiment;

FIG. 8 is a schematic diagram showing an integrated intracranial pressure signal, according to an exemplary embodiment;

FIG. 9 is a schematic diagram of an electrical circuit for the Ursino-Lodi physiological model, shown according to an example embodiment;

fig. 10 is a schematic structural diagram of a computer device shown according to an exemplary embodiment.

Reference numerals:

arterial blood pressure, representing the pressure at the heart pump; is intracranial compliance, the ability of the cranial cavity to respond to pressure changes; is intracranial pressure; Representing the pressure conversion between the chest and the cranium during the heartbeat; Arterial resistance, which represents vascular resistance from the heart to the cerebral arteries; Is arterial compliance, which means the elasticity of the arterial vessel wall, i.e. its ability to flex in the face of pressure changes; Is proximal venous resistance, representing resistance of venous vessels near the brain; Is distal venous resistance, representing resistance of venous vessels away from the brain; Representing the pressure at the venous side; Representing changes in chest pressure during breathing; representing the pressure transition between the chest and the cranium during breathing; is the filtration resistance, which represents the resistance of blood entering the cerebrospinal fluid space through the capillary vessel; is the reabsorption resistance, which represents the resistance before cerebrospinal fluid is reabsorbed into the venous system; indicating the effect of hematoma aspiration on intracranial pressure.

Detailed Description

The following description and the drawings sufficiently illustrate specific embodiments herein to enable those skilled in the art to practice them. Portions and features of some embodiments may be included in, or substituted for, those of others. The scope of the embodiments herein includes the full scope of the claims, as well as all available equivalents of the claims. The terms "first," "second," and the like herein are used merely to distinguish one element from another element and do not require or imply any actual relationship or order between the elements. Indeed the first element could also be termed a second element and vice versa. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a structure, apparatus, or device that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such structure, apparatus, or device. Without further limitation, an element defined by the phrase "comprising one does not exclude the presence of other like elements in a structure, apparatus or device comprising the element. Various embodiments are described herein in a progressive manner, each embodiment focusing on differences from other embodiments, and identical and similar parts between the various embodiments are sufficient to be seen with each other.

The terms "longitudinal," "transverse," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like herein refer to an orientation or positional relationship based on that shown in the drawings, merely for ease of description herein and to simplify the description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operate in a particular orientation, and thus are not to be construed as limiting the invention. In the description herein, unless otherwise specified and limited, the terms "mounted," "connected," and "coupled" are to be construed broadly, and may be, for example, mechanically or electrically coupled, may be in communication with each other within two elements, may be directly coupled, or may be indirectly coupled through an intermediary, as would be apparent to one of ordinary skill in the art.

Herein, unless otherwise indicated, the term "plurality" means two or more.

Herein, the character "/" indicates that the front and rear objects are an or relationship. For example, A/B represents A or B.

Herein, the term "and/or" is an association relation describing an object, meaning that three relations may exist. For example, A and/or B, represent A or B, or three relationships of A and B.

It should be understood that, although the steps in the flowchart are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the figures may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor does the order in which the sub-steps or stages are performed necessarily performed in sequence, but may be performed alternately or alternately with at least a portion of other steps or other steps.

The various modules in the apparatus or system of the present application may be implemented in whole or in part in software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.

Embodiments of the invention and features of the embodiments may be combined with each other without conflict.

FIG. 1 illustrates one embodiment of an intracranial pressure simulation method of an intracranial hematoma aspiration environment of the present invention.

In this alternative embodiment, the intracranial hematoma aspiration environment intracranial pressure analog simulation method comprises:

step S101, simulating intracranial pressure change based on each time point according to intracranial pressure physiological parameters to obtain a corresponding time window and intracranial pressure change trend signals;

step S103, taking the time window as a respiratory cycle window, adjusting respiratory frequency and shape based on the respiratory cycle window to simulate intracranial pressure change, and generating respiratory pulse signals with equal length as the intracranial pressure change trend signals;

step S105, based on each heartbeat period, adjusting the heartbeat interval, the pulse amplitude and the shape to simulate the intracranial pressure instantaneous pressure change caused by the heartbeat, obtaining intracranial pressure change pulse signals of each heartbeat period, and integrating the intracranial pressure change pulse signals of each heartbeat period to obtain an intracranial pressure pulse sequence;

Step S107, simulating the liquid pumping/injecting process at each time point according to the predetermined hematoma volume, liquid pumping/injecting speed and intracranial pressure change trend signals, and generating intracranial pressure change signals in the corresponding liquid pumping/injecting process;

and step S109, integrating the intracranial pressure change trend signal, the respiratory pulse signal, the intracranial pressure pulse sequence and the intracranial pressure change signal to obtain a total intracranial pressure signal.

FIG. 2 illustrates one embodiment of an intracranial pressure simulation system in an intracranial hematoma aspiration environment, in accordance with the present invention.

In this alternative embodiment, the intracranial hematoma aspiration environment intracranial pressure analog simulation system comprises:

The intracranial pressure-physiology simulation module 201 is used for simulating intracranial pressure change based on each time point according to the intracranial pressure physiology parameters, and obtaining a corresponding time window and intracranial pressure change trend signals;

the intracranial pressure-respiration simulation module 203 is configured to take the time window as a respiration cycle window, adjust a respiration frequency and shape based on the respiration cycle window, simulate intracranial pressure change, and generate a respiration pulse signal equal to the intracranial pressure change trend signal;

the intracranial pressure-heartbeat simulation module 205 is configured to simulate, based on each heartbeat cycle, intracranial pressure instantaneous pressure changes caused by the heartbeat by adjusting a heartbeat interval, a pulse amplitude and a shape, obtain intracranial pressure change pulse signals of each heartbeat cycle, and integrate the intracranial pressure change pulse signals of each heartbeat cycle, so as to obtain an intracranial pressure pulse sequence;

An intracranial pressure-hematoma simulation module 207 for simulating the liquid pumping/injecting process at each time point according to the predetermined hematoma volume, liquid pumping/injecting rate and intracranial pressure variation trend signal, and generating an intracranial pressure variation signal corresponding to the liquid pumping/injecting process;

the intracranial pressure signal integrating module 209 is configured to integrate the intracranial pressure variation trend signal, the respiration pulse signal, the intracranial pressure pulse sequence, and the intracranial pressure variation signal to obtain a total intracranial pressure signal.

In the embodiment, when the intracranial pressure change is simulated according to the intracranial pressure physiological parameters based on each time point to obtain a corresponding time window and an intracranial pressure change trend signal, an intracranial pressure physiological model can be constructed, and the intracranial pressure physiological parameters of a patient are acquired, wherein the intracranial pressure physiological parameters comprise cerebral blood volume, vascular resistance, arterial blood pressure, intracranial blood flow coefficients and variables, cerebrospinal fluid dynamic coefficients and variables, and an intracranial pressure physiological vector is generated according to the intracranial pressure physiological parameters of the patient based on the intracranial pressure physiological model, wherein the intracranial pressure physiological vector comprises cerebrospinal fluid volume, intracranial pressure and arterial exchange area, and then the intracranial pressure change trend signal is obtained by simulating the intracranial pressure change according to the intracranial pressure physiological vector based on each time point by using a Sigmoid function. Specifically, the intracranial pressure physiological model is Ursino-Lodi physiological model.

In the above embodiment, when the respiratory rate and shape are adjusted based on the respiratory cycle window to simulate the intracranial pressure change and generate the respiratory pulse signal equal to the intracranial pressure change trend signal, the respiratory rate and shape are adjusted based on the respiratory cycle window, and the respiratory pulse signal equal to the intracranial pressure change trend signal is generated by simulating the intracranial pressure change using the respiration _signal function.

Specifically, respiration _signal function firstly sets respiratory rate and respiratory cycle counter, initializes time pointer and array for storing respiratory signal, creates a respiratory rate vector with the same length as intracranial pressure trend data, then defines time window of current respiratory cycle, calculates average value of intracranial pressure in the window as amplitude, and then uses sine function to simulate respiratory waveform. Setting the value of the respiratory rate vector to the set respiratory rate in the current time window, updating the time pointer and the respiratory period counter to process the next respiratory period, and finally returning the generated respiratory signal and respiratory rate vector. The respiration _signal function uses the average value of the intra-window intracranial pressure signal as an amplitude to ensure that the simulated respiratory waveform matches the actual intracranial pressure variation. The sine function can well simulate the periodic variation in the breathing process and reflect the influence of the breathing on intracranial pressure.

In the embodiment, the intracranial pressure change caused by the heart beat is simulated by adjusting the heart beat interval and the pulse amplitude and the shape of the intracranial pressure change in the heart beat period based on each heart beat period to obtain the intracranial pressure change pulse signal of each heart beat period, and the intracranial pressure change pulse signal of each heart beat period is obtained by adjusting the heart beat interval, the pulse amplitude and the shape based on each heart beat period and utilizing the intracranial pressure change caused by generateICPpulse function heart beat.

Specifically, generateICPpulse functions are used for initializing a plurality of sets of intracranial pressure change pulse signals for storing heartbeat periods and mark bits of arrhythmia, determining initial heart beat interval values based on given sampling frequency, simulating arrhythmia phenomena caused by respiration by adjusting sine waveforms, further calculating actual heart beat intervals of each heartbeat period, generating pulse signals conforming to physiological characteristics by utilizing gamma distribution, dynamically adjusting pulse amplitudes according to average intracranial pressure in a current time window to ensure simulation accuracy, and performing proper scaling and linear interpolation processing on the generated pulse signals to enable the pulse signals to adapt to different heart beat intervals, so that continuity and physiological rationality of the signals are ensured. By introducing respiratory frequency and arrhythmia factors, the generateICPpulse function can reflect physiological changes under actual conditions more accurately, and by adopting gamma distribution to generate pulse signals, normal heart activities can be simulated well, arrhythmia conditions can be effectively treated, and the application range of the model is improved.

In the above embodiment, when the liquid pumping/injecting process at each time point is simulated according to the predetermined hematoma volume, the liquid pumping/injecting rate and the intracranial pressure variation trend signal, and the intracranial pressure variation signal in the corresponding liquid pumping/injecting process is generated, the liquid pumping/injecting process at each time point is simulated by using simulate _process function according to the predetermined hematoma volume, the liquid pumping/injecting rate and the intracranial pressure variation trend signal, and the intracranial pressure variation signal in the corresponding liquid pumping/injecting process is generated.

Specifically, simulate _treatment function firstly initializes the current intracranial pressure, intracranial volume, elastic coefficient of cranial cavity, base line volume and nonlinearity degree, sets liquid injection rate, liquid pumping rate and solid and liquid hematoma volume, and then decides whether to perform liquid injection or liquid pumping treatment according to intracranial pressure and hematoma volume. When the intracranial pressure is below a certain threshold (e.g., 15 mmHg), the hematoma clearance is considered successful and the treatment is ended. When the intracranial pressure is higher than the threshold value and liquid hematoma exists, liquid suction treatment is carried out. When the liquid hematoma is smaller than a certain threshold (for example, 0.2 milliliter), the liquid injection operation is carried out to liquefy the solid hematoma, and by introducing the nonlinearity degree, the function can more accurately simulate the intracranial pressure-volume relationship and reflect the complexity under the real physiological condition. The intracranial pressure change is calculated and the current intracranial pressure is updated, and finally the intracranial pressure change at each time point in the treatment process is returned.

In addition, in the above embodiment, in order to improve the sense of realism of the analog signal, when performing intracranial pressure analog simulation of the intracranial hematoma suction environment, noise distortion and filtering processing may be performed on the total intracranial pressure signal pair to obtain a final intracranial pressure signal.

In order to facilitate understanding of the above technical solution of the present invention, the following details of the technical solution of the present invention are described in terms of technical principles and calculation, and specifically as follows:

As shown in fig. 3-9, the Ursino-Lodi physiological model is a physiological model of brain blood circulation that combines biophysical, brain metabolic biochemistry and vascular smooth muscle function models, mathematically constructs dynamic balance and feedback mechanisms of brain blood flow, considers blood flow characteristics from aorta to vessel to vein, and their indirect effects on brain blood flow, models the automatic regulation mechanism of brain blood flow on blood pressure changes to maintain constant blood flow, and analyzes intracranial pressure changes while maintaining stability of brain perfusion even when blood pressure fluctuates. Ursino-Lodi physiological models were written using python, first setting up simulation parameters and time steps, and creating a time array from the total time of the simulation and the sampling frequency. Model parameters including vascular resistance, arterial blood pressure, intracranial blood flow and cerebrospinal fluid dynamics related coefficients and variables are then set. A plurality of vectors are created for analog calculations such as cerebrospinal fluid volume, intracranial pressure, cerebral arterial pressure, etc. In a physiological model, it is necessary to calculate the arterial exchange area And the rate of change of intracranial pressure.

Wherein the arterial exchange areaThe calculation is given by equation (1-1):

;

In the formula, Representing the area of the arterial exchange,The value representing the kth time step,Indicating the arterial compliance at the kth time,The arterial pressure at the kth time is indicated,Intracranial pressure at time k is indicated.

Arterial resistanceThe calculation is given by equation (1-2):

;

In the formula, Indicating the resistance of the artery,Representing the coefficient of compliance and,Indicating a normal arterial compliance and,Representing the arterial exchange area.

Cerebral perfusion pressureThe calculation is given by equation (1-3):

;

In the formula, The perfusion pressure of the brain is indicated,The venous resistance is indicated as such,The arterial pressure at the kth time is indicated,The intracranial pressure at the kth time is indicated,Representing arterial resistance.

Blood flow rateThe calculation is given by the formula (1-4):

;

In the formula, The flow rate of blood is indicated and,Arterial pressure at k-th time; brain perfusion pressure at time k; Representing arterial resistance.

Then define a dimensionless variableChanges in arterial compliance, which are nominal flowDepending onIs given by the formula (1-5):

;

In the formula, AndRepresenting the variation of arterial compliance under different conditions, in particular: Representing changes in arterial compliance under low blood flow conditions when blood flow is below a certain threshold The vessel may exhibit greater compliance, i.e., be able to expand more at lower pressures to maintain adequate blood flow supply.It is representative of a change in arterial compliance under normal or high blood flow conditions and the compliance of the vessel is correspondingly reduced when the blood flow is high in order to prevent over-distension and maintain the structural integrity of the vessel.

The sigmoid function was then used to model the nonlinear variation of arterial compliance, given by equations (1-6):

;

In the middle of The output of equations (1-6) is used to calculate the rate of change of arterial compliance; Represents the slope and takes the value as ;Is the gain factor of the gain factor and,Indicating normal arterial compliance; Is arterial resistance defined by equation (1-2), and x is a dimensionless variable defined above.

Rate of change of arterial complianceGiven by the formula (1-7):

;

In the formula, The time constant is represented by a time constant,Indicating arterial compliance at the kth time.

Rate of change in intracranial pressureGiven by the formula (1-8):

;

In the formula, Indicating the rate of cerebrospinal fluid production; Representing the time derivative of the arterial pressure, Represents the resistance to cerebral blood flow,Represents the outflow resistance of the cerebrospinal fluid,The vein Dou Yali is shown as being a representation of a vein,Indicating the volume of the injected cerebrospinal fluid,A rate of change of arterial compliance at a kth time; Is the intracranial pressure at the kth time as defined by equation (1-1); is the arterial pressure at the kth time defined by equation (1-1); Is the brain perfusion pressure at the kth time defined by the definition of equation (1-3).

Solving differential equations using a fourth-order Longer-Curve method to update arterial exchange area and intracranial pressure, then updating cerebrospinal fluid volumeGiven by the formula (1-9):

;

In the formula, Represent the firstThe cerebrospinal fluid volume at a time is determined,Represent the firstThe cerebrospinal fluid volume at a time is determined,Represent the firstIntracranial pressure at each time; Representation of Intracranial pressure compliance at various times; Representing the time step, which is the interval between each time point in the simulation process, the final intracranial pressure physiological model module returns the simulated time vector, the intracranial pressure Arterial exchange areaAnd cerebrospinal fluid volumeAs a result of (a).

For changes in intracranial pressure affected by heart beat, in practice, an array for storing heart pulse signals is initialized, and a flag is set to indicate whether or not arrhythmia is considered. According to the set sampling frequency, a value of an initial heart beat interval is determined. Sinus arrhythmia caused by respiration is simulated by adjusting the heart beat interval signal of a sinusoidal waveform. Subsequently, a cyclic process is entered to generate a heart pulse signal. In each cycle, the current heart beat interval is calculated and the time window for each pulse is determinedGiven by the formula (1-10):

;

where t represents the point in time of the breath sample, In order to be able to breathe at a frequency,For respiratory rate, pulse amplitude is calculated from the exponential pressure-volume relationshipGiven by the formula (1-11):

;

In the formula, Represents the mean intracranial pressure over the current time window and defines the parameters of the gamma distribution to produce pulses of a particular shape, e represents the base of the natural logarithm. In the treatment of premature beat, the heart beat interval and pulse shape are regulated according to the requirement, and the gamma distribution is used to generate corresponding pulse signalGiven by the formula (1-12):

;

In the formula, Represents the abscissa value used to calculate the gamma distribution probability density function,Is the amplitude of the pulse and,A probability density function representing the ith gamma distribution,Is the weight of the i-th pulse,Is the displacement of the ith pulse and the denominator is used to normalize the pulse amplitude.

These signals are inserted into icpBeats arrays by scaling and interpolating the pulse signals to fit the current beat interval, the array being intended to integrate the pulse signals of each beat cycle together to form one complete ICP signal. Scaling is given by the formula (1-13):

;

In the formula, Is a sequence of sampling points defining a pulse signal,Is a sequence ofIs used in the range of (a),Is the length of the x-sequence,Is the interval between the heart beats,Defined as a new sequence, the length of which is consistent with IBI, retaining the original sequenceEnsuring that the shape of the pulse signal remains unchanged after scaling.

Linear interpolation for deriving pulse signals fromResampling to be byThe defined length of the heartbeat interval maps the sampling point of the pulse signal from the original definition domain to the new length, ensures that the shape and the characteristics of the signal are preserved after scaling, and the linear interpolation is given by (1-14):

;

In the formula, The linear interpolation formula is used for estimating an unknown value between two known data points, so that the scaling and interpolation process of the pulse signal is completed; is two known data points and a new sampling point Requiring calculation of the correspondenceA value; Corresponding to ,Then correspond to,For the current index to be the one,Corresponding to,Then correspond toThe Pulse signal Pulse resampling is adapted to the current heart beat interval using a linear interpolation method. Finally, the time pointer and pulse counter are updated and the generated heart pulse signal array icpBeats, i.e., the signal representing the intracranial pressure change, is returned. The specific implementation method of the generateICPpulse functions from the formulas (1-10) to (1-14).

For respiration affecting intracranial pressure changes, the respiration rate is set, the time pointer is initialized, and an array of respiration signals is stored at the time of actual application. A respiratory rate vector of the same length as the intracranial pressure trend data is created and a respiratory cycle counter is initialized. Defining a time window for the current respiratory cycle, given by (1-15):

;

In the formula, The time pointer is indicated as such,Representing the sampling frequency of the sample,Which is indicative of the frequency of the breathing,Indicating how many sampling points there are in a complete breathing cycle, the round function is used to applyIs rounded to the nearest integer to ensure that the number of samples per breath cycle is an integer for use in generating the breath signal. Then calculate the time window of the current respiratory cycle and the amplitude of the signal within the windowGiven by the formula (1-16):

;

In the formula, Representing the average value of the ICP signal within a window, and then modeling the respiratory waveform using a sine functionThe method is given by (1-17):

;

where t represents the point in time of the breath sample, Which is indicative of the frequency of the breathing,Is the pulse amplitude.

The respiratory rate vector is then updated to have a value within the current window that is the set respiratory rate. The time pointer and the respiratory cycle counter are updated and the generated respiratory signal and respiratory frequency vector are returned. The specific implementation method from the formulas (1-15) to (1-17) is respiration _signal function.

For the effect of hematoma aspiration on intracranial pressure, based on intracranial pressure trend, infusion rate, withdrawal rate, and volumes of solid and liquid hematomas, it is then determined whether infusion or withdrawal is to be performed at each time point, in the present invention, when intracranial pressure is belowThe treatment is concluded when hematoma clearance is considered successful, so when intracranial pressure is higherAnd (3) carrying out liquid pumping treatment when the liquid hematoma exists, otherwise, carrying out liquid injection operation to liquefy the solid hematoma when the liquid hematoma is smaller than a threshold value, wherein the threshold value can be set to be 0.2 milliliter. Thus, the corresponding intracranial pressure change was calculated, given by the formula (1-18):

;

In the formula, The time point of the hematoma aspiration operation is indicated,Indicating the current intracranial pressure,Represents the intracranial volume,Indicating the liquid injection rate [ ]) And pumping rate [ ]) Is used for the difference in (a),Representing the elastic coefficient of the cranial cavity,The baseline volume is indicated as being the volume of the baseline,Indicating the degree of nonlinearity of the intracranial pressure-volume relationship.Indicating that the intracranial pressure increases faster than a linear relationship with volume, indicating that the intracranial pressure increases in sensitivity to volume changes, any additional volume increase resulting in a substantial increase in pressure; Indicating that the intracranial pressure-volume relationship is linear, meaning that the increase in pressure is proportional to the increase in volume, rarely occurring under real physiological conditions; Indicating that the rate of increase of intracranial pressure with volume is slower than a linear relationship, corresponding to a greater compliance of the cranial cavity or, under certain conditions, a weaker response of intracranial pressure to volume changes. The expression (1-18) is a specific implementation method of simulate _treatment function.

In order to enhance the sense of realism of the analogue signal, noise may be added to a given intracranial pressure signal and signal distortion processing may be performed. Specifically, a method of low-pass filtering is first used for removing high-frequency noise and unnecessary high-frequency components in a signal while retaining low-frequency information in the signal. Selecting signal subsegments, designing a 3-order Butterworth low pass filter using the signal function in python's scipy library (an advanced scientific computing library), and setting the cut-off frequency toThe sampling frequency is adopted, the signal components higher than the frequency are attenuated obviously, the signal components lower than the frequency can pass through the filter more completely, the high-frequency components of specific subsections in the original signal are removed effectively, and the low-frequency components are reserved, so that the low-pass filtering of the signal is realized. The hard saturated analog loss of signal is then used to locate the onset of loss of signal, then the duration of loss of signal is determined, and setting the signal value to 0 simulates a complete loss of signal. Finally, progressive saturation is used for simulating the situation that the dynamic range of the signal is limited or nonlinear distortion is faced, the starting point of signal gradual change is positioned, the duration of the signal gradual change is determined, and the application of the hyperbolic tangent function can be smoothly transited from an initial signal value to a saturated value. The gradual change processing is helpful for testing and optimizing signal processing, and can effectively evaluate the robustness and the recovery capability of the algorithm.

The invention is used for simulating the change of intracranial pressure and generating a comprehensive intracranial pressure signal by combining a plurality of physiological signals. Mainly comprises long-time trend of physiological model, respiratory signal, hematoma aspiration signal of heartbeat signal and noise treatment. Initializing parameters, setting sampling frequency and creating a time vector, simulating intracranial pressure trend by using an intracranial pressure physiological model module, simulating a respiratory signal by using a respiratory module, simulating a single heart beat signal by using a heart beat module, and simulating a hematoma signal by using a hematoma suction module. Then synthesizing the comprehensive intracranial pressure signal, adding noise treatment to the intracranial pressure signal and then returning the adjusted intracranial pressure signal. By integrating the modules, the invention can provide a comprehensive intracranial pressure signal for simulating the change trend of the intracranial pressure, respiratory and heartbeat signals and the influence of hematoma treatment, and provides a simulation basis for the formulation of intracranial hematoma removal treatment scheme and effect evaluation.

Fig. 10 illustrates one embodiment of a computer device, which may be a server, comprising a processor, memory, and network interface connected by a system bus, of the present invention. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used to store static information and dynamic information data. The network interface of the computer device is used for communicating with an external terminal through a network connection. Which computer program, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.

It will be appreciated by those skilled in the art that the structure shown in FIG. 10 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.

The invention further provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to realize the steps in the embodiment of the method.

In addition, the invention also provides a computer readable storage medium, on which a computer program is stored, which computer program, when being executed by a processor, implements the steps of the above-mentioned method embodiments.

Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, or the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory. By way of illustration, and 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 present invention is not limited to the structure that has been described above and shown in the drawings, and various modifications and changes can be made without departing from the scope thereof. The scope of the invention is limited only by the appended claims.

Claims

1. An intracranial hematoma suction environment intracranial pressure simulation method is characterized by comprising the following steps of:

2. The intracranial hematoma aspiration environment intracranial pressure simulation method as recited in claim 1, wherein the method comprises the steps of:

simulating intracranial pressure changes based on each time point according to the intracranial pressure physiological parameters, and obtaining corresponding time windows and intracranial pressure change trend signals comprises:

3. The intracranial hematoma aspiration environment intracranial pressure simulation method as recited in claim 2, wherein the method comprises the steps of:

The intracranial pressure physiological model is Ursino-Lodi physiological model.

4. The intracranial hematoma aspiration environment intracranial pressure simulation method as recited in claim 1, wherein the method comprises the steps of:

Adjusting a respiratory rate and shape based on the respiratory cycle window to simulate intracranial pressure changes, generating a respiratory pulse signal equal in length to the intracranial pressure change trend signal comprising: adjusting the respiratory frequency and shape based on the respiratory cycle window, and simulating intracranial pressure change by using respiration _signal function to generate respiratory pulse signals with equal length as the intracranial pressure change trend signals;

Based on each heartbeat period, adjusting the heartbeat interval, the pulse amplitude and the shape to simulate intracranial pressure instantaneous pressure change caused by the heartbeat, and obtaining an intracranial pressure change pulse signal of each heartbeat period comprises the steps of based on each heartbeat period, adjusting the heartbeat interval, the pulse amplitude and the shape, and obtaining the intracranial pressure change pulse signal of each heartbeat period by utilizing the intracranial pressure instantaneous pressure change caused by generateICPpulse function heartbeat;

Simulating the liquid pumping/injecting process at each time point according to the predetermined hematoma volume, the liquid pumping/injecting speed and the intracranial pressure change trend signals, and generating intracranial pressure change signals corresponding to the liquid pumping/injecting process comprises simulating the liquid pumping/injecting process at each time point by using simulate _process functions according to the predetermined hematoma volume, the liquid pumping/injecting speed and the intracranial pressure change trend signals, and generating intracranial pressure change signals corresponding to the liquid pumping/injecting process.

5. The method for simulating intracranial pressure in an intracranial hematoma aspiration environment according to claim 1, further comprising:

and carrying out noise distortion and filtering treatment on the total intracranial pressure signal pair to obtain a final intracranial pressure signal.

6. An intracranial pressure analog simulation system for an intracranial hematoma aspiration environment, comprising:

7. The intracranial hematoma aspiration environment intracranial pressure analog simulation system as recited in claim 6, wherein:

the intracranial pressure-physiology simulation module constructs an intracranial pressure physiology model and collects intracranial pressure physiology parameters of a patient when simulating intracranial pressure change based on each time point according to the intracranial pressure physiology parameters and obtaining a corresponding time window and intracranial pressure change trend signals; according to the intracranial pressure physiological vector, simulating intracranial pressure change by using a Sigmoid function based on each time point to obtain a corresponding time window and an intracranial pressure change trend signal;

8. An intracranial hematoma aspiration environmental intracranial pressure simulation system as recited in claim 7, wherein:

9. The intracranial hematoma aspiration environment intracranial pressure analog simulation system as recited in claim 6, wherein:

The intracranial pressure-respiration simulation module is used for adjusting the respiration frequency and the shape based on the respiration period window to simulate intracranial pressure change and generating respiration pulse signals with the same length as the intracranial pressure change trend signal, and adjusting the respiration frequency and the shape based on the respiration period window to simulate intracranial pressure change by utilizing respiration _signal function and generate respiration pulse signals with the same length as the intracranial pressure change trend signal;

The intracranial pressure-heartbeat simulation module is used for simulating intracranial pressure instantaneous pressure change caused by heartbeat by adjusting the heartbeat interval, the pulse amplitude and the shape based on each heartbeat period to obtain an intracranial pressure change pulse signal of each heartbeat period, and obtaining the intracranial pressure change pulse signal of each heartbeat period by adjusting the heartbeat interval, the pulse amplitude and the shape based on each heartbeat period and utilizing the intracranial pressure instantaneous pressure change caused by generateICPpulse function heartbeat;

the intracranial pressure-hematoma simulation module simulates the liquid pumping/injecting process at each time point according to the predetermined hematoma volume, liquid pumping/injecting speed and intracranial pressure change trend signals, and generates intracranial pressure change signals in the liquid pumping/injecting process according to the predetermined hematoma volume, liquid pumping/injecting speed and intracranial pressure change trend signals when simulating the liquid pumping/injecting process at each time point according to the predetermined hematoma volume, liquid pumping/injecting speed and intracranial pressure change trend signals, and generates intracranial pressure change signals in the liquid pumping/injecting process.

10. The intracranial hematoma aspiration environmental intracranial pressure analog simulation system as recited in claim 6, further comprising:

And the signal processing module is used for carrying out noise distortion and filtering processing on the total intracranial pressure signal pair to obtain a final intracranial pressure signal.