A method and system for adjusting neurological drug delivery parameters

Abstract

This application discloses a method and system for adjusting neurological drug delivery parameters. By collecting real-time ambient temperature information and actual instantaneous motor speed data around the infusion pump and comparing them with the expected response of the motor under ideal linear operating conditions, it can accurately identify and quantify the nonlinear behavior characteristics of the motor caused by temperature. A two-dimensional mapping relationship is established based on the ambient temperature information and nonlinear behavior characteristics. Before issuing the target control command, the current ambient temperature is acquired in real time, and the corresponding compensation parameters are calculated according to the mapping relationship. Finally, the target control command is adjusted and compensated based on these compensation parameters. This effectively solves the problems of decreased drug delivery accuracy and flow fluctuation caused by differences in the physical properties of novel drug solutions, long-term performance degradation of motors, and nonlinear response characteristics in the prior art.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of neurology drug delivery, in particular, relates to a neurology drug delivery parameter adjustment method and system. BACKGROUND

[0002] In the treatment of neurological diseases, accurate drug delivery is crucial for the treatment effect of patients. At present, advanced adaptive control drug delivery systems accurately control the drug flow of infusion pumps through micro drive motors, and set feedback adjustment parameters according to standard drug data to maintain the preset physiological indicators. However, when using new neurology drug solutions, their physical properties may differ from standard drugs, such as higher viscosity, which will bring challenges to the long-term stable operation of the system. In particular, this additional load may cause the performance of the drive motor to gradually degrade, and even exhibit nonlinear response characteristics, thereby affecting the accuracy of drug delivery.

[0003] Specifically, due to the physical viscosity of the new drug solution exceeding the design reference value initially set by the system, the micro drive motor inside the infusion pump will bear slightly larger load than expected during long-term continuous operation. This persistent additional resistance will gradually cause the lubricating grease inside the motor bearing to thin out or degrade in performance. Over time, this change in lubrication state causes the motor's rotational speed stability to start to decline slightly but continuously after long periods of operation. This decline is not a sudden failure, but a gradual performance degradation, which manifests as a small, difficult-to-accurately capture through a single instantaneous measurement, deviation between the actual delivery flow and the control command. The cumulative effect of this deviation affects the accuracy of drug delivery.

[0004] In order to monitor the actual situation of drug delivery, the system is equipped with a micro flow meter to continuously collect delivery flow data. However, the design precision and data sampling frequency of this micro flow meter make it difficult to provide clear and stable feedback signals in a short time when faced with such subtle and continuous flow fluctuations caused by motor wear. This difficulty in information processing causes the system to have a certain lag in evaluating the actual delivery amount, and cannot accurately reflect the subtle flow changes caused by motor performance degradation in a timely manner.

[0005] As the micro drive motor operates under the continued extra load, its internal mechanical wear gradually intensifies from the initial slight state and transforms from a uniform performance degradation to a nonlinear mechanical response characteristic. Specifically, when the control system issues a tiny speed change instruction for fine adjustment, the increased internal static friction force will cause the motor to exhibit a temporary "stickiness" phenomenon, i.e., the motor cannot immediately respond to the instruction as if it is stuck. Once the static friction force is overcome, the motor will suddenly "jump" to a new speed instead of smoothly transitioning. This "stickiness-jump" action causes the originally expected smooth and continuous drug flow output to become an irregular flow consisting of a series of tiny and abrupt flow steps. This nonlinear physical behavior deviates fundamentally from the linear motor response model on which the system was designed.

[0006] In this case, the adaptive control system attempts to correct these deviations by more frequently fine-tuning the motor speed. However, the control model of the system is based on the assumption that the motor can respond linearly and smoothly to instructions, and it has no way of anticipating the "stickiness-jump" physical characteristics that have already emerged in the motor. Therefore, each fine correction instruction issued by the system may trigger an unpredictable flow mutation, leading to failed adjustment or even exacerbating fluctuations. Ultimately, this continuous and nonlinear flow fluctuation results in poor drug treatment effectiveness, ineffective control of the patient's condition, and the system's inability to autonomously identify and report this specific physical failure mode of the core execution component. SUMMARY

[0007] The present application provides a neurological drug delivery parameter adjustment method and system, aiming to solve the problem that the existing neurological drug delivery system, when facing new types of drug solutions, has reduced drug delivery accuracy and flow fluctuations due to motor performance degradation and nonlinear response characteristics, and the system is difficult to autonomously identify and correct these problems.

[0008] In one aspect, the present application provides a neurological drug delivery parameter adjustment method, comprising:

[0009] Collecting environmental temperature information around the infusion pump and actual instantaneous speed data of the motor after receiving a control instruction;

[0010] Comparing the actual instantaneous speed data with the expected response of the motor in the ideal linear working state to obtain the nonlinear behavior characteristics of the motor, the nonlinear behavior characteristics including stickiness delay time and jump peak deviation, reflecting the phenomenon that the dynamic response of the motor deviates from the ideal linear characteristic due to temperature influence;

[0011] Establishing a two-dimensional mapping relationship according to the environmental temperature information and the nonlinear behavior characteristics;

[0012] Before sending a target control instruction to the motor, the current ambient temperature is obtained, and a nonlinear behavior characteristic corresponding to the current ambient temperature is obtained according to the two-dimensional mapping relationship; and a compensation parameter corresponding to the current ambient temperature is calculated in real time according to the corresponding nonlinear behavior characteristic, the compensation parameter including a viscous compensation coefficient and a jump suppression factor of the motor;

[0013] According to the compensation parameter, the target control instruction is compensated and adjusted to improve the motor control precision and reduce the fluctuation of the drug delivery flow.

[0014] Optionally, ambient temperature information around the infusion pump and an original pulse signal of the motor after receiving the control instruction are collected;

[0015] The original pulse signal is compared with an expected pulse mode of the motor under a standard temperature and an ideal linear working state to identify an abnormal mode;

[0016] When the abnormal mode is identified, whether a sensor artifact exists is determined according to a preset temperature artifact association rule table, the temperature artifact association rule table recording typical artifact modes of an optical encoder under different temperature change rates;

[0017] If the sensor artifact exists, the original pulse signal is modified to obtain a target pulse signal;

[0018] Actual instantaneous speed data of the motor is calculated according to the target pulse signal.

[0019] Optionally, if the original pulse signal satisfies at least one of a pulse width deviating from a normal range, a pulse amplitude deviating from a normal range, a pulse loss, and an extra pulse appearing that does not match an expected speed, it is identified that the abnormal mode exists.

[0020] Optionally, the step of modifying the original pulse signal to obtain the target pulse signal if the sensor artifact exists includes:

[0021] If a pulse loss artifact exists, a linear interpolation method is used for compensation; if an abnormal narrow pulse or an abnormal wide pulse artifact exists, the abnormal narrow pulse or the abnormal wide pulse is regarded as an invalid pulse and filtered out; and if an extra pulse artifact exists, the extra pulse is regarded as noise and filtered out, and finally the target pulse signal is obtained.

[0022] Optionally, the step of calculating the actual instantaneous speed data of the motor according to the target pulse signal includes:

[0023] The target pulse signal is converted into revolutions per minute in real time through speed calculation to obtain the actual instantaneous speed data.

[0024] Optionally, the step of establishing a two-dimensional mapping relationship according to the ambient temperature information and the nonlinear behavior characteristics comprises:

[0025] The correlation between the ambient temperature information and the nonlinear behavior characteristics is established by a two-dimensional lookup table, the horizontal axis of the two-dimensional lookup table is a temperature interval divided by a preset step size, and the vertical axis is a viscous compensation strength reference value and a jump suppression strength reference value in the corresponding temperature interval.

[0026] Optionally, the step of compensating and adjusting the target control instruction according to the compensation parameter to improve the motor control precision and reduce the fluctuation of the drug delivery flow comprises:

[0027] According to the compensation parameter, an enhanced voltage positively correlated with the viscous compensation coefficient is applied to overcome the viscosity in the initial stage of the target control instruction, and a voltage change curve with a decreasing slope determined by the jump suppression factor is used for smooth transition to suppress the jump.

[0028] Optionally, the viscous delay time is quantified by detecting the difference between the actual time required for the motor to reach 90% of the target speed and the expected response time, and the jump peak deviation is quantified by detecting the maximum deviation value of the motor speed exceeding 105% of the target speed.

[0029] Optionally, the step of collecting the ambient temperature information around the infusion pump and the original pulse signal of the motor after receiving the control instruction comprises:

[0030] An NTC thermistor temperature sensor is used to collect the ambient temperature information at a frequency of not less than 10 times per second, and an optical encoder is used to collect the original pulse signal at a frequency of not less than 0.5 milliseconds.

[0031] In another aspect, the present application provides a neurology drug delivery parameter adjustment system, which comprises:

[0032] A data collection module is configured to collect the ambient temperature information around the infusion pump and the actual instantaneous speed data of the motor after receiving the control instruction;

[0033] A characteristic identification module is configured to compare the actual instantaneous speed data with the expected response of the motor in an ideal linear working state to obtain the nonlinear behavior characteristics of the motor, the nonlinear behavior characteristics including a viscous delay time and a jump peak deviation, which reflect the phenomenon that the dynamic response of the motor deviates from the ideal linear characteristic due to the temperature influence;

[0034] A mapping establishment module is configured to establish a two-dimensional mapping relationship according to the ambient temperature information and the nonlinear behavior characteristics;

[0035] The compensation parameter calculation module is configured to acquire a current environment temperature before issuing a target control instruction to the motor, and acquire a nonlinear behavior characteristic corresponding to the current environment temperature according to the two-dimensional mapping relationship; and calculate a compensation parameter corresponding to the current environment temperature in real time according to the corresponding nonlinear behavior characteristic, wherein the compensation parameter includes a viscous compensation coefficient and a jump suppression factor of the motor.

[0036] The instruction compensation module is configured to compensate and adjust the target control instruction according to the compensation parameter, so as to improve the motor control precision and reduce the fluctuation of the drug delivery flow.

[0037] The application discloses a neurology drug delivery parameter adjustment method and system. By collecting the environment temperature information around the infusion pump and the actual instantaneous speed data of the motor in real time, and comparing the data with the expected response of the motor in the ideal linear working state, the nonlinear behavior characteristics of the motor caused by the temperature, such as the viscous delay time and the jump peak deviation, can be accurately identified and quantified. On this basis, a two-dimensional mapping relationship is established according to the environment temperature information and the nonlinear behavior characteristics, and the current environment temperature is acquired in real time before issuing the target control instruction. According to the mapping relationship, the corresponding compensation parameter, including the viscous compensation coefficient and the jump suppression factor, is calculated. Finally, the target control instruction is compensated and adjusted according to the compensation parameter.

[0038] Through the above technical solution, the application effectively solves the problems of the decline of the drug delivery precision and the fluctuation of the flow caused by the differences in the physical characteristics of new drug solutions, the long-term performance attenuation of the motor, and the nonlinear response characteristics (such as the "viscous-jump" phenomenon) in the prior art. Specifically, by accurately identifying and quantifying the nonlinear behavior of the motor, the application can compensate specifically, for example, by applying an enhanced voltage to overcome the viscosity in the initial stage of the instruction, and by using a voltage change curve with a reduced slope to smooth the transition and suppress the jump. This fine compensation adjustment enables the motor to respond to the control instruction more accurately and smoothly, thereby significantly improving the precision of drug delivery, reducing the fluctuation of the drug delivery flow, overcoming the limitation that the prior art cannot effectively cope with the nonlinear failure mode of the motor, and finally ensuring the effectiveness and safety of the neurology drug treatment. BRIEF DESCRIPTION OF DRAWINGS

[0039] In order to more clearly illustrate the application, the drawings required in the embodiments will be briefly introduced. Obviously, other drawings can also be obtained by those skilled in the art without any creative labor.

[0040] Figure 1 Fig. 1 exemplarily shows a flowchart of a neurology drug delivery parameter adjustment method in the embodiments;

[0041] Figure 2 Fig. 1 shows a schematic diagram of a neurology medicine delivery parameter adjustment system according to an embodiment.

[0042] Fig. 1 shows a schematic diagram of a neurology medicine delivery parameter adjustment system according to an embodiment. Fig. 1 shows a schematic diagram of a neurology medicine delivery parameter adjustment system according to an embodiment. DETAILED DESCRIPTION

[0043] The technical solutions in the present application will be described clearly and completely below in combination with the drawings in the present application. Obviously, the described embodiments are only some of the embodiments of the present application, rather than all the embodiments. The components of the present application described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0044] It should be noted that similar reference numerals and letters represent similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. Meanwhile, in the description of the present application, the terms "first", "second", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0045] The conventional existing neurology medicine delivery system faces new medicine solutions, due to the differences in physical properties from standard medicines, resulting in performance degradation of the driving motor, non-linear response characteristics, and further affecting the accuracy of medicine delivery. This non-linear behavior, such as stickiness and jumping, makes the medicine delivery flow difficult to predict, seriously affecting the treatment effect, and the existing system is difficult to identify and effectively compensate.

[0046] As shown in Fig. 1, a schematic diagram of a neurology medicine delivery parameter adjustment method according to an embodiment is exemplarily shown. Figure 1 The present application proposes a neurology medicine delivery parameter adjustment method, which comprises:

[0047] S10, collecting the ambient temperature information around the infusion pump and the actual instantaneous speed data of the motor after receiving the control instruction;

[0048] The infusion pump refers to a medical device for precisely controlling the flow rate of drug delivery, and the core driving component thereof is usually a micro motor. The motor refers to an actuator for driving the infusion pump to deliver drugs, and the rotational speed thereof directly affects the flow rate of drug delivery. The environmental temperature information refers to the temperature data of the working environment of the infusion pump, which has a significant impact on the performance of the motor, especially its nonlinear behavior. The actual instantaneous rotational speed data refers to the actual instantaneous rotational speed of the rotor of the motor after receiving the control instruction, which reflects the real-time dynamic response of the motor.

[0049] S20, comparing the actual instantaneous rotational speed data with the expected response of the motor in the ideal linear working state to obtain the nonlinear behavior characteristics of the motor, the nonlinear behavior characteristics including the viscous delay time and the jump peak deviation, for reflecting the phenomenon that the dynamic response of the motor deviates from the ideal linear characteristic due to the temperature influence;

[0050] The expected response in the ideal linear working state refers to the ideal rotational speed change curve of the motor according to the control instruction under standard environmental conditions and without external interference.

[0051] The nonlinear behavior characteristics refer to the deviation between the actual response and the ideal linear response of the motor, specifically including the viscous delay time and the jump peak deviation. The viscous delay time refers to the difference between the time required for the motor to reach a certain proportion (e.g. 90%) of the target rotational speed after receiving the instruction and the ideal response time, reflecting the additional time required for the motor to overcome internal friction when starting or accelerating. The jump peak deviation refers to the possible instantaneous overshoot or fluctuation of the rotational speed of the motor after reaching the target rotational speed, and the maximum deviation value reflects the smoothness of the response of the motor.

[0052] S30, establishing a two-dimensional mapping relationship according to the environmental temperature information and the nonlinear behavior characteristics;

[0053] The two-dimensional mapping relationship refers to the correlation model established between the environmental temperature information and the nonlinear behavior characteristics of the motor, which can be a function relationship or a neural network model, for predicting the nonlinear behavior of the motor at a specific temperature.

[0054] S40, before issuing a target control instruction to the motor, obtaining the current environmental temperature, and according to the two-dimensional mapping relationship, obtaining the nonlinear behavior characteristics corresponding to the current environmental temperature; and according to the corresponding nonlinear behavior characteristics, calculating the compensation parameters corresponding to the current environmental temperature in real time, the compensation parameters including the viscous compensation coefficient and the jump suppression factor of the motor;

[0055] The compensation parameters refer to the parameters calculated according to the nonlinear behavior characteristics for adjusting the control instruction of the motor, including the viscous compensation coefficient and the jump suppression factor.

[0056] The viscous compensation coefficient is used to provide additional driving force to overcome the viscous effect when the motor starts or accelerates.

[0057] The jump suppression factor is used to smooth the motor speed change and suppress the speed overshoot or fluctuation.

[0058] S50, according to the compensation parameter, the target control instruction is compensated and adjusted to improve the motor control precision and reduce the fluctuation of drug delivery flow.

[0059] The target control instruction refers to the original control signal sent to the motor according to the preset drug delivery technical scheme. The target control instruction is compensated and adjusted according to the compensation parameter, so that it is more suitable for the actual dynamic characteristics of the motor, thereby improving the control precision.

[0060] The neurology drug delivery parameter adjustment method proposed in the present application is to improve the motor control precision and reduce the fluctuation of drug delivery flow through a dynamic compensation mechanism.

[0061] Firstly, the ambient temperature information around the infusion pump and the actual instantaneous speed data of the motor after receiving the control instruction need to be collected. The ambient temperature information can be collected by a temperature sensor placed near the infusion pump, for example, a thermistor sensor can be used for continuous sampling at a frequency of one second. The actual instantaneous speed data can be obtained by an encoder installed on the motor, for example, an optical encoder can be used to calculate the instantaneous speed by detecting the rotation angle or pulse signal of the motor shaft. In one implementation, the original pulse signal output by the encoder can be directly used to calculate the speed. In another implementation, in order to improve the accuracy of the data, the original pulse signal can be preprocessed, for example, high-frequency noise can be removed by a digital filter, or instantaneous fluctuation can be reduced by a signal smoothing algorithm, and then the actual instantaneous speed data can be calculated.

[0062] Secondly, the actual instantaneous speed data is compared with the expected response of the motor in the ideal linear working state to obtain the nonlinear behavior characteristics of the motor. The expected response of the motor in the ideal linear working state can be modeled by experimental data under standard temperature and no-load conditions, for example, a mathematical model based on the physical parameters of the motor can be established, or an input-output linear relationship can be fitted by a large amount of experimental data. In the comparison process, the nonlinear behavior can be quantified by calculating the difference between the actual instantaneous speed curve and the expected response curve. If the motor overshoots after reaching the target speed, the speed will temporarily exceed the target speed, and the maximum overshoot value is the jump peak deviation. These quantitative indicators can reflect the phenomenon that the dynamic response of the motor deviates from the ideal linear characteristics due to temperature influence.

[0063] Then, a two-dimensional mapping relationship is established according to the environmental temperature information and the nonlinear behavior characteristics. When the nonlinear behavior characteristics at a specific temperature are needed to be queried, they can be directly obtained through the two-dimensional mapping relationship. Another implementation manner is that a machine learning algorithm, such as a support vector machine or a neural network, can be used to train the collected environmental temperature and nonlinear behavior characteristic data, thereby establishing a prediction model. The model can predict the corresponding viscous delay time and jump peak deviation according to the input environmental temperature.

[0064] Before sending a target control instruction to the motor, the current environmental temperature needs to be obtained, and the nonlinear behavior characteristics corresponding to the current environmental temperature are obtained according to the established two-dimensional mapping relationship. For example, if the current environmental temperature is 25℃, the two-dimensional lookup table or the prediction model is queried to obtain the viscous delay time and jump peak deviation of the motor at 25℃. Then, according to these nonlinear behavior characteristics, the compensation parameters corresponding to the current environmental temperature are calculated in real time, including the viscous compensation coefficient of the motor and the jump suppression factor. The viscous compensation coefficient can be calculated according to the viscous delay time, for example, the longer the viscous delay time, the larger the viscous compensation coefficient, indicating that a larger initial voltage needs to be applied to overcome the viscous. The jump suppression factor can be calculated according to the jump peak deviation, for example, the larger the jump peak deviation, the larger the jump suppression factor, indicating that a smoother voltage change curve is needed to suppress the jump. The calculation of these compensation parameters can be based on a preset mathematical formula or an empirical model.

[0065] Finally, the target control instruction is compensated and adjusted according to the calculated compensation parameters, so as to improve the motor control precision and reduce the fluctuation of the drug delivery flow. In this way, even when the environmental temperature changes cause nonlinear changes in the performance of the motor, the control strategy can be adjusted in real time to ensure that the motor operates according to the expected trajectory, thereby improving the accuracy and stability of drug delivery.

[0066] The neurology drug delivery parameter adjustment method proposed in the present application aims to solve the problem of nonlinear behavior of the motor caused by changes in environmental temperature and characteristics of new drug solutions in the prior art, which affects the accuracy of drug delivery. Its working principle is to maintain the motor in a near-ideal linear response under various working conditions through real-time monitoring and dynamic compensation.

[0067] Specifically, when the infusion pump is operating, the data acquisition module continuously collects ambient temperature information around the pump and the actual instantaneous speed data of the motor after receiving control commands. This data forms the basis for assessing the motor's current operating state and environmental influences. After receiving this data, the characteristic identification module compares the actual instantaneous speed data with the motor's expected response under ideal linear operating conditions. This comparison accurately identifies the motor's current nonlinear behavior characteristics, such as viscous delay time (motor response lag) and jump peak deviation (motor speed overshoot). These characteristics directly reflect the motor's dynamic response deviating from ideal linear characteristics due to temperature effects.

[0068] Subsequently, the mapping module establishes a two-dimensional mapping relationship based on the collected ambient temperature information and the identified nonlinear behavior characteristics. This mapping relationship can be understood as an intelligent "experience base" that records the nonlinear behavior patterns that the motor may exhibit under different ambient temperatures. For example, at higher temperatures, the motor may exhibit smaller viscous delays and larger jump peaks, and this mapping relationship can capture this pattern.

[0069] Before issuing new target control commands to the motor (such as adjusting drug delivery flow), the compensation parameter calculation module first obtains the current ambient temperature. Then, using the previously established two-dimensional mapping relationship, it queries or predicts the nonlinear behavior characteristics that the motor might exhibit at the current temperature. Based on these predicted nonlinear behavior characteristics, the compensation parameter calculation module calculates the corresponding compensation parameters in real time, including the viscous compensation coefficient and the jump suppression factor. The viscous compensation coefficient is used to provide additional driving force during motor start-up or acceleration to overcome the viscous effect; the jump suppression factor is used to smooth changes in motor speed and suppress speed overshoot.

[0070] Finally, the command compensation module adjusts the original target control command based on these real-time calculated compensation parameters. For example, if a significant viscous delay in the motor is predicted, the command compensation module applies an enhanced voltage at the initial stage of the command to help the motor reach the target speed more quickly. If a potential speed jump is predicted, the command compensation module adjusts the voltage change curve to make it smoother, thereby suppressing the jump. Through this dynamic, real-time compensation adjustment, the motor can respond to control commands more accurately, its speed fluctuations are effectively suppressed, and ultimately, the stability and accuracy of drug delivery flow are ensured.

[0071] The proposed method for adjusting neurological drug delivery parameters represents a significant advancement and innovation compared to existing technologies. Traditional drug delivery systems typically rely on preset standard drug data and fixed feedback adjustment parameters. When faced with novel neurological drug solutions (e.g., those with higher viscosity) or changes in ambient temperature, these systems struggle to adapt to the non-linear degradation of motor performance, leading to decreased drug delivery accuracy and even unpredictable flow fluctuations such as "viscosity-jump."

[0072] The core innovation of this application lies in the introduction of real-time identification of the nonlinear behavior characteristics of motors and a dynamic compensation mechanism based on ambient temperature. Specifically, by collecting ambient temperature information and actual instantaneous speed data of the motor, and comparing them with the ideal linear response, this application can accurately quantify the nonlinear behavior characteristics of the motor, such as "viscous delay time" and "jump peak deviation." This insight into the deep physical characteristics of motors is generally lacking in existing technologies.

[0073] Furthermore, this application establishes a two-dimensional mapping relationship between ambient temperature and these nonlinear behavioral characteristics, which enables the prediction of nonlinear behavior that the motor may exhibit at a specific temperature. Before issuing control commands, the corresponding nonlinear behavioral characteristics can be obtained in real time based on the current ambient temperature, and dynamic compensation parameters (viscous compensation coefficient and jump suppression factor) can be calculated.

[0074] By adjusting the target control command according to these compensation parameters—for example, applying an enhanced voltage at the initial stage of the command to overcome viscosity and using a smooth transition with a reduced-slope voltage change curve to suppress jumps—this application effectively improves motor control accuracy and significantly reduces fluctuations in drug delivery flow. It provides an adaptive and intelligent solution capable of handling the nonlinear response of the motor caused by environmental and load changes, thereby ensuring the accuracy of neurological drug delivery and the stability of patient treatment outcomes. Compared to existing technologies, this application achieves significant improvements in the refinement, adaptability, and robustness of motor control.

[0075] In some embodiments, the step of collecting ambient temperature information around the infusion pump and the actual instantaneous rotational speed data of the motor after receiving the control command includes:

[0076] Collect ambient temperature information around the infusion pump and the original pulse signal of the motor after receiving control commands;

[0077] The original pulse signal is compared with the expected pulse pattern of the motor under standard temperature and ideal linear operating conditions to identify abnormal patterns;

[0078] When an abnormal pattern is detected, the presence of sensor artifacts is determined according to a preset temperature artifact association rule table. The temperature artifact association rule table records typical artifact patterns of the optical encoder under different temperature change rates.

[0079] If sensor artifacts exist, the original pulse signal is corrected to obtain the target pulse signal;

[0080] The actual instantaneous speed data of the motor is calculated based on the target pulse signal.

[0081] The first step is to acquire the raw pulse signals generated by the motor encoder. These raw pulse signals are the most direct electrical manifestation of the motor's rotation, containing rich dynamic information, but may also contain noise or anomalies.

[0082] Furthermore, the raw pulse signal is compared with the expected pulse pattern of the motor under standard temperature and ideal linear operating conditions to identify abnormal patterns. This step aims to establish a benchmark, namely the pulse behavior pattern of the motor under ideal conditions. By comparing the raw pulse signal acquired in real time with this benchmark, any abnormal patterns deviating from the normal range can be effectively detected. Its purpose is to initially screen out raw data that may have problems.

[0083] When an abnormal pattern is detected, the presence of sensor artifacts is determined according to a preset temperature artifact association rule table. This table records typical artifact patterns of optical encoders at different rates of temperature change. This step introduces intelligent judgment of the source of abnormal patterns. Not all anomalies originate from the nonlinear behavior of the motor itself; some anomalies may be caused by artifacts generated by sensors (such as optical encoders) under specific ambient temperature changes. By consulting the preset association rule table, it is possible to distinguish between genuine motor behavior anomalies and sensor measurement errors, thereby avoiding misjudgments of motor behavior.

[0084] If sensor artifacts are present, the original pulse signal is corrected to obtain the target pulse signal. When it is confirmed that the abnormal pattern is caused by sensor artifacts, a corresponding correction algorithm is executed, such as interpolating and compensating for lost pulses, or filtering out abnormal narrow pulses, wide pulses, or extra pulses. This correction process aims to eliminate the interference of sensor artifacts on the original pulse signal, ensuring that the pulse signal used for subsequent processing is accurate and reliable.

[0085] Finally, the actual instantaneous speed data of the motor is calculated based on the target pulse signal. After anomaly identification and artifact correction of the original pulse signal, the obtained target pulse signal is used to accurately calculate the actual instantaneous speed data of the motor. This process ensures the accuracy of the speed data and provides high-quality input for subsequent nonlinear behavior feature recognition.

[0086] The technical solution of this application effectively solves the potential error problem of directly acquiring actual instantaneous speed data by introducing refined processing of the original pulse signal, including abnormal pattern recognition and sensor artifact correction. Through multi-dimensional analysis and correction of the original pulse signal, it ensures that the obtained actual instantaneous speed data can more realistically reflect the dynamic response of the motor, rather than being interfered with by measurement noise or sensor artifacts. This lays a solid foundation for the accurate quantification of subsequent nonlinear behavioral characteristics (such as viscous delay time and jump peak deviation), thereby improving the reliability of the entire drug delivery parameter adjustment method.

[0087] The above technical solution significantly improves the accuracy and robustness of acquiring actual instantaneous motor speed data. By identifying and correcting sensor artifacts caused by changes in ambient temperature, it avoids misinterpreting sensor errors as nonlinear motor behavior, thus making the identification of nonlinear behavior characteristics more accurate. This directly improves the accuracy of compensation parameter calculation, ultimately ensuring more effective compensation adjustments to motor control commands, further enhancing the accuracy and stability of drug delivery, and reducing flow fluctuations. Its advantages are particularly pronounced in application scenarios with significant ambient temperature fluctuations.

[0088] In some optional embodiments, it is assumed that during the operation of the infusion pump, the ambient temperature suddenly rises, causing the optical encoder to generate a series of abnormal narrow pulse artifacts due to thermal expansion or changes in the refractive index of the optical path. According to the method described above, the original pulse signal containing these abnormal narrow pulses is first acquired. Then, this original pulse signal is compared with the expected pulse pattern of the motor at standard temperature, and these abnormal narrow pulses are identified as abnormal patterns. Next, according to a preset temperature artifact association rule table, it is determined that this abnormal narrow pulse pattern is associated with the rapid rise in the current ambient temperature, thus confirming it as a sensor artifact. Based on this, the original pulse signal is corrected, specifically by filtering out these abnormal narrow pulses as invalid pulses, thereby obtaining a clean target pulse signal. Finally, based on this corrected target pulse signal, the actual instantaneous speed data of the motor is accurately calculated, avoiding misjudgment of speed due to sensor artifacts and ensuring the accuracy of subsequent nonlinear behavior feature identification and compensation parameter calculation.

[0089] In some embodiments, the step of comparing the original pulse signal with the expected pulse pattern of the motor under standard temperature and ideal linear operating conditions to identify abnormal patterns includes:

[0090] If the original pulse signal meets at least one of the following conditions: pulse width deviates from the normal range, pulse amplitude deviates from the normal range, pulse is lost, or an additional pulse that does not match the expected rotational speed, then an abnormal pattern is identified.

[0091] Specifically, abnormal patterns in the raw pulse signal can be understood as irregularities in time or amplitude. These irregularities may be caused by sensor malfunction, environmental interference, or the unstable behavior of the motor itself. For example, a pulse width deviating from the normal range means that the pulse duration is significantly longer or shorter than expected, which may indicate encoder signal distortion. A pulse amplitude deviating from the normal range means that the voltage peak or trough of the pulse is abnormal, which may reflect signal attenuation or noise interference. Pulse loss means that a pulse signal is not detected at the expected time point, which may be due to momentary sensor malfunction or signal interruption. The presence of extra pulses that do not match the expected speed means that pulses that should not be present are mixed into the normal pulse sequence, which is usually caused by electromagnetic interference or sensor mis-triggeredness. When the raw pulse signal exhibits any one or more of the above conditions, it can be determined that an abnormal pattern exists, thereby triggering the subsequent artifact detection and signal correction process.

[0092] The technical solution of this application, by setting specific abnormal pattern recognition conditions, can accurately capture various potential problems in the original pulse signal of the motor. By comprehensively judging pulse width, pulse amplitude, pulse loss, and extra pulses, it can effectively distinguish normal motor operating signals from signals affected by interference or faults. This meticulous recognition mechanism ensures that subsequent judgment of sensor artifacts and signal correction can be based on accurate abnormal signals, avoiding misjudging normal signals as abnormal, thereby improving the accuracy and reliability of data processing.

[0093] The above technical solution enables precise identification of abnormal patterns in the original pulse signal of the motor. This identification method not only comprehensively covers a variety of common signal anomalies but also effectively avoids misjudgments and omissions through clear judgment criteria, providing a solid foundation for subsequent sensor artifact judgment and signal correction. This ensures the accuracy of the actual instantaneous speed data of the motor, thereby improving the precision and reliability of the entire drug delivery parameter adjustment method, and ultimately guaranteeing the stability and safety of the drug delivery flow rate.

[0094] In some embodiments, the step of correcting the original pulse signal to obtain the target pulse signal if sensor artifacts exist includes:

[0095] If pulse loss artifacts exist, linear interpolation is used for compensation; if abnormally narrow or wide pulse artifacts exist, they are treated as invalid pulses and filtered out; and if extra pulse artifacts exist, they are treated as noise and filtered out, finally correcting to obtain the target pulse signal.

[0096] Specifically, pulse loss artifacts refer to the phenomenon where pulse signals that should appear in the original pulse signal fail to be properly acquired by the sensor or are lost during transmission. This loss leads to an underestimation of the rotational speed. Compensation using linear interpolation involves generating one or more simulated pulses at the point of loss based on the characteristics of adjacent valid pulse signals before and after the lost pulse, such as time interval and amplitude, through linear prediction. This restores the continuity and integrity of the signal. The purpose is to compensate for the information loss caused by pulse loss and ensure the accuracy of rotational speed calculations.

[0097] Abnormally narrow or wide pulse artifacts can be understood as pulse signal widths significantly deviating from their normal or expected range. Abnormally narrow pulses may be caused by transient interference, while abnormally wide pulses may be caused by signal sticking or sensor response lag. Filtering out abnormally narrow or wide pulses as invalid pulses means identifying pulse signals exceeding a set threshold range for pulse width and removing them from the original pulse signal, excluding them from subsequent speed calculations. The purpose is to eliminate erroneous counting or timing caused by abnormal pulse widths, avoiding interference with speed calculations.

[0098] In practical applications, extra pulse artifacts specifically refer to redundant pulse signals in the original pulse signal that are not generated by the normal rotation of the motor. These artifacts can be caused by electromagnetic interference, power supply noise, or sensor malfunctions. Filtering out these extra pulses as noise involves using signal processing techniques, such as setting pulse amplitude thresholds, frequency analysis, or pattern recognition, to identify these irregular and unexpected pulse signals as noise and remove them from the original pulse signal. The goal is to purify the pulse signal, ensuring that only pulse signals that truly reflect motor rotation are used for speed calculation.

[0099] The technical solution of this application effectively solves various error problems that may occur in the acquisition process of the original pulse signal by adopting targeted correction strategies for different types of sensor artifacts. Specifically, for pulse loss artifacts, the linear interpolation method can make reasonable inferences based on the inherent laws of the signal, recover the missing rotation information, and avoid underestimation of the rotation speed due to incomplete data. For abnormally narrow or wide pulse artifacts, by identifying them as invalid pulses and filtering them out, the interference of these distorted signals on pulse counting can be avoided, ensuring that each valid pulse accurately corresponds to one rotation event. In addition, for extra pulse artifacts, they are treated as noise and filtered out, which can effectively remove false signals generated by external interference or false triggering, ensuring the purity of the pulse signal. Thus, by performing multi-dimensional and refined correction on the original pulse signal, it is ensured that the final target pulse signal can more realistically and accurately reflect the actual rotation state of the motor.

[0100] Through the above technical solutions, this application can significantly improve the quality and accuracy of the original pulse signal. Customized correction methods are employed to address different types of sensor artifacts, avoiding the limitations that may arise from a single correction strategy. For example, linear interpolation effectively compensates for the information gaps caused by pulse loss, while filtering out abnormal pulse widths and extra pulses effectively suppresses interference from noise and distorted signals. This refined correction mechanism ensures that the target pulse signal extracted from the original pulse signal has higher reliability and accuracy, thus providing a solid foundation for the accurate calculation of subsequent actual instantaneous motor speed data, ultimately contributing to improving the overall accuracy and stability of neurological drug delivery.

[0101] In some alternative embodiments, it is assumed that during the operation of the infusion pump motor, the raw pulse signal acquired by its optical encoder exhibits the following characteristics:

[0102] First, during a certain time period, five consecutive pulse signals are lost due to a momentary signal interruption, creating a pulse loss artifact. At this point, a linear interpolation method is activated. Based on the valid pulse sequences before and after the loss, five simulated pulses are calculated and generated, and inserted into the lost position, thereby restoring the integrity of the pulse sequence for that time period.

[0103] Secondly, at another point in time, due to electromagnetic interference, an abnormally narrow pulse appeared, with a width much smaller than the normal pulse width. This abnormal narrow pulse was identified using a preset pulse width threshold and marked as an invalid pulse for filtering out, thus preventing it from being mistakenly counted as a rotation.

[0104] Secondly, during stable motor operation, due to power fluctuations, an extra pulse with low amplitude and irregularity appeared in the original pulse signal. This extra pulse was identified as noise and removed from the pulse sequence using a noise identification algorithm.

[0105] Through the above targeted correction processing, various artifacts in the original pulse signal are effectively eliminated or compensated, and the final target pulse signal is a highly pure signal that accurately reflects the actual speed of the motor, laying the foundation for subsequent accurate calculation of the actual instantaneous speed data of the motor.

[0106] In some embodiments, the step of calculating the actual instantaneous speed data of the motor based on the target pulse signal includes:

[0107] The target pulse signal is converted into revolutions per minute in real time through rotational speed calculation to obtain the actual instantaneous rotational speed data.

[0108] The process involves converting the pulse signal output from the optical encoder into motor speed. Specifically, the optical encoder generates a series of pulses as the motor rotates, with each pulse corresponding to a specific angle of rotation. By calculating the number of pulses generated per unit time, the instantaneous speed of the motor can be estimated. For example, a fixed time window can be set, the total number of pulses received within that window can be counted, and then the instantaneous speed of the motor can be calculated based on the encoder's resolution (i.e., the number of pulses per revolution) and the length of the time window. Revolutions per minute (RPM) is a commonly used unit for measuring motor speed, representing the number of revolutions the motor makes per minute. Converting the pulse signal into RPM helps to intuitively understand the motor's operating state and provides standardized input data for subsequent nonlinear behavior feature identification and compensation parameter calculation.

[0109] The technical solution of this application ensures that the obtained instantaneous speed data accurately reflects the true operating state of the motor by converting the corrected target pulse signal into revolutions per minute in real time. In cases where the original pulse signal may be affected by sensor artifacts, the corrected target pulse signal eliminates the influence of abnormal pulses, thus providing a reliable basis for subsequent speed calculation. This avoids speed calculation errors caused by pulse signal distortion and lays the foundation for accurately identifying the nonlinear behavior characteristics of the motor.

[0110] The above technical solution ensures accurate and real-time acquisition of the motor's actual instantaneous speed data from the corrected pulse signal. This precise speed data is a key input for subsequent identification of nonlinear behavioral characteristics such as motor hysteresis delay time and jump peak deviation, thereby effectively improving the accuracy and reliability of the entire drug delivery parameter adjustment method. Ultimately, this helps to achieve fine control of drug delivery flow rate and reduce fluctuations.

[0111] In some embodiments, the step of establishing a two-dimensional mapping relationship based on the ambient temperature information and the nonlinear behavior characteristics includes:

[0112] A two-dimensional lookup table is used to establish the correlation between ambient temperature information and nonlinear behavior characteristics. The horizontal axis of the two-dimensional lookup table represents the temperature range divided according to a preset step size, and the vertical axis represents the viscosity compensation strength benchmark value and jump suppression strength benchmark value within the corresponding temperature range.

[0113] The two-dimensional lookup table can be understood as a pre-built data structure designed to store and quickly retrieve the correspondence between ambient temperature and the nonlinear behavior characteristics of the motor. The horizontal axis of the lookup table is set as temperature intervals divided by a preset step size; for example, the temperature range can be divided into several discrete, equally spaced intervals, each representing a specific ambient temperature range. The vertical axis is set as the viscous compensation strength benchmark value and jump suppression strength benchmark value within the corresponding temperature interval. These benchmark values ​​are pre-determined through experiments or simulations at different temperature intervals, providing effective compensation for motor viscous behavior and suppression of jump. This approach avoids complex real-time calculations during runtime, thereby improving the efficiency and response speed of the mapping process.

[0114] The technical solution of this application introduces a two-dimensional lookup table to pre-store the correlation between ambient temperature information and nonlinear behavior characteristics. When compensation parameters are needed, the corresponding temperature range can be quickly located in the lookup table based on the current real-time ambient temperature, and the preset viscous compensation intensity benchmark value and jump suppression intensity benchmark value can be directly read. This lookup table-based mechanism avoids complex mathematical modeling and real-time calculations every time compensation is needed, significantly reducing the consumption of computing resources and shortening the response time. Therefore, it ensures the real-time acquisition of compensation parameters, thus providing a timely and accurate basis for subsequent target control command compensation adjustments.

[0115] The above technical solution utilizes a two-dimensional lookup table to pre-store the correlation between ambient temperature and nonlinear behavioral characteristics, greatly simplifying the process of establishing the mapping relationship. Compared to complex real-time mathematical model calculations, this solution significantly improves the efficiency and real-time performance of acquiring compensation parameters while reducing the computational burden. This enables a faster response to changes in ambient temperature and timely adjustment of compensation parameters, thereby further improving motor control accuracy, effectively reducing fluctuations in drug delivery flow, and ensuring the stability and accuracy of drug delivery. It is particularly suitable for neurological drug delivery scenarios with high real-time requirements.

[0116] In some optional embodiments, the two-dimensional lookup table can be constructed as a matrix or a multidimensional array. For example, the temperature range on the horizontal axis can be divided into 5°C increments, such as 0-5°C, 5-10°C, 10-15°C, etc. For each temperature range, the motor is subjected to extensive testing in a laboratory environment, and its viscous delay time and jump peak deviation at different temperatures are recorded. Based on this, the corresponding viscous compensation strength benchmark value and jump suppression strength benchmark value are determined. For example, in the temperature range of 10-15°C, the possible corresponding viscous compensation strength benchmark value is X, and the jump suppression strength benchmark value is Y. When the current ambient temperature is detected to be 12°C during operation, the row corresponding to 10-15°C is quickly found, and X and Y are extracted as the benchmark values ​​of the current compensation parameters, which are then used to calculate the final compensation parameters in real time. This preset and lookup method ensures that appropriate compensation parameters can be obtained quickly and accurately under various ambient temperatures, thereby effectively suppressing the nonlinear behavior of the motor.

[0117] In some embodiments, the step of adjusting the target control command according to the compensation parameters to improve motor control accuracy and reduce fluctuations in drug delivery flow includes:

[0118] According to the compensation parameters, an enhanced voltage positively correlated with the viscosity compensation coefficient is applied at the initial stage of the target control command to overcome viscosity, and a voltage change curve with a reduced slope determined by the jump suppression factor is used for smooth transition to suppress jump.

[0119] Specifically, the viscosity compensation coefficient is calculated based on the motor's viscosity delay time and is used to quantify the additional driving force required to overcome internal friction and inertia of the motor. At the initial stage of the target control command, i.e., when the motor starts or needs to rapidly change speed, an enhanced voltage positively correlated with the viscosity compensation coefficient is applied. This aims to provide additional instantaneous driving energy to quickly overcome the static and dynamic friction of mechanical components such as motor bearings and gears, as well as the starting lag caused by rotor inertia. The amplitude and duration of this enhanced voltage can be dynamically adjusted according to the viscosity compensation coefficient to ensure that the motor can quickly respond to the command and reach the target speed. The jump suppression factor is calculated based on the motor's jump peak deviation and is used to quantify the degree of suppression of motor speed overshoot. When the motor speed approaches the target value, directly cutting off or significantly reducing the driving voltage may cause the speed to exceed the target value due to inertia, resulting in a jump peak. Therefore, this application uses a voltage change curve with a reduced slope determined by the jump suppression factor for a smooth transition. This means that when the motor speed approaches the target value, the drive voltage does not change abruptly, but gradually decreases at a gentle slope determined by a preset jump suppression factor, thereby avoiding speed overshoot caused by inertia and achieving a smooth transition and precise stability of the speed.

[0120] The technical solution of this application effectively solves the problem of nonlinear dynamic response of motors under different ambient temperatures by specifying the compensation parameters as a dynamic adjustment strategy for the driving voltage. Specifically, in the initial stage of motor start-up or acceleration, due to the mechanical viscosity and inertia inside the motor, its response speed often lags behind the control command. By applying an enhanced voltage positively correlated with the viscosity compensation coefficient, an additional instantaneous driving force can be provided to the motor, thereby quickly overcoming these resistances, shortening the motor's response time, and enabling it to reach the target speed more quickly. This is equivalent to giving the motor a "boost" when it "starts up," ensuring that it can quickly leave the stationary state or accelerate to the required speed. At the same time, when the motor speed approaches the target value, if it is not controlled, its inertia may cause the speed to exceed the target value, resulting in unnecessary overshoot or jumps. This application introduces a jump suppression factor and uses it to determine the reduction slope of the driving voltage, making the voltage change process smoother. This smooth transition mechanism can effectively absorb motor inertia, avoid sudden changes in speed, and thus suppress the occurrence of speed overshoot. This ensures that the motor can operate stably after reaching the target speed, avoiding the problem of inaccurate drug delivery flow caused by speed fluctuations.

[0121] Through the above technical solution, this application can significantly improve the precision of motor control. By applying enhanced voltage at the initial stage of the command, the viscous effect during motor start-up or acceleration is effectively overcome, the response time is shortened, and the instantaneous response speed of the motor to control commands is improved. Simultaneously, by using a voltage change curve with a reduced slope for smooth transition, the jump and overshoot phenomena of motor speed are successfully suppressed, allowing the motor speed to reach and maintain the target value more smoothly and accurately. Therefore, fluctuations in drug delivery flow are significantly reduced, ensuring the stability and accuracy of neurological drug delivery, thereby improving treatment efficacy and patient safety.

[0122] In some alternative embodiments, it is assumed that the infusion pump motor needs to start from a standstill and reach a target speed of 1000 RPM within 100 milliseconds. At the current ambient temperature, based on the two-dimensional mapping and real-time calculations, a viscosity compensation coefficient of 0.15 and a jump suppression factor of 0.8 are obtained. When the target control command to start the motor is issued, in the initial phase of the command (e.g., the first 20 milliseconds), the controller applies an additional boost voltage on top of the normal starting voltage, based on the viscosity compensation coefficient of 0.15. For example, if the normal starting voltage is 5V, then in the initial phase, 5V + (5V) might be applied. An enhanced voltage of 5.75V (0.15) is applied. This enhanced voltage quickly overcomes the static friction and inertia within the motor, allowing the motor speed to increase rapidly in a short time, avoiding start-up delay. Subsequently, when the motor speed approaches the target speed of 1000 RPM (e.g., reaching 950 RPM), the controller adjusts the descent slope of the drive voltage based on a jump suppression factor of 0.8. For example, instead of directly dropping the voltage from a high level to the steady-state voltage required to maintain the speed, a gentler slope determined by the jump suppression factor 0.8 is applied (e.g., the voltage smoothly drops from 5.75V to 4.5V over the next 30 milliseconds). This smooth voltage change curve effectively buffers motor inertia, preventing the speed from exceeding 1000 RPM, thereby suppressing speed overshoot and ensuring that the motor smoothly reaches and stabilizes at 1000 RPM, thus guaranteeing the accuracy of drug delivery flow.

[0123] In some embodiments, the viscous delay time is quantified by detecting the difference between the time required for the actual motor speed to reach 90% of the target speed and the expected response time, and the jump peak deviation is quantified by detecting the maximum deviation value of the motor speed exceeding 105% of the target speed.

[0124] The viscous delay time refers to the difference between the time it takes for a motor to increase its actual speed from rest or a lower speed to 90% of the target speed after receiving a control command, and the time required to reach the same speed under ideal linear operating conditions. This 90% threshold was selected to capture the response lag caused by factors such as internal friction and changes in lubricant viscosity during the initial stages of motor start-up or acceleration. This lag is particularly pronounced at low speeds or during startup. By comparing the difference between the actual response and the expected response, the viscous effect of the motor during startup or acceleration can be accurately quantified.

[0125] Furthermore, the peak jump deviation refers to the brief moment when the motor speed exceeds the target speed in response to a control command, before falling back to the target speed. This application uses the maximum deviation of the motor speed exceeding the target speed by 105% as the quantitative index of the peak jump deviation. This 105% threshold is set to identify and quantify the instantaneous overshoot phenomenon caused by factors such as inertia, control system overshoot, or external disturbances when the motor reaches or approaches the target speed. By detecting the peak speed exceeding the target speed, the stability and overshoot degree of the motor during dynamic response can be effectively reflected.

[0126] The technical solution of this application enables the precise measurement and identification of two key nonlinear behavioral characteristics—viscous delay time and jump peak deviation—by setting specific quantification standards. Quantifying the viscous delay time allows for the identification of motor response hysteresis during startup or initial acceleration, which is crucial for drug delivery pumps requiring precise start-up and shutdown control. Quantifying the jump peak deviation allows for the capture of instantaneous overshoot when the motor reaches the target speed, which is significant for avoiding instantaneous fluctuations in drug delivery flow rate. These precise quantification methods provide reliable input data for subsequent compensation parameter calculations, thereby ensuring the effectiveness of the compensation strategy.

[0127] Through the aforementioned technical solution, the quantification method for viscous delay time and jump peak deviation is standardized and refined. This precise quantification method can more accurately capture the nonlinear dynamic response characteristics of the motor under different ambient temperatures, such as start-up hysteresis and instantaneous overshoot. Therefore, when establishing a two-dimensional mapping relationship, the obtained nonlinear behavioral characteristic data will more realistically reflect the actual operating state of the motor, enabling the subsequently calculated viscous compensation coefficient and jump suppression factor to more accurately match the actual needs of the motor. Ultimately, this helps improve the precision of compensation adjustments, further enhances motor control accuracy, and significantly reduces fluctuations in drug delivery flow, ensuring the stability and accuracy of drug delivery.

[0128] In some embodiments, the step of acquiring ambient temperature information around the infusion pump and the original pulse signal of the motor after receiving the control command includes:

[0129] An NTC thermistor temperature sensor is used to collect ambient temperature information at a frequency of no less than 10 times per second, and an optical encoder is used to collect raw pulse signals at a frequency of no less than 0.5 milliseconds.

[0130] Specifically, an NTC thermistor temperature sensor is a sensor whose resistance changes with temperature. It boasts advantages such as high sensitivity, fast response, and small size, making it suitable for accurately measuring the ambient temperature around infusion pumps. Using an NTC thermistor temperature sensor ensures high accuracy and real-time performance in acquiring ambient temperature information. Acquiring ambient temperature information at a frequency of at least 10 times per second means performing at least 10 temperature measurements per second. This high-frequency acquisition captures subtle changes and rapid fluctuations in ambient temperature, providing sufficient density of temperature data for subsequent nonlinear behavior feature identification and compensation parameter calculation.

[0131] In practical applications, optical encoders are sensors that convert mechanical displacement into electrical signals through photoelectric conversion, commonly used to measure the speed and position of motors. They reflect the motor's motion state by detecting the pulse signals generated when the motor rotates. Using an optical encoder provides high-precision raw motor pulse signals, laying the foundation for subsequent speed calculations and abnormal pattern recognition. Furthermore, the raw pulse signals are acquired at a frequency of no less than 0.5 milliseconds, i.e., at least 2000 pulse data points per second. This extremely high sampling frequency ensures precise capture of instantaneous changes in motor speed; even transient pulse signals generated when the motor is running at high speed or experiencing minor vibrations can be accurately recorded, thus avoiding signal distortion or information loss due to insufficient sampling.

[0132] The technical solution of this application solves the problems of insufficient data acquisition accuracy and real-time performance in traditional methods by employing an NTC thermistor temperature sensor and an optical encoder, and setting a high-frequency acquisition strategy. The high sensitivity and fast response characteristics of the NTC thermistor temperature sensor, combined with a acquisition frequency of at least 10 times per second, enable real-time and accurate acquisition of ambient temperature changes around the infusion pump, providing reliable input for the subsequent establishment of a temperature-nonlinear behavior mapping relationship. Simultaneously, the high-precision pulse output of the optical encoder, coupled with an ultra-high sampling frequency of at least 0.5 milliseconds, ensures the integrity and precision of the original pulse signal of the motor, allowing even minute instantaneous speed fluctuations generated by the motor after receiving control commands to be accurately captured. This provides high-quality raw data for accurately identifying nonlinear behavioral characteristics such as hysteresis delay time and jump peak deviation of the motor. This high-precision, high-frequency data acquisition mechanism ensures the accuracy of subsequent nonlinear behavior feature identification, two-dimensional mapping relationship establishment, and compensation parameter calculation from the source, laying a solid foundation for ultimately achieving high-precision motor control and stable drug delivery.

[0133] The above technical solution significantly improves the accuracy and real-time performance of acquiring ambient temperature information and the original motor pulse signal by employing an NTC thermistor temperature sensor and an optical encoder for high-frequency data acquisition. This enables more accurate perception of temperature changes around the infusion pump and the motor's dynamic response at different temperatures, providing high-quality raw data for accurately identifying the motor's nonlinear behavior characteristics (such as viscous delay time and jump peak deviation). Compared to technical solutions that do not specify sensor type and acquisition frequency, this solution effectively avoids nonlinear feature identification errors caused by insufficient or inaccurate data acquisition, thereby improving the accuracy of the two-dimensional mapping relationship and the precision of compensation parameter calculation. Ultimately, this optimization ensures more precise and effective compensation adjustments to the target control commands, significantly improving motor control accuracy and further reducing fluctuations in drug delivery flow, thus guaranteeing the stability and safety of neurological drug delivery.

[0134] As an optional implementation, the motor control unit of the infusion pump is equipped with an NTC thermistor temperature sensor and an optical encoder. The NTC thermistor temperature sensor is mounted near the infusion pump housing and sends temperature readings to the main controller every 0.1 seconds (i.e., 10 times per second). For example, when the ambient temperature rises rapidly from 20°C to 25°C, the sensor can promptly capture this change and provide a continuous stream of temperature data. Simultaneously, the optical encoder is integrated onto the motor shaft, and its output pulse signal is acquired every 0.2 milliseconds (i.e., 5000 times per second). When the motor receives a start command and begins to accelerate, the optical encoder can record every minute change in motor speed from rest to the target speed with extremely high resolution, including the viscous effect at startup and any potential speed overshoot. For example, at the moment of motor startup, due to the viscous effect, the actual speed may lag behind the expected speed; the high-frequency pulse data from the optical encoder can accurately reflect this delay. This high-frequency, high-precision data acquisition allows for the acquisition of sufficiently detailed ambient temperature and motor motion data, enabling accurate identification of nonlinear behavioral characteristics of the motor at the current temperature, such as viscous delay time and jump peak deviation, thus providing a solid data foundation for subsequent compensation parameter calculations.

[0135] This application also proposes a neurological drug delivery parameter adjustment system, such as... Figure 2 As shown, a neurological drug delivery parameter adjustment system 100 includes:

[0136] Data acquisition module 10 is used to collect ambient temperature information around the infusion pump and the actual instantaneous speed data of the motor after receiving control commands;

[0137] The feature recognition module 20 is used to compare the actual instantaneous speed data with the expected response of the motor under ideal linear working conditions to obtain the nonlinear behavior characteristics of the motor. The nonlinear behavior characteristics include viscous delay time and jump peak deviation, which are used to reflect the phenomenon that the dynamic response of the motor deviates from the ideal linear characteristics due to the influence of temperature.

[0138] The mapping establishment module 30 is used to establish a two-dimensional mapping relationship based on the ambient temperature information and the nonlinear behavior characteristics;

[0139] The compensation parameter calculation module 40 is used to obtain the current ambient temperature before issuing the target control command to the motor, and to obtain the nonlinear behavior characteristics corresponding to the current ambient temperature according to the two-dimensional mapping relationship; and to calculate the compensation parameters corresponding to the current ambient temperature in real time according to the corresponding nonlinear behavior characteristics, wherein the compensation parameters include the motor's viscosity compensation coefficient and jump suppression factor.

[0140] The instruction compensation module 50 is used to compensate and adjust the target control instruction according to the compensation parameters, so as to improve the motor control accuracy and reduce the fluctuation of drug delivery flow.

[0141] The neurology drug delivery parameter adjustment system proposed in this application acquires ambient temperature and the actual instantaneous speed of the motor in real time through its data acquisition module. A characteristic identification module accurately quantifies the nonlinear behavior characteristics of the motor, and a mapping module establishes a correlation between ambient temperature and these nonlinear behavior characteristics. Subsequently, a compensation parameter calculation module dynamically calculates compensation parameters based on the current ambient temperature and the mapping relationship. Finally, a command compensation module adjusts the target control command accordingly. Therefore, this system effectively overcomes the problem of decreased motor control accuracy in traditional systems under complex operating conditions, significantly improving the accuracy and stability of drug delivery and ensuring patient treatment outcomes.

[0142] The neurology drug delivery parameter adjustment system proposed in this application is based on improving motor control accuracy and reducing fluctuations in drug delivery flow rate through a dynamic compensation mechanism.

[0143] Specifically, the data acquisition module is configured to collect ambient temperature information around the infusion pump and the actual instantaneous rotational speed data of the motor after receiving control commands. The ambient temperature information can be collected by a temperature sensor (e.g., a thermistor sensor) integrated into the data acquisition module, which is set to continuously sample at a preset frequency (e.g., once per second). The actual instantaneous rotational speed data of the motor can be acquired by an encoder (e.g., an optical encoder) mounted on the motor, which calculates the instantaneous rotational speed by detecting the rotation angle of the motor shaft or outputting pulse signals. In a preferred embodiment, the data acquisition module may also include a signal preprocessing unit for preprocessing the raw pulse signal, such as removing high-frequency noise using a digital filter or reducing instantaneous fluctuations using a signal smoothing algorithm, to improve the accuracy of the actual instantaneous rotational speed data.

[0144] The characteristic identification module is configured to compare the actual instantaneous speed data acquired by the data acquisition module with the expected response of the motor under ideal linear operating conditions, thereby obtaining the nonlinear behavior characteristics of the motor. The expected response of the motor under ideal linear operating conditions can be pre-modeled using experimental data under standard temperature and no-load conditions, for example, by establishing a mathematical model based on the motor's physical parameters or by representing an input-output linear relationship fitted from experimental data. The characteristic identification module quantifies the nonlinear behavior by calculating the difference between the actual instantaneous speed curve and the expected response curve. Specifically, the viscous delay time can be quantified by detecting the difference between the time required for the motor's actual speed to reach 90% of the target speed and the expected response time; the jump peak deviation can be quantified by detecting the maximum deviation value of the motor speed exceeding 105% of the target speed. These nonlinear behavior characteristics are used to reflect the phenomenon that the motor's dynamic response deviates from the ideal linear characteristics due to temperature effects.

[0145] The mapping module is configured to establish a two-dimensional mapping relationship based on the ambient temperature information provided by the data acquisition module and the nonlinear behavior characteristics obtained by the characteristic identification module. In one implementation, the mapping module can construct a two-dimensional lookup table, where the horizontal axis is set to different ambient temperature ranges, and the vertical axis is set to the viscous delay time and jump peak deviation measured within the corresponding temperature range. This lookup table is filled by conducting multiple experiments at different temperatures and recording the nonlinear behavior characteristics of the motor. In another implementation, the mapping module can utilize machine learning algorithms (such as support vector machines or neural networks) to train the acquired ambient temperature and nonlinear behavior characteristic data, thereby establishing a predictive model that can predict the corresponding viscous delay time and jump peak deviation based on the input ambient temperature.

[0146] The compensation parameter calculation module is configured to acquire the current ambient temperature before issuing the target control command to the motor, and to obtain the nonlinear behavior characteristics corresponding to the current ambient temperature based on the two-dimensional mapping relationship established by the mapping module. For example, after acquiring the current ambient temperature, the compensation parameter calculation module will query a two-dimensional lookup table or use a prediction model to obtain the viscous delay time and jump peak deviation of the motor at that temperature. Subsequently, the compensation parameter calculation module calculates the compensation parameters corresponding to the current ambient temperature in real time based on these nonlinear behavior characteristics. The compensation parameters include the motor's viscous compensation coefficient and jump suppression factor. The viscous compensation coefficient can be calculated based on the viscous delay time; for example, the longer the viscous delay time, the larger the viscous compensation coefficient is set. The jump suppression factor can be calculated based on the jump peak deviation; for example, the larger the jump peak deviation, the larger the jump suppression factor is set. The calculation of these compensation parameters can be based on preset mathematical formulas or empirical models.

[0147] The command compensation module is configured to adjust the target control command based on the compensation parameters obtained from the compensation parameter calculation module, thereby improving motor control accuracy and reducing fluctuations in drug delivery flow. Specifically, in the initial stage of the target control command, the command compensation module can apply an additional boost voltage based on the viscosity compensation coefficient to help the motor overcome internal friction more quickly and reduce start-up delay. Furthermore, as the motor speed approaches the target speed, the command compensation module can use a voltage change curve with a reduced slope based on a jump suppression factor to smooth the transition, thus suppressing speed overshoot and avoiding instantaneous fluctuations in flow. Therefore, even when changes in ambient temperature cause nonlinear changes in motor performance, the command compensation module can adjust the control strategy in real time to ensure the motor operates along the expected trajectory, thereby improving the accuracy and stability of drug delivery.

[0148] The neurology drug delivery parameter adjustment system proposed in this application aims to solve the problem in existing technologies where nonlinear motor behavior, caused by changes in ambient temperature and the characteristics of novel drug solutions, affects the accuracy of drug delivery. Its working principle lies in using real-time monitoring and dynamic compensation to ensure that the motor maintains a near-ideal linear response under various operating conditions.

[0149] Specifically, when the infusion pump is operating, the data acquisition module continuously collects ambient temperature information around the pump and the actual instantaneous speed data of the motor after receiving control commands. This data forms the basis for assessing the motor's current operating state and environmental influences. After receiving this data, the characteristic identification module compares the actual instantaneous speed data with the motor's expected response under ideal linear operating conditions. This comparison accurately identifies the motor's current nonlinear behavior characteristics, such as viscous delay time (motor response lag) and jump peak deviation (motor speed overshoot). These characteristics directly reflect the motor's dynamic response deviating from ideal linear characteristics due to temperature effects.

[0150] Subsequently, the mapping module establishes a two-dimensional mapping relationship based on the collected ambient temperature information and the identified nonlinear behavior characteristics. This mapping relationship can be understood as an intelligent "experience base" that records the nonlinear behavior patterns that the motor may exhibit under different ambient temperatures. For example, at higher temperatures, the motor may exhibit smaller viscous delays and larger jump peaks, and this mapping relationship can capture this pattern.

[0151] Before the system needs to issue new target control commands to the motor (such as adjusting drug delivery flow), the compensation parameter calculation module first obtains the current ambient temperature. Then, it uses the previously established two-dimensional mapping relationship to query or predict the nonlinear behavior characteristics that the motor may exhibit at the current temperature. Based on these predicted nonlinear behavior characteristics, the compensation parameter calculation module calculates the corresponding compensation parameters in real time, including the viscous compensation coefficient and the jump suppression factor. The viscous compensation coefficient is used to provide additional driving force during motor start-up or acceleration to overcome the viscous effect; the jump suppression factor is used to smooth changes in motor speed and suppress speed overshoot.

[0152] Finally, the command compensation module adjusts the original target control command based on these real-time calculated compensation parameters. For example, if a significant viscous delay in the motor is predicted, the command compensation module applies an enhanced voltage at the initial stage of the command to help the motor reach the target speed more quickly. If a potential speed jump is predicted, the command compensation module adjusts the voltage change curve to make it smoother, thereby suppressing the jump. Through this dynamic, real-time compensation adjustment, the motor can respond to control commands more accurately, its speed fluctuations are effectively suppressed, and ultimately, the stability and accuracy of drug delivery flow are ensured.

[0153] The neurological drug delivery parameter adjustment system proposed in this application represents a significant advancement and innovation compared to existing technologies. Traditional drug delivery systems typically rely on preset standard drug data and fixed feedback adjustment parameters. When faced with novel neurological drug solutions (e.g., those with higher viscosity) or changes in ambient temperature, these systems struggle to adapt to the non-linear degradation of motor performance, leading to decreased drug delivery accuracy and even unpredictable flow fluctuations such as "viscosity-jumping." Existing systems often cannot autonomously identify this specific physical failure mode or provide effective compensation.

[0154] The core innovation of this application lies in its system architecture, which enables real-time identification of the nonlinear behavior characteristics of motors and dynamic compensation based on ambient temperature. Specifically, the data acquisition module and the characteristic identification module work together to accurately quantify the nonlinear behavior characteristics of motors, such as "viscous delay time" and "jump peak deviation," which is a capability for insight into the deep physical characteristics of motors that is generally lacking in existing systems.

[0155] Furthermore, the mapping module establishes a two-dimensional mapping relationship based on ambient temperature and these nonlinear behavioral characteristics, enabling the system to predict the nonlinear behavior that the motor may exhibit at specific temperatures. Before issuing control commands, the compensation parameter calculation module can acquire the corresponding nonlinear behavioral characteristics in real time based on the current ambient temperature and calculate dynamic compensation parameters (viscous compensation coefficient and jump suppression factor). This forward-looking, environmentally-based dynamic compensation strategy is unparalleled by existing fixed-parameter or hysteresis feedback control systems.

[0156] By adjusting the target control command according to these compensation parameters through the command compensation module, such as applying enhanced voltage in the initial stage of the command to overcome viscosity and using a voltage change curve with a reduced slope for smooth transition to suppress jumps, the system of this application can effectively improve the motor control accuracy and significantly reduce the fluctuation of drug delivery flow. This system not only solves the problem of decreased motor control accuracy in traditional systems under complex operating conditions, but more importantly, it provides an adaptive and intelligent solution that can cope with the nonlinear response of the motor caused by changes in environment and load, thereby ensuring the accuracy of neurological drug delivery and the stability of patient treatment effects. Compared with the prior art, the system of this application has achieved significant improvements in motor control refinement, adaptability, and robustness.

[0157] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A neurological drug delivery parameter adjustment system, characterized by, The system comprises: a data acquisition module, configured to acquire ambient temperature information around the infusion pump and actual instantaneous speed data of the motor after receiving a control instruction; a characteristic identification module, configured to compare the actual instantaneous speed data with an expected response of the motor in an ideal linear working state, to obtain nonlinear behavior characteristics of the motor, the nonlinear behavior characteristics including a viscous delay time and a jump peak deviation, and to reflect a phenomenon that a dynamic response of the motor deviates from an ideal linear characteristic due to temperature influence; a mapping establishment module, configured to establish a two-dimensional mapping relationship according to the ambient temperature information and the nonlinear behavior characteristics; a compensation parameter calculation module, configured to acquire a current ambient temperature before issuing a target control instruction to the motor, to acquire nonlinear behavior characteristics corresponding to the current ambient temperature according to the two-dimensional mapping relationship, and to calculate compensation parameters corresponding to the current ambient temperature in real time according to the corresponding nonlinear behavior characteristics, the compensation parameters including a viscous compensation coefficient and a jump suppression factor of the motor; an instruction compensation module, configured to compensate and adjust the target control instruction according to the compensation parameters, to improve motor control precision, and to reduce fluctuation of a drug delivery flow.

2. The neurologic drug delivery parameter adjustment system of claim 1, wherein, The data acquisition module is further configured to: acquire ambient temperature information around the infusion pump and original pulse signals of the motor after receiving a control instruction; compare the original pulse signals with an expected pulse mode of the motor in a standard temperature and an ideal linear working state, to identify an abnormal mode; when the abnormal mode is identified, determine whether there is a sensor artifact according to a preset temperature artifact association rule table, the temperature artifact association rule table recording typical artifact modes of an optical encoder under different temperature change rates; if there is a sensor artifact, correct the original pulse signals to obtain target pulse signals; calculate actual instantaneous speed data of the motor according to the target pulse signals.

3. The neurological drug delivery parameter adjustment system of claim 2, wherein, The comparison of the original pulse signals with the expected pulse mode of the motor in the standard temperature and the ideal linear working state to identify the abnormal mode comprises: if the original pulse signals satisfy at least one of the following conditions: a pulse width deviates from a normal range, a pulse amplitude deviates from a normal range, a pulse is lost, and an extra pulse appears which does not match an expected speed, it is identified that there is an abnormal mode.

4. The neurological drug delivery parameter adjustment system of claim 2, wherein, The correction of the original pulse signals to obtain the target pulse signals if there is a sensor artifact comprises: if there is a pulse loss artifact, a linear interpolation method is used for compensation; if there is an abnormal narrow pulse or an abnormal wide pulse artifact, the abnormal narrow pulse or the abnormal wide pulse is regarded as an invalid pulse and filtered out; and if there is an extra pulse artifact, the extra pulse is regarded as noise and filtered out, to finally correct the target pulse signals.

5. The neurologic drug delivery parameter adjustment system of claim 2, wherein, The calculation of the actual instantaneous speed data of the motor according to the target pulse signals comprises: the target pulse signals are converted into revolutions per minute in real time through speed calculation, to obtain the actual instantaneous speed data.

6. The neurologic drug delivery parameter adjustment system of claim 1, wherein, The mapping establishment module is further configured to: A two-dimensional lookup table is used to establish the correlation between the ambient temperature information and the nonlinear behavior characteristics, the horizontal axis of the two-dimensional lookup table is the temperature interval divided by a preset step size, and the vertical axis is the reference value of the viscosity compensation strength and the jump suppression strength in the corresponding temperature interval.

7. The neurologic drug delivery parameter adjustment system of claim 1, wherein, The instruction compensation module is further configured to: According to the compensation parameter, an enhanced voltage positively correlated with the viscosity compensation coefficient is applied to overcome the viscosity in the initial stage of the target control instruction, and a voltage change curve with a decreasing slope determined by the jump suppression factor is used for smooth transition to suppress the jump.

8. The neurologic drug delivery parameter adjustment system of claim 1, wherein, The viscosity delay time is quantified by detecting the difference between the time required for the actual motor speed to reach 90% of the target speed and the expected response time, and the jump peak deviation is quantified by detecting the maximum deviation value of the motor speed exceeding 105% of the target speed.

9. The neurologic drug delivery parameter adjustment system of claim 2, wherein, The ambient temperature information around the infusion pump and the original pulse signal of the motor after receiving the control instruction include: An NTC thermistor temperature sensor is used to collect ambient temperature information at a frequency of no less than 10 times per second, and an optical encoder is used to collect the original pulse signal at a frequency of no less than 0.5 milliseconds.

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