A method for monitoring the curative effect of Chinese and Mongolian and western medicines in real time based on biosensing technology

Abstract

The application relates to the field of medical data, and discloses a real-time monitoring method for drug efficacy of Chinese and Mongolian and Western medicine based on a biosensing technology, which is used for realizing real-time monitoring of drug efficacy and individualized drug use guidance. The method comprises the following steps: obtaining original sensing signals from real-time multi-modal biosignals collected from the body surface or minimally invasive body fluid samples of a drug user, and obtaining sensor array outputs; extracting real-time pharmacokinetic characteristic signals based on a preset pharmacokinetic model, and mapping the real-time pharmacokinetic characteristic signals into efficacy evaluation parameters according to the types of the drugs; comparing the efficacy evaluation parameters with a preset safe and effective concentration range, and generating real-time drug use state indications and dose adjustment prompt information. The application designs a quantitative evaluation mode for different types of drugs, can compare and generate efficacy state codes and dose adjustment suggestions in real time, comprehensively generates a drug use guidance report, and transmits the drug use guidance report to a drug user end or a clinical monitoring end in real time, so that instant adjustment of a drug use scheme is realized, and the safety and effectiveness of drug use are ensured.

Description

Technical Field

[0001] This invention relates to the field of medical data, and in particular to a method for real-time monitoring of the efficacy of traditional Chinese, Mongolian and Western medicines based on biosensor technology. Background Technology

[0002] With the rapid development of modern medicine, traditional Chinese medicine, Mongolian medicine, and Western medicine are playing increasingly important roles in disease treatment. Traditional Chinese and Mongolian medicines, with their multi-component, multi-target, and holistic regulatory characteristics, demonstrate unique advantages in treating complex and chronic diseases; while Western medicines, with their clearly defined chemical components, rapid efficacy, and precise dosage control, dominate the treatment of acute and infectious diseases. However, accurate assessment and real-time monitoring of the efficacy of both traditional Chinese and Mongolian medicines, as well as Western medicine, remains a challenge in clinical practice.

[0003] Traditionally, the assessment of drug efficacy has relied primarily on changes in patient symptoms, physical signs, and laboratory test results. These methods are often lagging and cannot reflect the dynamic changes of drugs in the body in real time. This is especially true for traditional Chinese and Mongolian medicines, whose complex components and diverse mechanisms of action make it difficult for traditional assessment methods to accurately quantify their efficacy, let alone provide personalized medication guidance. Furthermore, the metabolic process of drugs in the body is influenced by various factors, such as individual differences, drug interactions, and changes in physiological state, making the prediction and monitoring of drug efficacy even more challenging.

[0004] Various types of biological signals exist in living organisms, such as electrochemical signals and piezoelectric signals. These signals reflect the metabolic process of drugs in vivo from different perspectives. However, existing methods often use simple weighted averaging or superposition when fusing these multimodal signals, failing to fully consider the temporal correlation and dynamic changes between signals. This results in low-quality fused signals that cannot accurately reflect the true state of drugs in vivo.

[0005] Current methods for assessing drug efficacy often consider only the single parameter of drug concentration, failing to adequately account for factors such as drug type, mechanism of action, and individual patient differences. This is particularly true for traditional Chinese and Mongolian medicines, whose complex compositions and diverse mechanisms of action mean that a single drug concentration parameter cannot accurately reflect their efficacy. Furthermore, existing methods often lack specificity in generating efficacy assessment parameters, failing to provide personalized medication guidance for different types of patients.

[0006] Current methods often fail to provide timely feedback to patients or clinicians after monitoring drug efficacy, and cannot adjust medication regimens in real time based on the monitoring results. This can lead to adverse reactions or poor efficacy in patients due to inappropriate medication, increasing treatment risks and costs.

[0007] Therefore, we propose a real-time monitoring method for the efficacy of traditional Chinese medicine, Mongolian medicine, and Western medicine based on biosensor technology to address the above-mentioned problems. Summary of the Invention

[0008] This invention provides a method for real-time monitoring of the efficacy of traditional Chinese, Mongolian and Western medicines based on biosensor technology, which can be used to realize real-time monitoring of drug efficacy and personalized medication guidance.

[0009] The first aspect of this invention provides a method for real-time monitoring of the efficacy of traditional Chinese medicine, Mongolian medicine, and Western medicine based on biosensor technology. The method includes: collecting real-time multimodal biosignals from the patient's body surface or minimally invasive body fluid samples to obtain raw sensor signals; processing the raw sensor signals to generate a fused biodynamic response signal, and using this fused biodynamic response signal to dynamically calibrate the raw sensor signals to obtain sensor array output; extracting real-time pharmacokinetic characteristic signals from the sensor array output based on a preset pharmacokinetic model; mapping the pharmacokinetic characteristic signals to efficacy evaluation parameters according to the type of drug being monitored; comparing the efficacy evaluation parameters with a preset safe and effective concentration range to generate real-time medication status indications and dosage adjustment prompts.

[0010] Optionally, in a first implementation of the first aspect of the present invention, the method includes: extracting dynamic change characteristics of the electrochemical current signal and dynamic response characteristics of the piezoelectric frequency signal from the original sensing signal; constructing a time-varying fusion weight coefficient based on the temporal correlation between the dynamic change characteristics and the dynamic response characteristics, and using the fusion weight coefficient to fuse the electrochemical current signal and the piezoelectric frequency signal to generate a fused biological dynamic response signal; monitoring the stability index of the fused biological dynamic response signal in real time, and generating dynamic calibration parameters based on the stability index; and using the dynamic calibration parameters to perform real-time compensation and correction on the electrochemical current signal in the original sensing signal to obtain the sensor array output.

[0011] Optionally, in a second implementation of the first aspect of the present invention, the real-time monitoring of the stability index of the dynamic response signal of the fusion organism and the generation of dynamic calibration parameters based on the stability index includes: performing volatility analysis on the dynamic response signal of the fusion organism within a preset time window to generate an instantaneous stability index characterizing the short-term stability of the signal; extracting the long-term baseline trend of the dynamic response signal of the fusion organism from historical monitoring data to generate a baseline offset characterizing the long-term drift of the signal; generating a comprehensive dynamic calibration factor based on a weighted combination of the instantaneous stability index and the baseline offset; and performing calculations on the comprehensive dynamic calibration factor and a preset basic calibration matrix to generate dynamic calibration parameters.

[0012] Optionally, in a third implementation of the first aspect of the present invention, the method includes: extracting target concentration data and rate of change data corresponding to the current drug type from the pharmacokinetic characteristic signal according to a preset drug type identifier; for Western medicine, comparing the target concentration data with a preset minimum effective concentration threshold and a minimum toxic concentration threshold to generate quantified Western medicine efficacy evaluation parameters; for traditional Chinese medicine, performing weighted fusion calculation on the target concentration data based on a preset multi-component synergistic effect weight table to generate quantified traditional Chinese medicine compound synergistic efficacy evaluation parameters; for Mongolian medicine, combining the target concentration data and rate of change data, and referring to a preset mineral element metabolism baseline to generate quantified Mongolian medicine steady-state efficacy evaluation parameters; and uniformly converting the generated quantified efficacy evaluation parameters into a standardized efficacy index as efficacy evaluation parameters.

[0013] Optionally, in the fourth implementation of the first aspect of the present invention, the step of weighting and fusion calculation of the target concentration data based on a preset weighted table of synergistic effects of multiple components to generate quantitative evaluation parameters for the synergistic efficacy of traditional Chinese medicine compound includes: selecting multiple component concentrations belonging to the same compound from the target concentration data according to pre-stored component identifiers of traditional Chinese medicine compound, forming a compound component concentration set; querying the preset weighted table of synergistic effects to obtain standardized weight values ​​corresponding to each component in the compound component concentration set; calculating the synergistic effect strength parameter based on the concentration of each component and its corresponding standardized weight value, as well as the predefined synergistic or antagonistic relationship between components; and synthesizing the synergistic effect strength parameter with the preset baseline efficacy value of the traditional Chinese medicine compound to generate a synergistic efficacy index.

[0014] Optionally, in the fifth implementation of the first aspect of the present invention, the method includes: comparing the efficacy evaluation parameters with a pre-stored safe and effective concentration range in real time to generate an efficacy status code characterizing the current efficacy status; querying a preset dose adjustment rule table based on the efficacy status code and the concentration change rate parameter in the pharmacokinetic characteristic signal to generate a dose adjustment suggestion; combining the efficacy status code and the dose adjustment suggestion to generate a medication guidance report; and transmitting the medication guidance report in real time to the user or clinical monitoring terminal in visual, auditory, or data form through a preset feedback interface to guide the immediate adjustment of the medication regimen.

[0015] Optionally, in a sixth implementation of the first aspect of the invention, the recommended adjustment percentage for the current dose is set to... :

[0016] ;

[0017] in: The sensitivity coefficient for therapeutic effect gain; This is the inertial damping coefficient; For prediction time windows; For reference steady-state concentration; For standardized efficacy index; The preset optimal therapeutic target value; This is the concentration change rate parameter.

[0018] Optionally, in the seventh implementation of the first aspect of the present invention, the method further includes: at a preset time point before or during real-time monitoring, introducing a reference sample of known concentration into the synchronous multimodal sensing interface and acquiring its corresponding reference signal; comparing the reference signal with a pre-stored standard signal of the reference sample to generate a system accuracy verification result; when the system accuracy verification result exceeds a preset allowable deviation range, triggering a system calibration process and generating a calibration compensation coefficient based on the difference between the reference signal and the standard signal.

[0019] Optionally, in the eighth implementation of the first aspect of the present invention, the step of triggering a system calibration process when the system accuracy verification result exceeds a preset allowable deviation range, and generating a calibration compensation coefficient based on the difference between the reference signal and the standard signal, includes: generating a system calibration trigger command based on the judgment of whether the system accuracy verification result exceeds the allowable deviation range; extracting electrochemical signal deviation and piezoelectric signal deviation from the reference signal in response to the system calibration trigger command; inputting the electrochemical signal deviation and piezoelectric signal deviation into a preset linear compensation algorithm respectively to calculate the electrochemical channel calibration coefficient and the piezoelectric channel calibration coefficient; and integrating the electrochemical channel calibration coefficient and the piezoelectric channel calibration coefficient to form a calibration compensation coefficient.

[0020] The mechanism of this invention is as follows: by constructing a hardware algorithm collaborative framework for synchronous acquisition and adaptive fusion calibration of multimodal biological signals, and combining classical pharmacokinetic models with a regularized mapping strategy based on prior pharmacological knowledge, real-time and accurate monitoring of the efficacy of traditional Chinese medicine, Mongolian medicine and Western medicine can be achieved.

[0021] Beneficial effects: Traditional Chinese and Mongolian medicines differ significantly from Western medicines in terms of components and mechanisms of action. Traditional efficacy assessment methods are difficult to meet diverse needs. This invention fully considers the characteristics of different drugs and designs targeted assessment methods for Western medicines, traditional Chinese medicines, and Mongolian medicines respectively, so as to realize personalized efficacy assessment, make the assessment results more consistent with the actual treatment situation, and help improve the treatment effect.

[0022] Traditional medication monitoring often lacks a real-time feedback mechanism, making it impossible to adjust medication regimens in a timely manner. This invention can generate and provide feedback on medication guidance reports in real time, enabling patients and clinicians to understand the efficacy status in a timely manner, adjust medication dosages according to recommendations, avoid adverse reactions or poor efficacy caused by improper medication, improve treatment safety and effectiveness, and reduce treatment costs.

[0023] Traditional Chinese medicine (TCM) compound formulas have complex components, and there are synergistic or antagonistic effects among the components. Traditional evaluation methods are difficult to accurately quantify this complex relationship. This invention, by comprehensively processing the concentration data of each component in the compound formula and considering the interactions between components, can more accurately evaluate the synergistic efficacy of TCM compound formulas and provide a scientific basis for the rational use of TCM in clinical practice. Attached Figure Description

[0024] Figure 1 This is a schematic diagram of an embodiment of the method for real-time monitoring of the efficacy of traditional Chinese, Mongolian and Western medicines based on biosensor technology in this invention.

[0025] Figure 2 This is a schematic diagram of another embodiment of the method for real-time monitoring of the efficacy of traditional Chinese and Mongolian medicines based on biosensor technology in this invention;

[0026] Figure 3 A schematic diagram illustrating the process of collecting and preprocessing samples from the patient's body surface or minimally invasive body fluids.

[0027] Figure 4 This is a schematic diagram of an embodiment of a real-time monitoring device for the efficacy of traditional Chinese, Mongolian and Western medicines based on biosensor technology, as described in this invention. Detailed Implementation

[0028] This invention provides a method for real-time monitoring of the efficacy of traditional Chinese medicine, Mongolian medicine, and Western medicine based on biosensor technology, for achieving real-time monitoring of drug efficacy and personalized medication guidance. The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. Furthermore, the terms "comprising" or "having" and any variations thereof are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0029] For ease of understanding, the specific process of the embodiments of the present invention is described below. Please refer to [link / reference]. Figure 1One embodiment of the method for real-time monitoring of the efficacy of traditional Chinese and Mongolian medicines based on biosensor technology in this invention includes:

[0030] 101. Real-time multimodal biological signals are collected from the patient's body surface or minimally invasive body fluid samples through a synchronous multimodal sensing interface to obtain the raw sensing signals;

[0031] It is understood that the executing entity of this invention can be a real-time monitoring device for the efficacy of traditional Chinese, Mongolian, and Western medicines based on biosensor technology, or it can be a terminal or a server; no specific limitation is made here. This embodiment of the invention will be described using a server as an example.

[0032] It should be noted that the patient is a diabetic who is taking Western medicine to lower blood sugar and needs to monitor the drug's effectiveness in real time. We used an integrated biosensor system, which includes a wearable surface sensor and a minimally invasive body fluid sampling module, to simultaneously acquire multimodal biosignals. The surface component uses a flexible patch sensor attached to the patient's wrist skin to acquire photoplethysmography (PPG) and skin temperature signals in real time. The minimally invasive component uses a miniature implantable sensor inserted through a fine needle into the subcutaneous tissue to continuously acquire glucose and drug metabolite concentrations in the interstitial fluid.

[0033] The data acquisition process begins immediately after medication administration. A surface sensor synchronously records PPG and skin temperature signals at a frequency of 100 sampling points per second. The PPG signal reflects changes in blood flow volume, while the skin temperature signal reflects surface thermal dynamics. A minimally invasive sensor collects data on glucose concentration and the concentration of the hypoglycemic drug (metformin) in the interstitial fluid every 30 seconds, with data transmitted in real-time via Bluetooth Low Energy.

[0034] Sixty minutes after medication administration, the raw sensor signals acquired by the system included: PPG signal: waveform amplitude approximately 0.5 volts, pulse rate calculated as 68 beats per minute, with slight motion artifacts mixed in. Skin temperature signal: stable at 36.5 degrees Celsius, with fluctuations within ±0.1 degrees Celsius. Interstitial fluid glucose concentration: reading 6.2 mmol / L. Interstitial fluid drug concentration: metformin concentration 1.8 μg / mL.

[0035] These signals, without any processing, are directly uploaded to the server in real time as raw sensor outputs in digital stream format. The raw data includes timestamps, sensor identifiers, and raw voltage or concentration values. For example, the PPG signal has a voltage of 0.48 volts at a given moment, the skin temperature sensor outputs 3600 millivolts corresponding to 36.0 degrees Celsius (through inherent sensor conversion), and the minimally invasive sensor outputs 12 nanoamps corresponding to the aforementioned concentration values. The entire acquisition process ensures low latency, typically completing the synchronous acquisition of multimodal signals within one second, providing a real-time, multidimensional biological dynamic data foundation for subsequent analysis.

[0036] 102. The original sensing signal is coupled and processed to generate a fused biological dynamic response signal. The original sensing signal is then dynamically calibrated using the fused biological dynamic response signal to obtain the output of the dynamically calibrated sensor array.

[0037] It should be noted that the implementation of this step will be explained in detail using the scenario of monitoring diabetic patients taking Western hypoglycemic drugs as an example.

[0038] The raw sensor signals received in step 101 include PPG voltage signal (amplitude 0.48 volts, corresponding to a pulse rate of 68 beats / minute), skin temperature signal (36.0 degrees Celsius), interstitial fluid glucose concentration (6.2 mmol / L), and metformin drug concentration (1.8 μg / mL). All signals are timestamped and updated every second.

[0039] The coupling process generates a fused biodynamic response signal: The original signals are preprocessed. The PPG signal is filtered to remove motion artifacts, and a stable amplitude of 0.48 volts is extracted. The temperature signal is used directly. Glucose and drug concentration signals are verified to be normal. Next, each signal is normalized to the range of 0 to 1. Based on the patient's individual baseline history, the PPG amplitude is normalized to 0.6, temperature to 0.5, glucose concentration to 0.7, and drug concentration to 0.4. Then, according to preset weights (PPG 30%, temperature 20%, glucose 30%, drug 20%), the fused biodynamic response signal is calculated, yielding a value of 0.55. This value comprehensively represents the overall intensity of the biodynamic response after medication.

[0040] Dynamic calibration was performed using the fusion biological dynamic response signal: Based on the fusion signal value of 0.55, the expected relationship between each original signal was analyzed. Under steady-state conditions, the fusion signal indicates that the PPG amplitude should be close to 0.5 volts, but the original value of 0.48 volts was slightly low due to minor interference, so it was calibrated to 0.5 volts. The temperature signal was consistent with the fusion signal and remained at 36.0 degrees Celsius without adjustment. The original glucose concentration value was 6.2 mmol / L, and based on the correlation between the fusion signal and drug concentration, it was calibrated to 6.1 mmol / L to eliminate minor sensor drift. The original drug concentration value was 1.8 μg / mL, and it was calibrated to 1.75 μg / mL to compensate for the delay effect of minimally invasive sampling.

[0041] The output of the dynamically calibrated sensor array is as follows: PPG amplitude 0.5 volts, skin temperature 36.0 degrees Celsius, glucose concentration 6.1 mmol / L, and drug concentration 1.75 μg / mL.

[0042] 103. Based on a pre-set pharmacokinetic model, extract real-time pharmacokinetic characteristic signals from the dynamically calibrated sensor array output;

[0043] It should be noted that, based on a pre-defined pharmacokinetic model, real-time pharmacokinetic characteristic signals are extracted from the dynamically calibrated sensor array output. The following example, using the monitoring scenario of a diabetic patient taking the Western medicine metformin, illustrates the implementation of this step.

[0044] The sensor array output after dynamic calibration in step 102 is received, namely PPG amplitude 0.5 volts, skin temperature 36.0 degrees Celsius, interstitial fluid glucose concentration 6.1 mmol / L, and interstitial fluid metformin concentration 1.75 μg / mL.

[0045] The pre-defined pharmacokinetic model for metformin is invoked. This model is a mathematical framework that includes parameters for absorption, distribution, metabolism, and excretion. Its core is to establish the dynamic relationship between drug concentration in the blood (or interstitial fluid) and time and physiological state. The model has been pre-trained based on a large amount of clinical data, and its parameters include the drug's apparent volume of distribution, clearance rate constant, etc.

[0046] Real-time input data is fed into the model to drive calculations and extract key pharmacokinetic characteristic signals. Specifically, using a calibrated interstitial fluid drug concentration of 1.75 μg / mL as the direct observation point, and combining this with the time point 60 minutes after administration, the model estimates the current blood drug concentration trend value at 1.6 μg / mL. Simultaneously, using the drug concentration sequence from the current and previous time points, the model calculates and outputs the real-time rate of drug ascent in vivo at 0.8 μg / mL per hour, reflecting the overall state of absorption and distribution. The model also estimates the current drug half-life (2.5 hours) and apparent drug clearance (0.15 liters per hour) based on the concentration-time curve.

[0047] Integrating other calibrated biological signals to optimize feature extraction, heart rate (68 beats / minute) and skin temperature (36.0 degrees Celsius) reflected by PPG signals were used as physiological state parameters for dynamic fine-tuning of model parameters such as volume of distribution, making them more closely reflect the current individual state of the user. Interstitial fluid glucose concentration of 6.1 mmol / L was also used by the model as a co-observation indicator of drug efficacy and was used to cross-validate the rationality of the drug metabolism process.

[0048] The real-time pharmacokinetic characteristic signals output include: estimated real-time blood drug concentration of 1.6 μg / mL, drug concentration rise rate of 0.8 μg / mL per hour, current drug half-life of 2.5 hours, and apparent clearance of 0.15 L / h. This set of characteristic signals quantitatively characterizes the "fingerprint" of the drug's real-time dynamic process in the patient's body.

[0049] 104. Based on the type of drug being monitored, pharmacokinetic characteristic signals are mapped into efficacy evaluation parameters; for Western medicine, the mapping is based on the known relationship between blood drug concentration and efficacy; for traditional Chinese medicine, the mapping is based on the synergistic effect of the concentrations of multiple components in the compound; for Mongolian medicine, the mapping is based on the concentration levels and trends of characteristic mineral element ions.

[0050] It should be noted that the real-time pharmacokinetic characteristic signals extracted in step 103 are received, including the estimated real-time blood drug concentration of 1.6 μg / mL, the rate of increase in drug concentration of 0.8 μg / mL per hour, the current drug half-life of 2.5 hours, and the apparent clearance of 0.15 L / h. The goal of step 104 is to convert these characteristic signals into intuitive efficacy assessment parameters for subsequent judgment.

[0051] The mapping process relies on a pre-defined database that stores the known relationship between metformin plasma concentration and therapeutic efficacy. This database, based on clinical studies, defines an effective plasma concentration range of 0.5 to 2.5 μg / mL, an optimal therapeutic concentration of 1.8 μg / mL, and includes normal pharmacokinetic parameters: a rate of ascent of 0.1 to 0.3 μg / mL per hour, a half-life of 2 to 3 hours, and a clearance of 0.1 to 0.2 L / mL.

[0052] Real-time feature signals are compared and analyzed against these preset ranges, and efficacy assessment parameters are generated through rule-based mapping. The mapping does not involve complex formulas but is based on thresholds and logical judgments. The specific mapping results are shown in Table 1 below:

[0053] Table 1

[0054]

[0055] The above parameters are combined to generate an overall efficacy assessment parameter called the "immediate efficacy score". The calculation method is a weighted average, in which the concentration efficacy index has the highest weight. Based on the concentration efficacy index of 85, normal absorption status (converted to 100), normal metabolism status (converted to 100), and normal clearance status (converted to 100), the weighted average yields an immediate efficacy score of 88, ranging from 0 to 100. The higher the score, the better the efficacy.

[0056] Efficacy assessment parameters include specific concentration-efficacy indices, absorption status, metabolic status, clearance status, and a comprehensive immediate efficacy score. These parameters quantify the drug's efficacy at the current moment.

[0057] 105. Compare the efficacy assessment parameters with the preset safe and effective concentration range, generate real-time medication status indications and dosage adjustment prompts, and feed this information back to the user or clinical monitoring terminal.

[0058] It should be noted that the efficacy assessment parameters received in step 104 include the concentration-efficacy index 85, normal absorption status, normal metabolic status, normal clearance status, and the immediate efficacy score 88. These parameters are obtained based on pharmacokinetic characteristic signal mapping and are used to assess the current drug efficacy.

[0059] The pre-defined safe and effective ranges for metformin and the individual patient are invoked. These ranges are derived from clinical guidelines and patient history data, specifically: the safe and effective range for the concentration-efficacy index is 70 to 100, with 90 to 100 being the optimal therapeutic range; absorption, metabolism, and clearance status must all be "normal" to indicate safety; the effective range for the immediate efficacy score is 70 to 100, with an optimal range of 90 to 100. Furthermore, the direct safe range for plasma concentration is 0.5 to 2.5 μg / mL, and the optimal therapeutic concentration is 1.8 μg / mL (based on the real-time estimated plasma concentration of 1.6 μg / mL from step 103).

[0060] The efficacy assessment parameters were compared one by one with these preset ranges: Concentration-efficacy index 85: higher than the effective lower limit 70, but lower than the optimal lower limit 90, indicating sufficient efficacy but not optimal. Absorption, metabolism, and clearance status: all normal, meeting safety requirements. Immediate efficacy score 88: higher than the effective lower limit 70, but lower than the optimal lower limit 90, consistent with the concentration-efficacy index. Real-time estimated blood drug concentration 1.6 μg / mL: within the safe range of 0.5 to 2.5, but lower than the optimal therapeutic concentration of 1.8 μg / mL.

[0061] Based on the comparison results, a medication status indicator is generated. Since all parameters are within the safe and effective range, but not optimal, the status indicator is set as "Good efficacy, room for optimization." Simultaneously, a dosage adjustment suggestion is generated: considering that the blood drug concentration and efficacy score are slightly below optimal, but the status is normal and there is no risk, the suggestion is "It is recommended to maintain the current dosage. Consider discussing a slight increase with your doctor at the next visit to optimize efficacy; no immediate adjustment is needed at this time."

[0062] This information is fed back to the patient or clinical monitoring unit in real time. The message is pushed to the patient's smartphone app via an encrypted network, displaying: "Current medication status: Good efficacy, room for optimization. Dosage reminder: Maintain the current dosage; consult your doctor at the next follow-up visit. Real-time blood drug concentration is 1.6 micrograms / ml, within the safe range." Simultaneously, the same information is sent to the doctor's workstation at the clinical monitoring unit for medical staff to view.

[0063] Please see Figure 2 and Figure 3 Another embodiment of the method for real-time monitoring of the efficacy of traditional Chinese and Mongolian medicines based on biosensor technology in this invention includes:

[0064] 201. Real-time multimodal biological signals are collected from the patient's body surface or minimally invasive body fluid samples through a synchronous multimodal sensing interface to obtain the raw sensing signals;

[0065] Specifically, the electrochemical sensing unit and the piezoelectric sensing unit are activated simultaneously to acquire real-time current signals characterizing the oxidation-reduction process of the target substance in the body fluid sample, and real-time frequency shift signals characterizing the change in sensor surface quality, respectively. The real-time current signals are denoised and baseline corrected to generate a first optimized signal, while the real-time frequency shift signals are temperature compensated to generate a second optimized signal. Based on a unified timestamp, the first optimized signal and the second optimized signal are aligned and merged to form the original sensing signal.

[0066] It should be noted that this describes the process of collecting and preprocessing bodily fluid drug signals from a patient taking a "combined Chinese and Western medicine hypoglycemic compound (containing metformin and berberine)".

[0067] A microneedle patch integrating an electrochemical electrode and a quartz crystal microbalance (QCM) piezoelectric component was applied to the patient's upper arm. The system sampling frequency was set to 10Hz. The current time is the 10th minute of the monitoring cycle, and the system needs to complete a full multimodal signal acquisition, optimization, and alignment encapsulation.

[0068] The initial multimodal signal acquisition was triggered by the system clock, and the sensing interface was simultaneously activated. The electrochemical unit applied a 0.65-volt working potential to the microneedle working electrode to initiate the redox reaction of metformin and berberine metabolites in the body fluid. The acquired raw current signal at this time contained high-frequency electronic noise and was displayed as 67.5 nanoamps (nA). The piezoelectric sensing unit drove the piezoelectric crystal to oscillate; due to the adsorption of drug molecules on the sensor surface, the mass increased, and the oscillation frequency decreased. The acquired raw frequency signal at this time was 9,985,020 Hz. Simultaneously, the integrated temperature sensor read 37.2 degrees Celsius.

[0069] The first optimized signal (electrochemical path) is generated by filtering the original current of 67.5 nA using a five-point moving average to remove jitter noise and obtain a smoothed value of 67.0 nA. Next, the system reads the pre-stored baseline current value of the drug-free blank body fluid (40.0 nA) and performs a baseline correction operation (i.e., subtracting the baseline value from the smoothed value) to generate the first optimized signal reflecting the true oxidation level of the drug: 27.0 nA.

[0070] Generating a second optimized signal (piezoelectric path): The system detects that the current temperature (37.2 degrees Celsius) is higher than the standard calibration temperature (37.0 degrees Celsius). Based on the crystal's temperature-frequency drift coefficient (0.1 degree Celsius increase results in a -5 Hz drift), the frequency deviation caused by temperature is calculated to be -10 Hz. To eliminate temperature interference, the system performs reverse compensation on the original frequency, generating a second optimized signal that only reflects the quality change: 9,985,030 Hz.

[0071] A unified timestamp (2024-05-2009:10:00.050) is generated, and the processed current and frequency data are locked in the same data frame to form the original sensing signal packet that can be called by subsequent algorithms.

[0072] Table 2 below visually illustrates the data transformation process from initial acquisition to the final formation of the original sensor signal:

[0073] Table 2

[0074]

[0075] Through the above steps, the system successfully eliminated the interference of environmental noise and body temperature fluctuations on the sensor, and output a set of original sensing signals with high signal-to-noise ratio and strict time alignment.

[0076] 202. The original sensing signal is coupled and processed to generate a fused biological dynamic response signal. The original sensing signal is then dynamically calibrated using the fused biological dynamic response signal to obtain the output of the dynamically calibrated sensor array.

[0077] Specifically, the dynamic change characteristics of the electrochemical current signal and the dynamic response characteristics of the piezoelectric frequency signal are extracted from the original sensing signal. Based on the temporal correlation between the dynamic change characteristics and the dynamic response characteristics, a time-varying fusion weight coefficient is constructed, and the electrochemical current signal and the piezoelectric frequency signal are fused using this fusion weight coefficient to generate a fused biological dynamic response signal. The stability index of the fused biological dynamic response signal is monitored in real time, and dynamic calibration parameters are generated based on the stability index. The electrochemical current signal in the original sensing signal is compensated and corrected in real time using the dynamic calibration parameters to obtain the dynamically calibrated sensor array output.

[0078] Furthermore, the stability index of the dynamic response signal of the fusion organism is monitored in real time, and dynamic calibration parameters are generated based on the stability index. This includes: performing volatility analysis on the dynamic response signal of the fusion organism within a preset time window to generate an instantaneous stability index characterizing the short-term stability of the signal; extracting the long-term baseline trend of the dynamic response signal of the fusion organism from historical monitoring data to generate a baseline offset characterizing the long-term drift of the signal; generating a comprehensive dynamic calibration factor based on a weighted combination of the instantaneous stability index and the baseline offset; and performing calculations on the comprehensive dynamic calibration factor and a preset basic calibration matrix to generate dynamic calibration parameters for real-time signal compensation and correction.

[0079] It should be noted that the piezoelectric signal (reflecting changes in physical mass) is used to correct the electrochemical signal (reflecting biochemical concentration), thus eliminating signal drift caused by non-specific adsorption.

[0080] The time is at the 10th minute of the monitoring cycle. The input data are the first optimized signal (electrochemical current) of 27.0 nanoamps and the second optimized signal (piezoelectric frequency) of 9,985,030 Hz output from step 201. The system detected that although the drug concentration should theoretically remain stable, the electrochemical signal showed a slow upward trend, which is suspected to be due to baseline drift caused by biofilm fouling.

[0081] A 60-second data window was captured to extract the dynamic characteristics of the signal. Electrochemical characteristics: The calculated current change slope was an increase of 0.2 nanoamps per second, indicating a positive signal drift. Piezoelectric characteristics: The calculated frequency decay slope was a decrease of 3 Hz per second, indicating a continuous increase in the sensor surface mass (non-drug-specific protein adsorption). Correlation construction: System analysis revealed a high degree of synchronization between the two trends on the time axis, with a calculated Pearson correlation coefficient of 0.92. Based on this, a fusion weighting coefficient of 0.85 was constructed, implying that the change in physical mass has a significant impact on the current signal.

[0082] The two signals are fused to generate a dimensionless fused response signal, and dual analysis is performed: Instantaneous stability index: Within the current 5-second time window, the variance of the fused signal is analyzed, revealing minimal fluctuations, resulting in an instantaneous stability index of 0.98 (out of 1.0), indicating short-term signal smoothness. Baseline offset: Tracing back to the monitoring start point (0 minutes), the cumulative trend of the fused signal deviates from the preset zero-point baseline, and the equivalent current drift caused by cumulative non-specific adsorption is calculated to be 0.8 nanoamps.

[0083] The instantaneous stability index (0.98) and baseline offset (0.8 nanoamperes) are input into a weighted algorithm. Due to the high instantaneous stability, the system determines that the current drift is a systematic "long-term drift" rather than random noise. Therefore, the algorithm generates a negative comprehensive dynamic calibration factor, which, combined with the basic calibration matrix, finally outputs the dynamic calibration parameter for the current moment: -0.8 nanoamperes.

[0084] The final algebraic addition operation was performed, adding the dynamic calibration parameter (-0.8 nanoamps) to the original input electrochemical current (27.0 nanoamps). The calculation result was: 27.0 - 0.8 = 26.2 nanoamps. This decreased value eliminated false positive increments caused by protein adsorption and accurately reflected the effective concentrations of metformin and berberine in body fluids.

[0085] Table 3 below shows the changes in key parameters from the raw input to the final calibration output:

[0086] Table 3

[0087]

[0088] Through step 202, the system successfully identified and eliminated a systematic drift error of 0.8 nanoamps, ensuring the accuracy of subsequent efficacy evaluation.

[0089] 203. Based on the preset pharmacokinetic model, extract real-time pharmacokinetic characteristic signals from the dynamically calibrated sensor array output;

[0090] Specifically, the output of the dynamically calibrated sensor array is converted into concentration-time series data reflecting the real-time concentration of the target drug or its metabolites based on a pre-stored standard curve. The concentration-time series data is analyzed based on a preset one-compartment or two-compartment classical pharmacokinetic model, and the drug concentration change rate parameter describing the drug absorption and elimination process is calculated and output in real time. The real-time concentration-time series data and the drug concentration change rate parameter are synchronously integrated to generate pharmacokinetic characteristic signals for characterizing the dynamic process of the drug in vivo.

[0091] It should be noted that the current monitoring time point is 10 minutes after drug administration. The input data is the dynamically calibrated electrochemical current value of 26.2 nanoamps output from step 202. At this time, the drug is in the stage of rapid absorption by the body.

[0092] The system retrieves the standard response curve for metformin in subcutaneous interstitial fluid from its internal memory. This curve, pre-calibrated using extensive clinical data, demonstrates a highly linear relationship between current intensity and drug concentration. Substituting the input current value of 26.2 nanoamps into the standard curve algorithm, and after subtracting background noise, the system calculates the real-time concentration of metformin in the body fluid to be 0.55 mg / L. This value not only represents the physical quantity detected by the sensor but also directly reflects the instantaneous drug concentration in the target tissue.

[0093] The calculated real-time concentration (0.55 mg / L) is stored in a time-indexed circular data buffer, and the preset "one-compartment pharmacokinetic model" is activated for real-time calculation. The system reads back the concentration data from the previous monitoring time (i.e., the 9th minute), which is recorded as 0.51 mg / L. By comparing the current concentration data with the previous time, the model calculates the concentration increment per minute to be 0.04 mg / L. Based on the one-compartment model logic, the system identifies that the current concentration change slope is positive and relatively large, determining that the drug is in the "rapid absorption phase." The system then calculates the current drug concentration change rate parameter as +0.04 mg / L / min. This parameter is crucial for predicting when the drug will reach its peak concentration (Cmax).

[0094] Perform a synchronization and integration operation to encapsulate the static "real-time concentration data" (0.55 mg / L), the dynamic "rate of change parameter" (+0.04 mg / L / min), and the "pharmacokinetic phase" (absorption phase) determined by the model.

[0095] Output a set of structured pharmacokinetic characteristic signals. The core information contained in this signal packet clearly indicates that the current metformin concentration in the patient is 0.55 mg / L and is continuously increasing at a rate of 0.04 mg / L per minute.

[0096] 204. Based on the type of drug being monitored, pharmacokinetic characteristic signals are mapped into efficacy evaluation parameters; for Western medicine, the mapping is based on the known relationship between blood drug concentration and efficacy; for traditional Chinese medicine, the mapping is based on the synergistic effect of the concentrations of multiple components in the compound; for Mongolian medicine, the mapping is based on the concentration levels and trends of characteristic mineral element ions.

[0097] Specifically, based on a preset drug type identifier, target concentration data and rate of change data corresponding to the current drug type are extracted from pharmacokinetic characteristic signals. For Western medicine, the target concentration data is compared with preset minimum effective concentration thresholds and minimum toxic concentration thresholds to generate quantitative Western medicine efficacy evaluation parameters. For traditional Chinese medicine, based on a preset weighted table of synergistic effects of multiple components, the target concentration data is weighted and fused to generate quantitative traditional Chinese medicine compound synergistic efficacy evaluation parameters. For Mongolian medicine, the target concentration data and rate of change data are combined, and a preset mineral element metabolism baseline is referenced to generate quantitative Mongolian medicine steady-state efficacy evaluation parameters. The generated quantitative efficacy evaluation parameters are uniformly converted into standardized efficacy indices as efficacy evaluation parameters.

[0098] Furthermore, for traditional Chinese medicine (TCM), based on a pre-defined weighted table of synergistic effects of multiple components, the target concentration data is weighted and fused to generate quantitative TCM compound synergistic efficacy evaluation parameters. These parameters include: selecting multiple component concentrations belonging to the same compound from the target concentration data based on pre-stored TCM compound component identifiers to form a compound component concentration set; querying the pre-defined weighted table of synergistic effects to obtain standardized weight values ​​corresponding to each component in the compound component concentration set; calculating a synergistic effect strength parameter based on each component concentration, its corresponding standardized weight value, and predefined synergistic or antagonistic relationships between components; and combining the synergistic effect strength parameter with the pre-defined baseline efficacy value of the TCM compound to generate a standardized synergistic efficacy index as an evaluation parameter for the synergistic efficacy of the TCM compound.

[0099] It should be noted that the current time is 10 minutes after administration. The input data includes two parts: Western medicine characteristics: The real-time concentration of metformin output in step 203 is 0.55 mg / L, which is in the rising phase. Traditional Chinese medicine characteristics: The concentration of the key active ingredient "berberine" in the compound was monitored simultaneously at 0.52 mg / L, and the concentration of the auxiliary ingredient "palmatine" was 0.11 mg / L.

[0100] Based on the preset "integrated traditional Chinese and Western medicine blood sugar lowering program" label, the input pharmacokinetic characteristic signals are automatically diverted to two parallel processing channels: the Western medicine evaluation channel (for metformin) and the traditional Chinese medicine compound evaluation channel (for Coptis chinensis alkaloids).

[0101] The system calls upon the metformin efficacy threshold library. Threshold comparison: The real-time concentration (0.55 mg / L) is compared with the "minimum effective concentration threshold" (0.5 mg / L) and the "minimum toxic concentration threshold" (5.0 mg / L). Parameter generation: The data falls within the safe and effective range. The system calculates the relative position (percentile) of this concentration within the treatment window, determines that it is currently at the lower end of the optimal efficacy range (onset stage), and generates a quantitative evaluation parameter for the efficacy of the Western medicine with a score of 65 (out of 100, indicating effectiveness and extreme safety).

[0102] The evaluation of the synergistic efficacy of traditional Chinese medicine compound (berberine component) involves a specific "weighted fusion calculation": Component screening: The system identifies "berberine" and "palmatine" as belonging to the pre-stored "Coptis compound component set". Weight acquisition: The synergistic effect weight table is queried, and the standardized weight value of berberine is 0.8 (principal drug), and the standardized weight value of palmatine is 0.2 (assistant drug). Synergistic strength calculation: The weighted concentration sum is calculated as: (0.52 × 0.8) + (0.11 × 0.2) = 0.438. Next, the system reads the predefined relationship between the two as "synergistic effect", with a synergistic coefficient of 1.1. The synergistic effect strength parameter is obtained by performing the calculation: 0.438 × 1.1 = 0.4818. Baseline synthesis: The intensity parameter (0.4818) was compared with the "baseline efficacy value" (0.4000) of the compound to confirm that the current compound has reached the expected 120% activity level in vivo, and the quantitative evaluation parameter of the synergistic efficacy of the traditional Chinese medicine compound was 85 points.

[0103] The parameters for Western medicine (65 points) and traditional Chinese medicine (85 points) were normalized, and their geometric mean was calculated to output a unified standardized efficacy index of 75. This index clearly indicates that the current medication regimen produced a significant and safe combined efficacy at 10 minutes, with the synergistic effect of the traditional Chinese medicine components contributing significantly to the overall efficacy.

[0104] 205. Compare the efficacy assessment parameters with the preset safe and effective concentration range, generate real-time medication status indications and dosage adjustment prompts, and feed this information back to the user or clinical monitoring terminal.

[0105] Specifically, the efficacy assessment parameters are compared in real time with pre-stored safe and effective concentration ranges for specific drugs and individuals to generate a efficacy status code characterizing the current efficacy status. Based on the efficacy status code and the concentration change rate parameter in the pharmacokinetic characteristic signal, a preset dose adjustment rule table is queried to generate dose adjustment suggestions containing specific adjustment directions and amounts. Combining the efficacy status code and dose adjustment suggestions, a medication guidance report is generated. Through a preset feedback interface, the medication guidance report is transmitted in real time to the user or clinical monitoring end in visual, auditory, or data form to guide the immediate adjustment of the medication regimen.

[0106] It should be noted that the current time is 10 minutes after administration. Input data includes: Standardized Efficacy Index (E). actual : Set to 75.0 (because the concentration of 0.55 is in the early stage of efficacy, the index is slightly low, not reaching optimal efficacy but normal). Concentration change rate (V conc ): 0.04 mg / L / min. Preset target: The pre-set optimal therapeutic target value (E) for this patient's disease course. target The value is 95.0.

[0107] To accurately calculate whether and how much additional dose is needed, a predictive dose dynamic adjustment formula is introduced. This formula not only considers the current efficacy gap but also incorporates the momentum (rate) of drug concentration increase, preventing over-correction caused by the drug taking effect rapidly.

[0108] The formula is as follows:

[0109] ;

[0110] in:

[0111] : Recommended percentage adjustment of the current dose (positive value for addition, negative value for reduction).

[0112] The sensitivity coefficient for therapeutic effect gain was set to 1.2.

[0113] Inertial damping coefficient (to prevent overshoot), set to 0.8.

[0114] The prediction time window is set to 15 minutes.

[0115] The reference steady-state concentration is set at 1.5 mg / L.

[0116] Data substitution and calculation:

[0117] Treatment gap: 1.2 × (1 − 75.0 / 95.0) = 0.252;

[0118] Rate damping term: 0.8 × ((0.04 × 15) / 1.5) = 0.32;

[0119] Final calculation: (0.252−0.32)×100%=−6.8%;

[0120] Interpretation of Results: The calculated result is a slight negative value (-6.8%). This indicates that although the current therapeutic effect has not yet peaked, the drug absorption rate is normal and is predicted to rise steadily within the next 15 minutes. The system recommends maintaining the current dose without intervention. Risk Warning: A strong absorption trend has been detected, and the therapeutic index is expected to naturally exceed 95.0 in 15 minutes, posing a risk of borderline hypoglycemia.

[0121] The system accesses the patient's smart bracelet via Bluetooth: Visual feedback: A green icon (indicating good condition) is displayed on the screen, accompanied by a yellow "rising trend" arrow. Data transmission: The specific "estimated peak time: 10:25" is sent to the clinical monitoring terminal (doctor's tablet). Tactile feedback: The bracelet emits a short-long vibration pattern, indicating to the patient that no additional medication is needed and they should wait for the medication to reach its peak effect.

[0122] 206. Before starting real-time monitoring or at a preset time point during the monitoring process, a reference sample of known concentration is introduced into the synchronous multimodal sensing interface, and its corresponding reference signal is collected; the reference signal is compared with the pre-stored standard signal of the reference sample to generate a system accuracy verification result; when the system accuracy verification result exceeds the preset allowable deviation range, the system calibration process is triggered, and a calibration compensation coefficient is generated based on the difference between the reference signal and the standard signal; the calibration compensation coefficient is used to correct the original sensing signal or the output of the dynamically calibrated sensor array in subsequent steps to ensure the accuracy of the entire monitoring link.

[0123] Specifically, when the system accuracy verification result exceeds the preset allowable deviation range, the system calibration process is triggered, and calibration compensation coefficients are generated based on the difference between the reference signal and the standard signal. This includes: generating a system calibration trigger command based on whether the system accuracy verification result exceeds the allowable deviation range; in response to the system calibration trigger command, extracting the electrochemical signal deviation and piezoelectric signal deviation from the reference signal; inputting the electrochemical signal deviation and piezoelectric signal deviation into a preset linear compensation algorithm to calculate the electrochemical channel calibration coefficient and the piezoelectric channel calibration coefficient; and integrating the electrochemical channel calibration coefficient and the piezoelectric channel calibration coefficient to form a calibration compensation coefficient for correcting subsequent signals.

[0124] It should be noted that the current scenario is 8:00 AM, before the patient is about to take a new round of medication. The microneedle sensor patch has been worn for more than 24 hours. To prevent measurement errors caused by sensor aging, the system has automatically started a "daily self-calibration program".

[0125] The microfluidic module integrated within the patch is activated, releasing 5 μL of pre-stored "standard control solution" onto the sensor surface. This control solution contains metformin standard at a precise concentration of 5.0 mg / L, and its physical viscosity is consistent with human interstitial fluid. The standard solution concentration (5.0 mg / L) is set at a high concentration close to the toxicity threshold to verify the linearity of the sensor across the entire measurement range. Although the current measured concentration in the patient (0.55 mg / L) is in the lower range, this calibration effectively ensures measurement accuracy.

[0126] Signal acquisition under standard solution conditions: The measured electrochemical current was 235.0 nanoamps; the measured piezoelectric frequency offset was 98 Hz. Standard comparison: The system retrieved the factory standard parameters from its memory. For a concentration of 5.0 mg / L, the standard current should be 250.0 nanoamps, and the standard frequency offset should be 100 Hz. Deviation calculation: Electrochemical channel deviation: (235.0 - 250.0) / 250.0 = -6.0%. Piezoelectric channel deviation: (98 - 100) / 100 = -2.0%.

[0127] The built-in allowable deviation range is ±5%. The test results show that the electrochemical channel deviation (-6.0%) has exceeded the allowable range, indicating a decrease in sensor sensitivity (possibly due to slight passivation of the electrode surface). The system then generates a "system calibration trigger command".

[0128] The deviation data is input into the linear compensation algorithm: Electrochemical channel: Calculate the gain compensation coefficient. The target value of 250.0 divided by the measured value of 235.0 yields a coefficient of 1.0638. This means that all subsequent current readings need to be amplified by 6.38% to revert to the true value. Piezoelectric channel: Calculate the offset compensation coefficient. The target value of 100 minus the measured value of 98 yields an offset of +2 Hz. Integrated output: The system packages these two parameters into a new set of "calibration compensation coefficients (k=1.0638, b=+2)" and updates them in the register of the signal processing unit. In subsequent real-time monitoring, all raw data will be automatically multiplied or added to this coefficient for correction, thereby "pulling" the passive drift error back to the standard curve.

[0129] Table 4 below visually illustrates the signal differences and calibration parameter generation logic during this self-test process:

[0130] Table 4

[0131]

[0132] Through this step, the system successfully identified the decline in electrode sensitivity and automatically completed the mathematical repair, ensuring that subsequent collection of real patient body fluid data would not result in misjudgment due to sensor aging.

[0133] Figure 4 This is a schematic diagram of a real-time monitoring device for the efficacy of traditional Chinese medicine, Mongolian medicine, and Western medicine based on biosensor technology, provided in an embodiment of the present invention. The device 400 may include: a processor 401, a receiver 402, a transmitter 403, and a memory 404. The receiver 402, transmitter 403, and memory 404 are respectively connected to the processor 401 via a bus. It should be noted that in some possible implementations, the processor 401 and memory 404 may be integrated together.

[0134] The processor 401 includes one or more processing cores. The processor 401 executes the methods performed by the base station in the random access method provided in this application embodiment by running software programs and modules. The memory 404 can be used to store software programs and modules. Specifically, the memory 404 can store an operating system 4041 and at least one application module 4042 required for a function. The receiver 402 is used to receive communication data sent by other devices, and the transmitter 403 is used to send communication data to other devices.

[0135] The present invention also provides a real-time monitoring device for the efficacy of traditional Chinese medicine, Mongolian medicine and Western medicine based on biosensor technology. The real-time monitoring device for the efficacy of traditional Chinese medicine, Mongolian medicine and Western medicine based on biosensor technology includes a memory and a processor. The memory stores computer-readable instructions. When the computer-readable instructions are executed by the processor, the processor performs the steps of the real-time monitoring method for the efficacy of traditional Chinese medicine, Mongolian medicine and Western medicine based on biosensor technology in the above embodiments.

[0136] The present invention also provides a computer-readable storage medium, which can be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium, wherein the computer-readable storage medium stores instructions that, when the instructions are executed on a computer, cause the computer to perform the steps of the method for real-time monitoring of the efficacy of traditional Chinese and Mongolian medicines based on biosensor technology.

[0137] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0138] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0139] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for real-time monitoring of the efficacy of traditional Chinese, Mongolian, and Western medicines based on biosensor technology, characterized in that, include: Real-time multimodal biological signals are collected from the patient's body surface or minimally invasive body fluid samples to obtain raw sensing signals; The original sensing signal is processed to generate a fused biological dynamic response signal, and the original sensing signal is dynamically calibrated using this fused biological dynamic response signal to obtain the sensor array output, including: The dynamic change characteristics of the electrochemical current signal and the dynamic response characteristics of the piezoelectric frequency signal are extracted from the original sensing signal. Based on the temporal correlation between the dynamic change characteristics and the dynamic response characteristics, a time-varying fusion weighting coefficient is constructed, and the electrochemical current signal and the piezoelectric frequency signal are fused using the fusion weighting coefficient to generate a fused biological dynamic response signal. The stability index of the dynamic response signal of the fused organism is monitored in real time, and dynamic calibration parameters are generated based on the stability index. The electrochemical current signal in the original sensing signal is compensated and corrected in real time using the dynamic calibration parameters to obtain the sensor array output. Based on a preset pharmacokinetic model, real-time pharmacokinetic characteristic signals are extracted from the output of the sensor array. Based on the preset drug type identifier, target concentration data and rate of change data corresponding to the current drug type are extracted from the pharmacokinetic characteristic signal; For Western medicines, the target concentration data is compared with preset minimum effective concentration thresholds and minimum toxic concentration thresholds to generate quantitative Western medicine efficacy evaluation parameters. For traditional Chinese medicine, based on a preset weighted table of synergistic effects of multiple components, the target concentration data is weighted and fused to generate quantitative parameters for evaluating the synergistic efficacy of traditional Chinese medicine compound prescriptions. For Mongolian medicine, the target concentration data and change rate data are combined, and a preset mineral element metabolism baseline is referenced to generate quantitative steady-state efficacy evaluation parameters for Mongolian medicine. The generated quantitative efficacy assessment parameters are uniformly converted into standardized efficacy indices and used as efficacy assessment parameters. The efficacy evaluation parameters are compared with the pre-stored safe and effective concentration range in real time to generate a efficacy status code that represents the current efficacy status. Based on the therapeutic status code and the concentration change rate parameter in the pharmacokinetic characteristic signal, a preset dose adjustment rule table is queried to generate a dose adjustment suggestion, wherein the suggested adjustment percentage for the current dose is set to... : ； in: The sensitivity coefficient for therapeutic effect gain; This is the inertial damping coefficient; For prediction time windows; For reference steady-state concentration; For standardized efficacy index; The preset optimal therapeutic target value; This is a parameter representing the rate of concentration change. By combining the efficacy status code and the dosage adjustment recommendations, a medication guidance report is generated; Through a preset feedback interface, the medication guidance report is transmitted in real time to the user or clinical monitoring terminal in the form of visual, auditory or data, so as to guide the immediate adjustment of the medication plan.

2. The method for real-time monitoring of the efficacy of traditional Chinese, Mongolian, and Western medicines based on biosensor technology according to claim 1, characterized in that, The real-time monitoring of the stability index of the dynamic response signal of the fusion organism, and the generation of dynamic calibration parameters based on the stability index, includes: Within a preset time window, the fusion biological dynamic response signal is subjected to fluctuation analysis to generate an instantaneous stability index characterizing the short-term stability of the signal. The long-term baseline trend of the fused biological dynamic response signal is extracted from historical monitoring data to generate a baseline offset characterizing the long-term drift of the signal. A comprehensive dynamic calibration factor is generated based on a weighted combination of the instantaneous stability index and the baseline offset. The integrated dynamic calibration factor is calculated with the preset basic calibration matrix to generate dynamic calibration parameters.

3. The method for real-time monitoring of the efficacy of traditional Chinese, Mongolian, and Western medicines based on biosensor technology according to claim 1, characterized in that, For traditional Chinese medicine, based on a preset weighted table of synergistic effects of multiple components, the target concentration data is weighted and fused to generate quantified parameters for evaluating the synergistic efficacy of traditional Chinese medicine compound prescriptions, including: Based on the pre-stored identifiers of Chinese herbal compound components, the concentrations of multiple components belonging to the same compound are screened from the target concentration data to form a compound component concentration set; Query the preset synergistic effect weight table to obtain the standardized weight values ​​corresponding to each component in the concentration set of the compound components; Based on the concentration of each component and its corresponding standardized weight value, as well as the predefined synergistic or antagonistic relationship between components, the synergistic effect strength parameter is calculated. The synergistic effect intensity parameter is synthesized with the preset baseline efficacy value of the traditional Chinese medicine compound to generate a synergistic efficacy index.

4. The method for real-time monitoring of the efficacy of traditional Chinese, Mongolian, and Western medicines based on biosensor technology according to claim 1, characterized in that, Also includes: Before real-time monitoring is initiated or at a preset time point during the monitoring process, a reference sample of known concentration is introduced into the synchronous multimodal sensing interface, and its corresponding reference signal is collected. The reference signal is compared with the pre-stored reference standard signal to generate a system accuracy verification result. When the system accuracy verification result exceeds the preset allowable deviation range, the system calibration process is triggered, and a calibration compensation coefficient is generated based on the difference between the reference signal and the standard signal.

5. The method for real-time monitoring of the efficacy of traditional Chinese medicine, Mongolian medicine, and Western medicine based on biosensor technology according to claim 4, characterized in that, When the system accuracy verification result exceeds the preset allowable deviation range, the system calibration process is triggered, and a calibration compensation coefficient is generated based on the difference between the reference signal and the standard signal, including: Based on the determination of whether the system accuracy verification result exceeds the allowable deviation range, a system calibration trigger command is generated; In response to the system calibration trigger command, the electrochemical signal deviation and piezoelectric signal deviation are extracted from the reference signal; The electrochemical signal deviation and the piezoelectric signal deviation are respectively input into a preset linear compensation algorithm to calculate the electrochemical channel calibration coefficient and the piezoelectric channel calibration coefficient. The electrochemical channel calibration coefficient and the piezoelectric channel calibration coefficient are integrated to form the calibration compensation coefficient.

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