Multi-time temperature compensation method, system and equipment for intracranial pressure sensor

Abstract

The invention discloses a multi-time temperature compensation method, system and equipment for an intracranial pressure sensor, and relates to the technical field of sensors. The method comprises the following steps: controlling a plurality of preset temperature points through an incubator, and determining the plurality of temperature points as a temperature set; in the state of the target temperature point, obtaining a target temperature ADC value according to each temperature ADC value obtained at each preset moment, and obtaining pressure ADC values under a plurality of pressure points corresponding to the target temperature ADC value; performing calculation according to the pressure ADC values under the plurality of pressure points to obtain corresponding zero offset values and pressure sensitivity; obtaining each zero offset value and each pressure sensitivity corresponding to the temperature set; and substituting the temperature set, and each zero offset value and each pressure sensitivity corresponding to the temperature set into a preset fitting model to obtain a final fitting coefficient value, and importing the final fitting coefficient value into a target memory to output a compensation parameter. According to the method and the device, a dynamic scheme that cubic fitting is preferential and quadratic fitting is automatically switched is adopted, so that over-fitting is effectively avoided, and the adaptability of temperature compensation is improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of sensors, and particularly relates to a multiple temperature compensation method, system and device for an intracranial pressure sensor. BACKGROUND

[0002] With the development of intelligence, the corresponding sensors are also more and more accurate, and then have accurate temperature compensation processing. For the performance change of the intracranial pressure sensor under different temperature environments, multiple compensation corrections are performed, so as to eliminate the influence of temperature on the measurement accuracy of the sensor, form a perfect compensation system, provide accurate and reliable data for intracranial pressure monitoring, and help the precise diagnosis and treatment of intracranial pressure related diseases in the medical field.

[0003] The fitting algorithm of the existing intracranial pressure sensor temperature compensation method is single, it is difficult to balance the algorithm simplicity and the adaptability of different pressure sensors, and the overfitting problem is prone to occur; when processing data, the temperature is converted and then calculated, there is a calculation error, and the precision of the temperature intervention operation is reduced, and then the accuracy of the intracranial pressure sensor measurement data is reduced. SUMMARY

[0004] The purpose of the application is to solve the overfitting problem; the temperature is converted and then calculated, there is a calculation error, and the precision of the temperature intervention operation is reduced, and the multiple temperature compensation method, system and device for the intracranial pressure sensor are proposed.

[0005] In the first aspect of the application, a multiple temperature compensation method for an intracranial pressure sensor is first proposed, and the method comprises: A plurality of temperature points are determined as a temperature set by controlling the plurality of temperature points by a temperature box; At a target temperature point, a target temperature ADC value is obtained by averaging each temperature ADC value obtained at each time according to the preset temperature ADC value, and a plurality of pressure ADC values under a plurality of pressure points corresponding to the target temperature ADC value are obtained; the zero offset value and the pressure sensitivity corresponding to the plurality of pressure points are calculated according to the plurality of pressure ADC values; the target temperature point is any one of the temperature set; Each zero offset value and each pressure sensitivity corresponding to the temperature set are obtained; The temperature set, each zero offset value and each pressure sensitivity corresponding to the temperature set are substituted into a preset fitting model to obtain a final fitting coefficient value; The final fitting coefficient value is imported into a target memory to output a compensation parameter.

[0006] Optionally, the calculation of the corresponding zero offset value and the pressure sensitivity according to the plurality of pressure ADC values comprises: When the pressure of the target temperature ADC value and the pressure point is zero, the corresponding pressure ADC value is obtained and recorded as a zero offset value; the maximum pressure ADC value and the minimum pressure ADC value in the pressure ADC values of multiple pressure points are obtained; The calculation formula of the sensitivity is: Wherein, S represents the sensitivity value at the target temperature point, P max_b represents the maximum pressure ADC value at the target temperature point, P min_b represents the minimum pressure ADC value at the target temperature point, P max represents the maximum standard pressure value, P min represents the minimum standard pressure value.

[0007] Optionally, the final fitting coefficient value is obtained by substituting the temperature set, the zero offset value corresponding to each temperature in the temperature set and the pressure sensitivity into the preset fitting model, and the final fitting coefficient value is obtained by substituting the temperature set, the zero offset value corresponding to each temperature in the temperature set and the pressure sensitivity into the preset fitting model. The first fitting coefficient value is obtained by substituting the temperature set, the zero offset value corresponding to each temperature in the temperature set and the pressure sensitivity into a cubic fitting model. The first fitting coefficient value and the preset fitting threshold are judged whether to perform the degraded fitting. If the degraded fitting is needed, the second fitting coefficient value is obtained by substituting the temperature set, the zero offset value corresponding to each temperature in the temperature set and the pressure sensitivity into a quadratic fitting model. The preset fitting model includes a cubic fitting model and a quadratic fitting model.

[0008] Optionally, the first fitting coefficient value and the preset fitting threshold are judged whether to perform the degraded fitting. If the first fitting coefficient value is greater than the preset fitting threshold, the degraded fitting is performed.

[0009] If the first fitting coefficient value is less than or equal to the preset fitting threshold, the degraded fitting is not performed, and the first fitting coefficient value is taken as the final fitting coefficient value.

[0010] In the second aspect of the embodiment of the application, a multiple temperature compensation system of an intracranial pressure sensor is provided, comprising: A data acquisition module: a plurality of temperature points are determined as a temperature set by controlling the plurality of temperature points in a temperature box; A pressure analysis module: in the state of a target temperature point, the target temperature ADC value is obtained by averaging the temperature ADC values obtained at each time according to the preset temperature ADC values, and the pressure ADC values of the target temperature ADC value corresponding to multiple pressure points are obtained; the corresponding zero offset value and pressure sensitivity are obtained by calculating the pressure ADC values of the multiple pressure points; the target temperature point is any one of the temperature set; Fitting coefficient calculation module: obtains each zero bias value and each pressure sensitivity corresponding to the temperature set; substitutes the temperature set, each zero bias value and each pressure sensitivity corresponding to the temperature set into the preset fitting model to obtain the final fitting coefficient value; Compensation Parameter Module: Imports the final fitting coefficient values ​​into the target memory and outputs the compensation parameters.

[0011] Optionally, the pressure analysis module is further used to calculate the corresponding zero bias value and pressure sensitivity based on the pressure ADC values ​​at multiple pressure points: When the target temperature ADC value and the pressure at the pressure point are zero, the corresponding pressure ADC value is obtained and recorded as the zero bias value; the maximum pressure ADC value and the minimum pressure ADC value among the pressure ADC values ​​at multiple pressure points are obtained. The formula for calculating the sensitivity is: Where S represents the sensitivity value at the target temperature point, and P max_b P represents the maximum pressure ADC value at the target temperature point. min_b P represents the minimum pressure ADC value at the target temperature point. max P represents the maximum standard pressure applied. min This indicates the minimum standard pressure value applied.

[0012] Optionally, the fitting coefficient calculation module includes: a first fitting coefficient module, a judgment module, and a second fitting coefficient module. The first fitting coefficient module is used to substitute the temperature set, the zero bias value corresponding to the temperature set, and the pressure sensitivity into the cubic fitting model to obtain the first fitting coefficient value. The judgment module is used to determine whether a downgraded fitting is needed based on the first fitting coefficient value and the preset fitting threshold. The second fitting coefficient module is used to substitute the temperature set, the zero bias values ​​corresponding to the temperature set, and the pressure sensitivity into the quadratic fitting model to obtain the second fitting coefficient value if a downgrade fitting is required. The preset fitting model includes a cubic fitting model and a quadratic fitting model.

[0013] Optionally, determining whether to perform downgrade fitting based on the first fitting coefficient value and the preset fitting threshold includes: If the first fitting coefficient value is greater than the preset fitting threshold, then a downgraded fitting is performed; If the first fitting coefficient value is less than or equal to the preset fitting threshold, then no downgrading fitting is performed, and the first fitting coefficient value is used as the final fitting coefficient value.

[0014] In a third aspect of the invention, an electronic device is provided, characterized in that it comprises: Memory, used to store executable instructions; The processor, when executing executable instructions stored in the memory, implements the steps of the multiple temperature compensation method for any of the intracranial pressure sensors described above.

[0015] The beneficial effects of this invention are: This invention proposes a multiple temperature compensation method for an intracranial pressure sensor. It involves controlling multiple preset temperature points using a temperature chamber, defining these points as a temperature set. At the target temperature point, based on preset temperature ADC values ​​acquired at various time points, the average of these ADC values ​​is calculated to obtain the target temperature ADC value. The pressure ADC values ​​at multiple pressure points corresponding to the target temperature ADC value are then obtained. Based on the pressure ADC values ​​at these pressure points, the corresponding zero bias and pressure sensitivity are calculated. The target temperature point is any temperature point within the temperature set. The zero bias and pressure sensitivity corresponding to the temperature set are acquired. The temperature set, the corresponding zero bias and pressure sensitivity are substituted into a preset fitting model to obtain the final fitting coefficient values. Finally, the final fitting coefficient values ​​are imported into the target memory to output compensation parameters. This invention employs a "priority to tertiary fitting, automatic switching to secondary fitting" approach. This approach leverages the advantages of the tertiary fitting algorithm, which is simple and easy to calculate, while also adapting to different pressure sensors. This effectively avoids overfitting and improves the adaptability of temperature compensation. By directly using temperature and pressure ADC values ​​in the calculation, the invention reduces the calculation error caused by the temperature conversion process, improves accuracy, and ensures the accuracy of intracranial pressure sensor measurement data. Attached Figure Description

[0016] The invention will now be further described with reference to the accompanying drawings.

[0017] Figure 1 A flowchart of a multiple temperature compensation method for an intracranial pressure sensor provided in an embodiment of the present invention; Figure 2 A framework diagram of the multiple temperature compensation method for an intracranial pressure sensor provided in an embodiment of the present invention; Figure 3 This is a structural diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The term "and / or" in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and B can represent: A alone, A and B simultaneously, and B alone. Furthermore, descriptions involving "first," "second," etc., in this invention are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" or "second" can explicitly or implicitly include at least one of those features. Additionally, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention.

[0019] Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] This invention provides a method for multiple temperature compensation of an intracranial pressure sensor. See also... Figure 1 , Figure 1 A flowchart illustrating a method for multiple temperature compensation of an intracranial pressure sensor provided in an embodiment of the present invention. The method includes the following steps: Multiple preset temperature points are controlled by a temperature chamber, and these multiple temperature points are defined as a temperature set. Under the condition of the target temperature point, the target temperature ADC value is obtained by averaging the ADC values ​​of each temperature at preset times. The pressure ADC values ​​at multiple pressure points corresponding to the target temperature ADC value are then obtained. The corresponding zero bias value and pressure sensitivity are calculated based on the pressure ADC values ​​at multiple pressure points. The target temperature point is any temperature point in the temperature set. Obtain the zero bias values ​​and pressure sensitivities corresponding to the temperature set; Substitute the temperature set, the corresponding zero bias value of the temperature set, and the pressure sensitivity into the preset fitting model to obtain the final fitting coefficient value. The final fitting coefficient values ​​are imported into the target memory to output the compensation parameters.

[0021] Based on the multiple temperature compensation method for intracranial pressure sensors provided in this invention, by adopting a scheme of "prioritizing tertiary fitting and automatically switching to secondary fitting", it not only utilizes the advantages of the simplicity and ease of calculation of the tertiary fitting algorithm, but also adapts to different pressure sensors, effectively avoiding overfitting and improving the adaptability of temperature compensation; by directly using temperature ADC values ​​and pressure ADC values ​​in the calculation, it reduces the calculation error caused by the temperature conversion process, improves accuracy, and ensures the accuracy of intracranial pressure sensor measurement data.

[0022] Specifically, the ADC value is what translates continuous analog signals (such as pressure and temperature) into digital signals that computers can understand. In one implementation, the corresponding zero bias and pressure sensitivity are calculated based on the pressure ADC values ​​at multiple pressure points, including: When the ADC value at the target temperature and the pressure at the pressure point are zero, the corresponding pressure ADC value is obtained and recorded as the zero bias value; the maximum and minimum pressure ADC values ​​among the pressure ADC values ​​at multiple pressure points are obtained. The formula for calculating sensitivity is: Where S represents the sensitivity value at the target temperature point, and P max_b P represents the maximum pressure ADC value at the target temperature point. min_b P represents the minimum pressure ADC value at the target temperature point. max P represents the maximum standard pressure applied. min This indicates the minimum standard pressure value applied.

[0023] In one implementation, there are multiple pressure points (e.g., 0 kPa, 10 kPa, 20 kPa, etc.); when the pressure point is 0 kPa, the corresponding pressure ADC value is obtained as a zero bias value. In one implementation, accurately acquiring the zero bias value of the pressure sensor at the target temperature lays the foundation for the accuracy of subsequent pressure measurements. This ensures the accuracy of the reference value when the pressure is zero, avoiding measurement errors caused by zero-point offset. Simultaneously, sensitivity is determined by calculating the ratio of the difference between the maximum and minimum pressure ADC values ​​to the corresponding standard pressure difference. This quantifies the sensor's response to pressure changes at the target temperature, allowing users to clearly understand its pressure sensing accuracy under that temperature environment. This facilitates the selection of appropriate pressure sensors or precise calibration of measurement results in practical applications. Furthermore, this calculation method based on multiple pressure point ADC values ​​comprehensively considers multiple data points within the pressure variation range. Compared to single-data-point calculation methods, it better reflects the sensor's performance across the entire pressure range, effectively improving the stability of zero bias and pressure sensitivity calculations, thereby enhancing the overall accuracy of the pressure measurement system.

[0024] In one implementation, the final fitting coefficient values ​​are obtained by substituting the temperature set, the corresponding zero bias values, and the pressure sensitivities into a preset fitting model, including: Substitute the temperature set, the corresponding zero bias values ​​of the temperature set, and the pressure sensitivity into the cubic fitting model to obtain the first fitting coefficient value. Determine whether a downgraded fitting is needed by comparing the first fitting coefficient value with the preset fitting threshold. If a downgraded fitting is required, the temperature set, the corresponding zero bias values ​​of the temperature set, and the pressure sensitivity are substituted into the quadratic fitting model to obtain the second fitting coefficient values. The preset fitting models include cubic fitting models and quadratic fitting models.

[0025] Specifically, the preset fitting model is obtained through intelligent training based on historical zero bias values ​​and pressure sensitivity. The preset fitting model includes a cubic fitting model and a quadratic fitting model. The cubic fitting model is a preset cubic polynomial fitting method; the quadratic fitting model is a preset quadratic polynomial fitting method. In one implementation, a cubic fitting model is preferentially used for calculation. This approach can more accurately capture the complex nonlinear relationships that may exist between temperature and zero bias, as well as pressure sensitivity. It is particularly suitable for scenarios with a wide temperature range and complex temperature-dependent sensor characteristics, providing higher-precision foundational data for subsequent pressure measurement calibration. Simultaneously, by setting a preset fitting threshold to judge the first fitting coefficient value, it is possible to effectively identify whether the cubic fitting model meets the accuracy requirements of the actual application, avoiding overfitting due to blindly using high-order fitting and ensuring the reliability of the fitting results. When a downgraded fitting is required, a quadratic fitting model is used, achieving flexible adaptation of the fitting model. The quadratic model maintains a certain level of accuracy while having lower computational complexity, balancing accuracy and efficiency when the cubic fitting effect is poor, reducing computational resource consumption and avoiding fitting result distortion. Furthermore, the preset fitting model includes both cubic and quadratic models, forming a multi-level fitting scheme that can handle complex temperature characteristic curves and efficiently complete fitting in simple scenarios, improving the adaptability and versatility of the entire fitting process to different sensor characteristics and application scenarios.

[0026] In one implementation, determining whether a downgraded fitting is needed based on the first fitting coefficient value and a preset fitting threshold includes: If the first fitting coefficient value is greater than the preset fitting threshold, then a downgraded fitting is performed.

[0027] If the first fitting coefficient value is less than or equal to the preset fitting threshold, then no downgrading fitting is performed, and the first fitting coefficient value is used as the final fitting coefficient value.

[0028] Specifically, the preset fitting threshold is set by staff based on historical experience; In one implementation, the first fitting coefficient value is compared with a preset fitting threshold to achieve a dynamic scheme of "prioritizing tertiary fitting and automatically switching to secondary fitting". This improves the ease of calculation and allows for adaptation to different pressure sensors, effectively avoiding overfitting and enhancing the adaptability of temperature compensation.

[0029] Based on the same inventive concept, embodiments of the present invention also provide a multiple temperature compensation system for an intracranial pressure sensor. See also Figure 2 , Figure 2 A schematic diagram of the structure of the multiple temperature compensation system for the intracranial pressure sensor provided in this embodiment of the invention includes: Data acquisition module: Controls multiple preset temperature points through the temperature chamber and defines these multiple temperature points as a temperature set; Pressure Analysis Module: Under the condition of the target temperature point, based on the ADC values ​​of each temperature acquired at preset times, the average value of each temperature ADC value is calculated to obtain the target temperature ADC value, and the pressure ADC values ​​at multiple pressure points corresponding to the target temperature ADC value are obtained; the corresponding zero bias value and pressure sensitivity are calculated based on the pressure ADC values ​​at multiple pressure points; the target temperature point is any temperature point in the temperature set. Fitting coefficient calculation module: Obtains the zero bias values ​​and pressure sensitivities corresponding to the temperature set; Substitutes the temperature set, the zero bias values ​​and pressure sensitivities corresponding to the temperature set into the preset fitting model to obtain the final fitting coefficient values. Compensation Parameter Module: Imports the final fitting coefficient values ​​into the target memory and outputs the compensation parameters.

[0030] Based on the device provided in the embodiments of the present invention, by adopting the scheme of "prioritizing triple fitting and automatically switching to double fitting", it not only takes advantage of the advantages of the simple and convenient calculation of triple fitting algorithm, but also can perform adaptation processing for different pressure sensors, effectively avoiding overfitting and improving the adaptability of temperature compensation; by directly using temperature ADC value and pressure ADC value to intervene in the calculation, the calculation error caused by temperature conversion process is reduced, the accuracy is improved, and the accuracy of intracranial pressure sensor measurement data is guaranteed.

[0031] This invention also provides an electronic device, such as... Figure 3 The diagram shows the structure of an electronic device, including a processor 301, a communication interface 302, a memory 303, and a communication bus 304. The processor 301, communication interface 302, and memory 303 communicate with each other via the communication bus 304. The memory 303 stores computer programs. When the processor 301 executes the program stored in the memory 303, it performs the following steps: Multiple preset temperature points are controlled by a temperature chamber, and these multiple temperature points are defined as a temperature set. Under the condition of the target temperature point, the target temperature ADC value is obtained by averaging the ADC values ​​of each temperature at preset times, and the pressure ADC values ​​at multiple pressure points corresponding to the target temperature ADC value are obtained. The corresponding zero bias value and pressure sensitivity are calculated based on the pressure ADC values ​​at multiple pressure points. The target temperature point is any temperature point in the temperature set. Obtain the zero bias values ​​and pressure sensitivities corresponding to the temperature set; Substitute the temperature set, the corresponding zero bias value of the temperature set, and the pressure sensitivity into the preset fitting model to obtain the final fitting coefficient value. The final fitting coefficient values ​​are imported into the target memory to output the compensation parameters.

[0032] The communication bus mentioned above can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in the diagram, but this does not mean that there is only one bus or one type of bus.

[0033] The communication interface is used for communication between the aforementioned terminal and other devices.

[0034] The memory may include random access memory (RAM) or non-volatile memory, such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0035] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0036] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the claims of this invention should still fall within the patent coverage of this invention.

Claims

1. A method for multiple temperature compensation of an intracranial pressure sensor, characterized in that, The method includes: Multiple preset temperature points are controlled by a temperature chamber, and these multiple temperature points are defined as a temperature set. Under the condition of the target temperature point, the target temperature ADC value is obtained by averaging the ADC values ​​of each temperature at preset times, and the pressure ADC values ​​at multiple pressure points corresponding to the target temperature ADC value are obtained. The corresponding zero bias value and pressure sensitivity are calculated based on the pressure ADC values ​​at multiple pressure points. The target temperature point is any temperature point in the temperature set. Obtain the zero bias values ​​and pressure sensitivities corresponding to the temperature set; Substitute the temperature set, the corresponding zero bias value of the temperature set, and the pressure sensitivity into the preset fitting model to obtain the final fitting coefficient value. The final fitting coefficient values ​​are imported into the target memory to output the compensation parameters.

2. The method for multiple temperature compensation of an intracranial pressure sensor according to claim 1, characterized in that, The calculation of the corresponding zero bias and pressure sensitivity based on the pressure ADC values ​​at multiple pressure points includes: When the target temperature ADC value and the pressure at the pressure point are zero, the corresponding pressure ADC value is obtained and recorded as the zero bias value; the maximum pressure ADC value and the minimum pressure ADC value among the pressure ADC values ​​at multiple pressure points are obtained. The formula for calculating sensitivity is: Where S represents the sensitivity value at the target temperature point, and P max_b P represents the maximum pressure ADC value at the target temperature point. min_b P represents the minimum pressure ADC value at the target temperature point. max P represents the maximum standard pressure applied. min This indicates the minimum standard pressure value applied.

3. The method for multiple temperature compensation of an intracranial pressure sensor according to claim 1, characterized in that, The step of substituting the temperature set, the corresponding zero bias values ​​of the temperature set, and the pressure sensitivity into the preset fitting model to obtain the final fitting coefficient values ​​includes: Substitute the temperature set, the corresponding zero bias values ​​of the temperature set, and the pressure sensitivity into the cubic fitting model to obtain the first fitting coefficient value. Determine whether a downgraded fitting is needed by comparing the first fitting coefficient value with the preset fitting threshold. If a downgraded fitting is required, the temperature set, the corresponding zero bias values ​​of the temperature set, and the pressure sensitivity are substituted into the quadratic fitting model to obtain the second fitting coefficient values. The preset fitting model includes a cubic fitting model and a quadratic fitting model.

4. The method for multiple temperature compensation of an intracranial pressure sensor according to claim 3, characterized in that, Determining whether to perform downgrade fitting based on the first fitting coefficient value and the preset fitting threshold includes: If the first fitting coefficient value is greater than the preset fitting threshold, then a downgraded fitting is performed; If the first fitting coefficient value is less than or equal to the preset fitting threshold, then no downgrading fitting is performed, and the first fitting coefficient value is used as the final fitting coefficient value.

5. A multiple temperature compensation system for an intracranial pressure sensor, characterized in that, The system includes: Data acquisition module: Controls multiple preset temperature points through the temperature chamber and defines these multiple temperature points as a temperature set; Pressure Analysis Module: Under the condition of the target temperature point, based on the ADC values ​​of each temperature obtained at preset times, the average value of each temperature ADC value is calculated to obtain the target temperature ADC value, and the pressure ADC values ​​at multiple pressure points corresponding to the target temperature ADC value are obtained; the corresponding zero bias value and pressure sensitivity are calculated based on the pressure ADC values ​​at multiple pressure points; the target temperature point is any temperature point in the temperature set. Fitting coefficient calculation module: obtains each zero bias value and each pressure sensitivity corresponding to the temperature set; substitutes the temperature set, each zero bias value and each pressure sensitivity corresponding to the temperature set into the preset fitting model to obtain the final fitting coefficient value; Compensation Parameter Module: Imports the final fitting coefficient values ​​into the target memory and outputs the compensation parameters.

6. The multiple temperature compensation system for the intracranial pressure sensor according to claim 5, characterized in that, The pressure analysis module is also used to calculate the corresponding zero bias and pressure sensitivity based on the pressure ADC values ​​at multiple pressure points: When the target temperature ADC value and the pressure at the pressure point are zero, the corresponding pressure ADC value is obtained and recorded as the zero bias value; the maximum pressure ADC value and the minimum pressure ADC value among the pressure ADC values ​​at multiple pressure points are obtained. The formula for calculating sensitivity is: Where S represents the sensitivity value at the target temperature point, and P max_b P represents the maximum pressure ADC value at the target temperature point. min_b P represents the minimum pressure ADC value at the target temperature point. max P represents the maximum standard pressure applied. min This indicates the minimum standard pressure value applied.

7. The multiple temperature compensation system for the intracranial pressure sensor according to claim 5, characterized in that, The fitting coefficient calculation module includes: a first fitting coefficient module, a judgment module, and a second fitting coefficient module. The first fitting coefficient module is used to substitute the temperature set, the zero bias value corresponding to the temperature set, and the pressure sensitivity into the cubic fitting model to obtain the first fitting coefficient value. The judgment module is used to determine whether a downgraded fitting is needed based on the first fitting coefficient value and the preset fitting threshold. The second fitting coefficient module is used to substitute the temperature set, the zero bias values ​​corresponding to the temperature set, and the pressure sensitivity into the quadratic fitting model to obtain the second fitting coefficient value if a downgrade fitting is required. The preset fitting model includes a cubic fitting model and a quadratic fitting model.

8. The multiple temperature compensation system for the intracranial pressure sensor according to claim 7, characterized in that, Determining whether to perform downgrade fitting based on the first fitting coefficient value and the preset fitting threshold includes: If the first fitting coefficient value is greater than the preset fitting threshold, then a downgraded fitting is performed; If the first fitting coefficient value is less than or equal to the preset fitting threshold, then no downgrading fitting is performed, and the first fitting coefficient value is used as the final fitting coefficient value.

9. An electronic device, characterized in that, include: Memory, used to store executable instructions; The processor, when executing executable instructions stored in the memory, implements the multiple temperature compensation method for the intracranial pressure sensor as described in any one of claims 1 to 4.

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