A multi-mode dynamic calibration method and device for precise measurement of urine volume of an indwelling urinary catheter

Abstract

The application discloses a multi-mode dynamic calibration method and device for precise measurement of urine volume of a remaining urinary catheter, and relates to the technical field of medical measurement. The pressure signal data and the urine bag weight change data are input into a preset data merging algorithm to obtain a merged data group. The application solves the technical problems of insufficient measurement accuracy of a single sensor and lack of condition correction in the prior art, adopts a technical means combining double-sensor data merging and condition updating, and achieves the technical effects of improving urine volume measurement accuracy and realizing condition correction.

Description

Technical Field

[0001] This application relates to the field of medical measurement technology, and in particular to a multimodal dynamic calibration method and device for accurate measurement of urine volume in an indwelling urinary catheter. Background Technology

[0002] Currently, urine volume measurement using indwelling urinary catheters primarily employs single-sensor methods, such as the weight-based method using the urine bag and the pressure-based method using the tubing. Weight-based methods calculate urine volume by monitoring changes in the weight of the urine bag, providing a relatively stable measurement basis. Pressure-based methods estimate urine flow by detecting changes in pressure signals within the indwelling catheter, offering a fast response time. These single-modal measurement methods have played a crucial role in clinical applications, providing technical support for urine volume monitoring for healthcare professionals. However, single-sensor methods are susceptible to external interference factors, such as changes in patient position, urine bag movement, and tubing blockage, which can lead to data deviations. Furthermore, single-modal data lacks cross-validation, making it difficult to identify and correct systematic errors generated during measurement, thus affecting the accuracy and reliability of urine volume measurement.

[0003] Therefore, when using a single sensor to measure urine volume, the measurement data is easily affected by interference factors, and there is a lack of effective error identification and calibration methods, resulting in insufficient measurement accuracy and reliability. Summary of the Invention

[0004] In view of the aforementioned problems, this application is hereby filed.

[0005] Therefore, this application provides a multimodal dynamic calibration method and device for accurate measurement of urine volume in indwelling urinary catheters, which can solve the problems mentioned in the background art.

[0006] To solve the above-mentioned technical problems, this application provides the following technical solution:

[0007] In a first aspect, this application provides a multimodal dynamic calibration method for accurate measurement of urine volume in an indwelling urinary catheter, comprising: acquiring pressure signal data and urine bag weight change data in the indwelling urinary catheter through a pressure sensor and a weight sensor, respectively;

[0008] Based on the pressure signal data and the urine bag weight change data, comprehensive measurement data is generated through data integration and processing.

[0009] Calculate the deviation between the comprehensive measurement data and the preset reference value. If the deviation exceeds the preset deviation range, generate a calibration parameter set containing correction values. If the deviation is within the preset deviation range, maintain the current calibration parameter set.

[0010] The comprehensive measurement data is calibrated based on the correction values ​​in the calibration parameter set to obtain the target urine volume value.

[0011] Preferably, the step of generating comprehensive measurement data through data integration processing based on the pressure signal data and the urine bag weight change data includes:

[0012] The pressure signal data is filtered to obtain filtered pressure data;

[0013] Baseline correction is performed on the weight change data of the urine bag to obtain the corrected weight data;

[0014] The filtered pressure data and the corrected weight data are numerically synthesized according to a preset ratio to generate the comprehensive measurement data.

[0015] Preferably, the generation of the calibration parameter set containing the correction amount includes:

[0016] Based on the magnitude and direction of the deviation, determine the pressure correction and weight correction amounts;

[0017] Determine the compensation correction amount based on historical calibration records;

[0018] The pressure correction, weight correction, and compensation correction are combined to generate the calibration parameter set.

[0019] Preferably, determining the pressure correction and weight correction amounts based on the magnitude and direction of the deviation includes:

[0020] If the deviation is positive and greater than the first preset threshold, then the pressure correction amount is increased and the weight correction amount is decreased.

[0021] If the deviation is negative and its absolute value is greater than the second preset threshold, then the pressure correction amount is reduced and the weight correction amount is increased.

[0022] If the absolute value of the deviation is within the range of the first preset threshold and the second preset threshold, then the pressure correction amount and the weight correction amount are modified according to the preset adjustment range.

[0023] Preferably, calculating the deviation between the comprehensive measurement data and the preset benchmark value includes:

[0024] Obtain a reference urine volume value that matches the current measurement conditions from the standard urine volume database, and set the reference urine volume value as the preset benchmark value;

[0025] The difference between the comprehensive measurement data and the preset benchmark value is calculated to obtain the deviation.

[0026] Record the time stamp and measurement environment parameters of the deviation.

[0027] Preferably, before acquiring pressure signal data within the indwelling urinary catheter and weight change data of the urine bag via pressure and weight sensors respectively, the method further includes:

[0028] Zero-point calibration is performed on the pressure sensor and the weight sensor;

[0029] The operating status of the pressure sensor and the weight sensor is detected. If the operating status of the pressure sensor and the weight sensor is abnormal, a prompt signal is issued.

[0030] Set the data acquisition frequency and acquisition duration parameters.

[0031] Preferably, after calibrating the integrated measurement data according to the correction amount in the calibration parameter set, the method further includes:

[0032] The target urine volume value is compared and verified with a preset reasonable range;

[0033] If the target urine volume value exceeds the preset reasonable range, it is marked as abnormal data and the calibration process is re-executed;

[0034] If the target urine volume value is within the preset reasonable range, then the target urine volume value and the corresponding calibration record are stored.

[0035] Secondly, this application also provides a multimodal dynamic calibration device for accurate measurement of urine volume in an indwelling urinary catheter, comprising: a data acquisition module for acquiring pressure signal data and urine bag weight change data in the indwelling urinary catheter through a pressure sensor and a weight sensor, respectively;

[0036] The data processing module is used to generate comprehensive measurement data by integrating and processing the pressure signal data and the weight change data of the urine bag.

[0037] The deviation detection module is used to calculate the deviation between the comprehensive measurement data and the preset reference value. If the deviation exceeds the preset deviation range, a calibration parameter set containing correction values ​​is generated. If the deviation is within the preset deviation range, the current calibration parameter set is maintained.

[0038] The calibration processing module is used to calibrate the comprehensive measurement data according to the correction amount in the calibration parameter group to obtain the target urine volume value.

[0039] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0040] Pressure signal data and urine bag weight change data in the indwelling urinary catheter are collected by pressure sensor and weight sensor, respectively.

[0041] Based on the pressure signal data and the urine bag weight change data, comprehensive measurement data is generated through data integration and processing.

[0042] Calculate the deviation between the comprehensive measurement data and the preset reference value. If the deviation exceeds the preset deviation range, generate a calibration parameter set containing correction values. If the deviation is within the preset deviation range, maintain the current calibration parameter set.

[0043] The comprehensive measurement data is calibrated based on the correction values ​​in the calibration parameter set to obtain the target urine volume value.

[0044] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0045] Pressure signal data and urine bag weight change data in the indwelling urinary catheter are collected by pressure sensor and weight sensor, respectively.

[0046] Based on the pressure signal data and the urine bag weight change data, comprehensive measurement data is generated through data integration and processing.

[0047] Calculate the deviation between the comprehensive measurement data and the preset reference value. If the deviation exceeds the preset deviation range, generate a calibration parameter set containing correction values. If the deviation is within the preset deviation range, maintain the current calibration parameter set.

[0048] The comprehensive measurement data is calibrated based on the correction values ​​in the calibration parameter set to obtain the target urine volume value.

[0049] Implementing this application has the following beneficial effects: This application provides a multimodal dynamic calibration method and device for accurate measurement of urine volume in indwelling urinary catheters. By acquiring data from both pressure and weight sensors in a dual-modal manner, a complementary measurement data source is constructed. The pressure signal reflects instantaneous flow changes, while the weight signal provides an accurate basis for cumulative volume. The combination of these two data sources overcomes the limitations of single-sensor measurement, improving the comprehensiveness and reliability of data acquisition. Data integration processing fuses measurement information from different physical quantities into comprehensive measurement data, eliminating the bias of a single data source and forming a more stable and accurate measurement basis. Deviation detection and calibration parameter generation establish the ability to actively identify and correct measurement errors. Through real-time comparison with preset benchmark values, measurement deviations can be detected promptly, and corresponding corrections can be generated, avoiding the impact of error accumulation on measurement results. Dynamic calibration processing makes targeted corrections to the measurement data based on actual deviations, achieving continuous maintenance of measurement accuracy and overcoming the technical limitation of traditional methods lacking self-calibration capabilities. Through the synergistic effect of multimodal data fusion and dynamic calibration, this application can maintain measurement accuracy and stability even in clinical environments, providing a reliable guarantee for monitoring urine volume in indwelling urinary catheters. Attached Figure Description

[0050] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0051] Figure 1 This is an overall flowchart of a multimodal dynamic calibration method for accurate measurement of urine volume in an indwelling urinary catheter, which is the subject of this application.

[0052] Figure 2 This is a schematic diagram of the overall structure of a multimodal dynamic calibration device for accurate measurement of urine volume in an indwelling urinary catheter, as described in this application.

[0053] Figure 3 This is a computer device diagram of a multimodal dynamic calibration method for accurate measurement of urine volume in an indwelling urinary catheter, which is the subject of this application. Detailed Implementation

[0054] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0055] Step 100: Collect pressure signal data and urine bag weight change data in the indwelling urinary catheter using pressure sensors and weight sensors, respectively.

[0056] Specifically, the pressure sensor is installed at a suitable location on the indwelling urinary catheter, typically about 10 centimeters above the connection between the catheter and the urine bag. The pressure sensor can monitor pressure changes within the tubing in real time. The weight sensor is located on the support device at the bottom of the urine bag and can continuously record changes in the total weight of the urine bag.

[0057] In practical applications, the pressure sensor's measurement range is typically set to 0 to 50 kPa with a measurement accuracy of 0.1 kPa, which meets the requirements for urine flow pressure detection. The weight sensor's measurement range is set to 0 to 2000 grams with a measurement accuracy of 1 gram, covering the commonly used urine bag capacity range in clinical practice. The data acquisition frequency is determined according to monitoring needs; for critically ill patients, it is usually set to once per second, while for patients under general monitoring, it can be set to once every 5 seconds.

[0058] Pressure signal data reflects the flow state and flow rate changes of urine in the catheter, with corresponding pressure pulsations occurring as urine flows through the catheter. Urine bag weight change data provides a direct measurement of urine accumulation; the weight increment directly corresponds to the newly generated urine volume. The two data sources are complementary: pressure data reflects instantaneous flow characteristics, while weight data provides an accurate basis for the accumulated amount.

[0059] Before acquiring pressure signal data within the indwelling urinary catheter and weight change data of the urine bag using pressure and weight sensors respectively, the method also includes sensor calibration and status detection processes:

[0060] Zero-point calibration is performed on both the pressure and weight sensors. Zero-point calibration is a crucial step to ensure measurement accuracy. The pressure sensor's zero-point calibration is performed at atmospheric pressure, adjusting the sensor output to the standard atmospheric pressure value of 101.325 kPa. The weight sensor's zero-point calibration is performed under no-load conditions to ensure that the weight reading in the empty urine bag state is the standard value of the urine bag's own weight. Zero-point calibration is typically performed automatically upon device startup and the calibration process lasts approximately 30 seconds.

[0061] The system monitors the operating status of the pressure and weight sensors. If either sensor malfunctions, an alert signal is issued. Operating status monitoring includes sensor responsiveness testing, signal stability verification, and measurement range confirmation. Pressure sensor status monitoring verifies sensor response by applying a standard pressure value, while weight sensor status monitoring verifies measurement accuracy by placing a standard weight. An abnormal operating status is determined when the sensor output signal exceeds the normal range, exhibits abnormal signal fluctuations, or shows no response.

[0062] Set the data acquisition frequency and duration parameters. The data acquisition frequency is determined based on the patient's monitoring level and clinical needs; the acquisition frequency for intensive care patients is set to 1 Hz, and for general patients, it is set to 0.2 Hz. The acquisition duration parameter is set according to the monitoring cycle, typically for continuous 24-hour acquisition. The data storage interval is set to save historical data every 5 minutes to ensure data security and traceability.

[0063] Step 200: Based on the pressure signal data and urine bag weight change data, generate comprehensive measurement data through data integration and processing.

[0064] Data integration and processing is the core of multimodal measurement methods. By preprocessing and fusing measurement data from different sources, more reliable comprehensive measurement results are formed.

[0065] Based on pressure signal data and urine bag weight change data, comprehensive measurement data is generated through data integration and processing, including three sub-steps:

[0066] The pressure signal data is filtered to obtain filtered pressure data. During the acquisition process, the pressure signal contains various noise interferences, including environmental vibrations, electrical interference, and electronic noise from the sensor itself. A digital low-pass filter algorithm is used, with a cutoff frequency set to 5 Hz, effectively removing high-frequency noise components. A Butterworth filter is selected as the filtering algorithm, with a filter order set to 4th order, to minimize noise impact while preserving the effective components of the signal. The filtered pressure data exhibits better stability and reliability.

[0067] Baseline correction is performed on the urine bag weight change data to obtain corrected weight data. Urine bag weight measurement is affected by factors such as the bag's own weight, temperature changes, and humidity. Baseline correction eliminates constant bias and slow drift by establishing a weight baseline. The baseline value is determined by analyzing the weight change trend over the past 15 minutes, using the least squares method to fit the baseline trend. When a significant linear drift in the weight data is detected, the baseline correction algorithm automatically adjusts the baseline value. The corrected weight data more accurately reflects the actual urine weight change.

[0068] Filtered pressure data and corrected weight data are numerically synthesized according to a preset ratio to generate comprehensive measurement data. The numerical synthesis employs a proportional allocation fusion method, assigning different weight values ​​to pressure and weight data. Under normal flow conditions, the weight data weight is set to 0.7, and the pressure data weight is set to 0.3, with weight data serving as the primary reference. Under low flow or intermittent flow conditions, the weight ratio is adjusted to 0.5 for weight data and 0.5 for pressure data, increasing the influence of the pressure signal. The comprehensive measurement data is obtained through weighted calculation using the following formula: the comprehensive measurement value equals the filtered pressure data multiplied by the pressure weight plus the corrected weight data multiplied by the weight weight.

[0069] Step 300: Calculate the deviation between the comprehensive measurement data and the preset reference value. If the deviation exceeds the preset deviation range, generate a calibration parameter set containing correction values. If the deviation is within the preset deviation range, maintain the current calibration parameter set.

[0070] Deviation detection and calibration parameter generation are crucial for ensuring measurement accuracy. By monitoring measurement deviations in real time and generating corresponding correction parameters, the reliability of measurement results can be guaranteed.

[0071] Calculate the deviation between the comprehensive measurement data and the preset benchmark value, including the benchmark value acquisition and deviation calculation process:

[0072] A reference urine volume value matching the current measurement conditions is obtained from a standard urine volume database and set as the preset baseline. The standard urine volume database contains normal urine volume ranges for patients of different ages, sexes, and health conditions. The normal urine volume range for adult men is 40 to 80 ml per hour, and for adult women it is 30 to 70 ml per hour. Reference values ​​for elderly patients and patients with special pathological conditions will be adjusted accordingly. The selection of the reference urine volume value considers the patient's basic information, the current time period, and the clinical context to ensure the rationality of the baseline value.

[0073] The deviation is calculated by comparing the aggregated measurement data with the preset benchmark value. The deviation is calculated using the absolute difference method; the deviation equals the absolute value of the aggregated measurement data minus the preset benchmark value. A positive deviation indicates that the measured value is higher than the benchmark value, while a negative deviation indicates that the measured value is lower than the benchmark value. The magnitude of the deviation reflects how close the current measurement result is to the standard reference value.

[0074] Record the time stamp of the deviation and the measurement environment parameters. The time stamp includes the specific moment and duration of the deviation detection, which facilitates tracking the trend of deviation changes. The measurement environment parameters include influencing factors such as ambient temperature, relative humidity, and atmospheric pressure. Recording the environmental parameters helps in analyzing the external causes of the deviation.

[0075] The preset deviation range is determined based on clinical accuracy requirements and is typically set to ±10% of the baseline value. For example, when the baseline value is 50 ml, the preset deviation range is 45 to 55 ml. This deviation range balances measurement accuracy and practicality; too small a range leads to frequent calibrations, while too large a range affects measurement accuracy.

[0076] Generate a set of calibration parameters containing corrections, including the process of determining corrections and combining parameters:

[0077] Based on the magnitude and direction of the deviation, pressure and weight corrections are determined. The determination of these corrections is based on deviation analysis and sensor characteristics. When the deviation primarily originates from pressure measurements, the pressure correction is set to 80% of the deviation, and the weight correction to 20%. When the deviation primarily originates from weight measurements, the weight correction is set to 80% of the deviation, and the pressure correction to 20%. This allocation of corrections ensures the relevance and effectiveness of the calibration.

[0078] The compensation correction amount is determined based on historical calibration records. This compensation correction amount is based on statistical analysis of past calibration data, identifying the periodicity and trend characteristics of measurement deviations to predict and compensate for potential future deviations. The historical data analysis period is typically the calibration records of the most recent 7 days, and the compensation correction amount is calculated using a moving average algorithm. When a significant deviation trend is detected, the compensation correction amount is increased accordingly, typically set at 5% to 15% of the reference deviation.

[0079] The pressure correction, weight correction, and compensation correction are combined to generate a calibration parameter set. The calibration parameter set organizes each correction parameter in a data structure, including the correction value, applicable conditions, and validity period. The generation of the calibration parameter set follows a priority principle: pressure and weight corrections have immediate effects, while compensation corrections serve as long-term trend corrections.

[0080] The specific rules for determining pressure and weight correction amounts based on the magnitude and direction of the deviation include:

[0081] If the deviation is positive and exceeds the first preset threshold, the pressure correction is increased and the weight correction is decreased. The first preset threshold is set according to the measurement accuracy requirements, typically 15% of the reference value. A positive deviation exceeding the first preset threshold indicates that the measured value is significantly higher than expected, possibly due to an oversensitive pressure sensor or a low reading from the weight sensor. The pressure correction is increased by 60% of the deviation, and the weight correction is decreased by 40% of the deviation.

[0082] If the deviation is negative and its absolute value exceeds the second preset threshold, the pressure correction is reduced and the weight correction is increased. The second preset threshold is equal to the first preset threshold to maintain calibration symmetry. A negative deviation exceeding the second preset threshold indicates that the measured value is significantly lower than expected, usually caused by insufficient sensitivity of the pressure sensor or an excessively high reading from the weight sensor. The correction is adjusted in the opposite direction to that for positive deviations to ensure calibration effectiveness.

[0083] If the absolute value of the deviation is within the range of the first and second preset thresholds, the pressure correction and weight correction are adjusted according to the preset adjustment range. The preset adjustment range is set to 30% of the deviation, which is relatively small to avoid over-calibration. When the deviation is within an acceptable range, calibration is mainly based on fine-tuning to maintain measurement stability.

[0084] Step 400: Calibrate the comprehensive measurement data according to the correction values ​​in the calibration parameter group to obtain the target urine volume value.

[0085] Calibration is the final step in the measurement process. It involves applying calibration parameters to correct the comprehensive measurement data and outputting accurate and reliable urine volume measurement results.

[0086] The calibration process employs an additive correction mode, where the target urine volume value equals the comprehensive measurement data plus the pressure correction, weight correction, and compensation correction. The correction calculation considers the cumulative effect and mutual influence of each correction to ensure the reasonableness of the calibration results. When multiple corrections are added in the same direction, the total correction does not exceed 25% of the comprehensive measurement data to prevent distortion caused by over-calibration.

[0087] The calibration process also includes outlier detection and boundary constraints. Outlier detection compares the changes in values ​​before and after calibration, triggering an alarm when the calibration correction exceeds a preset limit. Boundary constraints ensure that the target urine volume is within a physiologically reasonable range, typically with a lower limit of 0 ml and an upper limit determined based on the patient's condition and monitoring duration.

[0088] After calibrating the integrated measurement data according to the corrections in the calibration parameter set, the method also includes result verification and data management processes:

[0089] The target urine output was compared and validated against a pre-defined reasonable range. This range was determined based on clinical medical standards and individual patient characteristics; for normal adults, the reasonable range for hourly urine output is 30 to 100 ml. The upper and lower limits of this range were individually adjusted based on the patient's age, weight, disease state, and medication effects. Validation was performed by determining the numerical range to ensure the measurement results conformed to physiological principles.

[0090] If the target urine volume exceeds the preset reasonable range, it is marked as abnormal data and recalibration is performed. Abnormal data marking includes the time of exceedance, the magnitude of exceedance, and possible cause analysis. The recalibration process uses stricter calibration parameters and a more conservative correction margin; the adjustment range of the calibration parameters is reduced to 50% of the original range to avoid calibration oscillations.

[0091] If the target urine volume is within a preset reasonable range, the target urine volume and the corresponding calibration record are stored. Data storage uses a time-series database format, and the record includes measurement time, raw data, calibration parameters, target value, and quality identifier. Saving calibration records provides fundamental data support for subsequent data analysis and calibration parameter optimization.

[0092] The multimodal calibration method for urine volume measurement using indwelling urinary catheters provided in this embodiment establishes a complementary measurement data foundation through parallel data acquisition from pressure and weight sensors. Data integration and processing eliminates the limitations of a single data source, improving the reliability of measurement data. Deviation detection and calibration parameter generation establish proactive error identification and correction capabilities, ensuring the continuous maintenance of measurement accuracy. Calibration processing, through the synergistic effect of multiple correction parameters, achieves optimized output of measurement results. The overall technical solution maintains stable measurement performance even in complex clinical environments, providing reliable technical support for medical monitoring.

[0093] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0094] Based on the same inventive concept, this application also provides a multimodal dynamic calibration device for accurate measurement of urine volume in indwelling catheters. The solution provided by this system is similar to the solution described in the above method. Therefore, the specific limitations of one or more embodiments of the multimodal dynamic calibration device for accurate measurement of urine volume in indwelling catheters provided below can be found in the limitations of the multimodal dynamic calibration method for accurate measurement of urine volume in indwelling catheters described above, and will not be repeated here.

[0095] In one exemplary embodiment, such as Figure 2As shown, a multimodal dynamic calibration device for accurate measurement of urine volume in an indwelling urinary catheter is provided, comprising:

[0096] The data acquisition module is used to collect pressure signal data in the indwelling urinary catheter and weight change data of the urine bag through pressure sensors and weight sensors, respectively.

[0097] The data processing module is used to generate comprehensive measurement data by integrating and processing the pressure signal data and the weight change data of the urine bag.

[0098] The deviation detection module is used to calculate the deviation between the comprehensive measurement data and the preset reference value. If the deviation exceeds the preset deviation range, a calibration parameter set containing correction values ​​is generated. If the deviation is within the preset deviation range, the current calibration parameter set is maintained.

[0099] The calibration processing module is used to calibrate the comprehensive measurement data according to the correction amount in the calibration parameter group to obtain the target urine volume value.

[0100] Each module in the aforementioned multimodal dynamic calibration device for accurate urine volume measurement of indwelling urinary catheters can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0101] In one exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 3As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When executed by the processor, the computer program implements a multimodal dynamic calibration method for accurate measurement of urine volume in an indwelling urinary catheter. The display unit is used to form a visually visible image and can be a display screen, projection device, or virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0102] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0103] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0104] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps in the above method embodiments.

[0105] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0106] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0107] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0108] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0109] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A multimodal dynamic calibration method for accurate measurement of urine volume in an indwelling urinary catheter, characterized in that, include: Pressure signal data and urine bag weight change data in the indwelling urinary catheter are collected by pressure sensor and weight sensor, respectively. Based on the pressure signal data and the urine bag weight change data, comprehensive measurement data is generated through data integration processing, including: The pressure signal data is filtered to obtain filtered pressure data; Baseline correction is performed on the weight change data of the urine bag to obtain the corrected weight data; The filtered pressure data and the corrected weight data are numerically synthesized according to a preset ratio to generate the comprehensive measurement data. Calculate the deviation between the comprehensive measurement data and the preset benchmark value. If the deviation exceeds the preset deviation range, generate a calibration parameter set including correction values, including: Based on the magnitude and direction of the deviation, determine the pressure correction and weight correction amounts; Determine the compensation correction amount based on historical calibration records; The pressure correction, the weight correction, and the compensation correction are combined to generate the calibration parameter set; If the deviation is within the preset deviation range, then the current calibration parameter set is maintained; The comprehensive measurement data is calibrated based on the correction values ​​in the calibration parameter set to obtain the target urine volume value.

2. The multimodal dynamic calibration method for accurate measurement of urine volume in an indwelling urinary catheter as described in claim 1, characterized in that: The step of determining the pressure correction and weight correction based on the magnitude and direction of the deviation includes: If the deviation is positive and greater than the first preset threshold, then the pressure correction amount is increased and the weight correction amount is decreased. If the deviation is negative and its absolute value is greater than the second preset threshold, then the pressure correction amount is reduced and the weight correction amount is increased. If the absolute value of the deviation is within the range of the first preset threshold and the second preset threshold, then the pressure correction amount and the weight correction amount are modified according to the preset adjustment range.

3. The multimodal dynamic calibration method for accurate measurement of urine volume in an indwelling urinary catheter as described in claim 2, characterized in that: The calculation of the deviation between the comprehensive measurement data and the preset benchmark value includes: Obtain a reference urine volume value that matches the current measurement conditions from the standard urine volume database, and set the reference urine volume value as the preset benchmark value; The difference between the comprehensive measurement data and the preset benchmark value is calculated to obtain the deviation. Record the time stamp and measurement environment parameters of the deviation.

4. The multimodal dynamic calibration method for accurate measurement of urine volume in an indwelling urinary catheter as described in claim 3, characterized in that: Before acquiring pressure signal data within the indwelling urinary catheter and weight change data of the urine bag via pressure and weight sensors respectively, the method further includes: Zero-point calibration is performed on the pressure sensor and the weight sensor; The operating status of the pressure sensor and the weight sensor is detected. If the operating status of the pressure sensor and the weight sensor is abnormal, a prompt signal is issued. Set the data acquisition frequency and acquisition duration parameters.

5. The multimodal dynamic calibration method for accurate measurement of urine volume in an indwelling urinary catheter as described in claim 4, characterized in that: After calibrating the integrated measurement data according to the correction values ​​in the calibration parameter set, the method further includes: The target urine volume value is compared and verified with a preset reasonable range; If the target urine volume value exceeds the preset reasonable range, it is marked as abnormal data and the calibration process is re-executed; If the target urine volume value is within the preset reasonable range, then the target urine volume value and the corresponding calibration record are stored.

6. A multimodal dynamic calibration device for accurate measurement of urine volume in an indwelling urinary catheter, employing the multimodal dynamic calibration method for accurate measurement of urine volume in an indwelling urinary catheter as described in any one of claims 1 to 5, characterized in that, include: The data acquisition module is used to collect pressure signal data in the indwelling urinary catheter and weight change data of the urine bag through pressure sensors and weight sensors, respectively. The data processing module is used to generate comprehensive measurement data through data integration processing based on the pressure signal data and the urine bag weight change data, including: The pressure signal data is filtered to obtain filtered pressure data; Baseline correction is performed on the weight change data of the urine bag to obtain the corrected weight data; The filtered pressure data and the corrected weight data are numerically synthesized according to a preset ratio to generate the comprehensive measurement data. A deviation detection module is used to calculate the deviation between the comprehensive measurement data and a preset reference value. If the deviation exceeds a preset deviation range, a calibration parameter set including correction values ​​is generated. If the deviation is within the preset deviation range, the current calibration parameter set is maintained, including: Based on the magnitude and direction of the deviation, determine the pressure correction and weight correction amounts; Determine the compensation correction amount based on historical calibration records; The pressure correction, the weight correction, and the compensation correction are combined to generate the calibration parameter set; The calibration processing module is used to calibrate the comprehensive measurement data according to the correction amount in the calibration parameter group to obtain the target urine volume value.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the multimodal dynamic calibration method for accurate measurement of urine volume in an indwelling catheter as described in any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the multimodal dynamic calibration method for accurate measurement of urine volume in an indwelling catheter as described in any one of claims 1 to 5.

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