Portable bedside blood potassium detector

Abstract

The invention provides a portable bedside blood potassium detector, and relates to the technical field of blood potassium detection, and the portable bedside blood potassium detector comprises a collection module used for collecting finger blood and then conveying the finger blood to a disposable test piece through a test paper interface; the detection module is used for activating the power supply unit to supply power to the electrode of the disposable test piece and then outputting an electric signal; the signal processing module is used for receiving the electric signal and then outputting a digital signal after signal amplification and signal conversion; the synchronous acquisition module is used for synchronously activating an environment acquisition sensor to execute test environment acquisition and establishing a test environment data set when the detection module works; and the central processing unit is used for performing signal compensation on the digital signal after receiving the digital signal and the test environment data set, and establishing a test result. The technical problem that in the prior art, due to the fact that the influence of changes of environmental factors on the measurement result is not considered, the accuracy of the detection result is insufficient is solved, and the accuracy and reliability of blood potassium detection are improved.

Description

Technical Field

[0001] This application relates to the technical field of blood potassium detection, and particularly to a portable bedside blood potassium detector. Background Art

[0002] Blood potassium detection is an important indicator for evaluating the body's electrolyte balance and physiological functions. Traditional blood potassium detection methods mainly use venous blood analysis, which requires collecting venous blood and performing detection and analysis in a laboratory. The process is cumbersome and time-consuming. With the development of technology, portable blood potassium detection devices have gradually emerged. These detection devices usually use ion-selective electrode method (ISE) or microfluidic technology, etc., and use fingertip blood collection for detection. The operation is simple and the results can be obtained quickly. However, these methods are easily affected by environmental factors during the detection process, resulting in fluctuations in measurement results. For example, the ion-selective electrode method is easily interfered by factors such as temperature and humidity. Temperature changes will change the response characteristics of the electrode, resulting in deviations in measurement results; humidity changes may affect the stability of the electrode. The current portable blood potassium detection devices do not fully consider the interference caused by these environmental factors, making the measurement results have large fluctuations under different environmental conditions, affecting their accuracy and reliability in practical applications. Summary of the Invention

[0003] This application provides a portable bedside blood potassium detector, which solves the technical problem that the existing technology has deviations in detection results under different environments and insufficient accuracy due to the failure to consider the influence of environmental factor changes on measurement results, and achieves the technical effect of improving the accuracy and reliability of blood potassium detection. The blood potassium detector includes: a collection module, which is used to collect finger blood and then transport the finger blood to a disposable test strip through a test strip interface; a detection module, which is used to activate the power supply unit to supply power to the electrodes of the disposable test strip and then output an electrical signal; a signal processing module, which is used to receive the electrical signal, perform signal amplification and signal conversion through an A / D signal converter, and then output a digital signal; a synchronous collection module, which is used to synchronously activate an environmental collection sensor to perform test environment collection and establish a test environment data set when the detection module is working; a central processing unit, which is used to receive the digital signal and the test environment data set, perform signal compensation on the digital signal, and establish a test result. The signal compensation is to perform correction compensation on the digital signal according to the test environment data set.

[0004] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0005] After collecting finger blood through the collection module, the finger blood is transported to the disposable test strip through the test strip interface, ensuring the convenience and accuracy of sample collection. At the same time, the design of the disposable test strip avoids cross-contamination. After the detection module activates the power supply unit to supply power to the electrodes of the disposable test strip, a measurable electrical signal is generated through the reaction of the electrodes with potassium ions in the blood sample; the signal processing module receives the electrical signal output by the detection module and converts it into a digital signal through signal amplification and A / D conversion, ensuring the stability and processability of the signal and providing a basis for subsequent data analysis. When the detection module is working, the synchronous collection module synchronously activates the environmental collection sensor to establish a test environment data set, and provides data support for subsequent signal compensation by real-time monitoring of the detection environment (such as temperature, humidity, etc.). The central processing unit receives the digital signal and the test environment data set, corrects the digital signal according to the test environment data set, and establishes the final test result, thereby improving the accuracy and reliability of the detection result.

[0006] In summary, this application realizes convenient sample collection through the collection module. The detection module and the signal processing module ensure the stable output and accurate conversion of the detection signal. The addition of the synchronous collection module and the central processing unit enables the detection result to be corrected and compensated according to the test environment, thereby effectively improving the accuracy and reliability of the detection and realizing fast, convenient and high-precision blood potassium detection.

[0007] The above description is only an overview of the technical solution of this application. In order to be able to understand the technical means of this application more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of this application more obvious and understandable, the following specifically illustrates the specific implementation manners of this application. Brief Description of the Drawings

[0008] Figure 1 It is a structural schematic diagram of a portable bedside blood potassium detector provided by an embodiment of this application.

[0009] Figure 2 It is another structural schematic diagram of a portable bedside blood potassium detector provided by an embodiment of this application.

[0010] Description of the reference numerals: collection module 10, detection module 20, signal processing module 30, synchronous collection module 40, central processing unit 50, first self-checking and correction module 21, second self-checking and correction module 22, output module 23, signal amplification circuit 31, A / D signal converter 32, alarm module 61, communication module 62, display module 71, storage module 72, data interaction module 81, replacement module 82, cross-certification module 83, self-update module 90. Detailed Description of the Invention

[0011] The overall idea of the technical solution provided by this application is as follows:

[0012] By integrating core components such as the acquisition module 10, the detection module 20, the signal processing module 30, the synchronous acquisition module 40, and the central processor 50, during the detection process, the detection environment (such as temperature, humidity, etc.) is monitored in real time, and the detection signal is corrected and compensated according to these environmental data, thus effectively reducing the interference of environmental factors on the detection result and improving the accuracy and reliability of the detection.

[0013] After introducing the basic principle of this application, the various non-restrictive implementation manners of this application will be specifically introduced below in conjunction with the accompanying drawings of the specification.

[0014] As Figure 1 shown, the embodiment of this application provides a portable bedside potassium blood detector, and the potassium blood detector includes:

[0015] An acquisition module 10, which is used to collect finger blood and then transport the finger blood to a disposable test strip through a test strip interface.

[0016] Specifically, the test strip interface is a channel connecting the acquisition module 10 and the disposable test strip, which can enable the collected finger blood to reach the disposable test strip smoothly. After collecting finger blood through a blood collection needle or other collection devices, it flows through the test strip interface to the disposable test strip. There are special electrode materials on the disposable test strip, and these materials will react with potassium ions in the blood. The design of the acquisition module 10 ensures that the blood sample can be efficiently and accurately transmitted to the test strip, providing a sample source for subsequent potassium blood detection. Moreover, finger blood collection is convenient and causes little trauma, making it suitable for various scenarios such as bedside detection.

[0017] A detection module 20, which is used to activate the power supply unit to supply power to the electrodes of the disposable test strip and then output an electrical signal.

[0018] Specifically, the power supply unit is the part that provides electrical energy for the detection module 20. Common batteries or external power adapters, etc., can all be used as the power supply unit. When the acquisition module 10 collects a finger blood sample, the detection module 20 activates the power supply unit to supply power to the electrodes of the disposable test strip. After being powered on, the electrodes react with the finger blood sample sent from the acquisition module 10, thereby generating an electrical signal, and this signal can transmit the potassium blood-related information detected. Through the detection module 20, the potassium blood information in the blood sample can be obtained and converted into an electrical signal, providing a basic information source for subsequent signal processing and result analysis.

[0019] A signal processing module 30, which is used to receive the electrical signal and then output a digital signal after signal amplification and signal conversion by an A / D signal converter.

[0020] Specifically, the signal processing module 30 receives the electrical signals output by the detection module 20. These electrical signals are usually relatively weak. First, the signal amplification circuit 31 is used to amplify and enhance the weak electrical signals for subsequent processing. Then, the A / D signal converter 32 is used to convert the analog electrical signals into digital signals for output. Digital signals are discrete signals, representing information with only two states, 0 and 1, which are convenient for direct processing by a computer. Compared with analog signals, digital signals are more convenient for storage, transmission, and processing. By converting the electrical signals output by the detection module 20, which are not easy to process, into digital signals that are easy for the central processing unit 50 to recognize and process, the quality of the signals is improved, and important information in the digital signals is ensured not to be lost during subsequent processing.

[0021] The synchronous acquisition module 40 is used to synchronously activate the environmental acquisition sensors to perform test environment acquisition and establish a test environment data set when the detection module 20 is working.

[0022] Specifically, environmental factors (such as temperature changes, humidity, etc.) may affect the results of blood potassium tests. Therefore, it is necessary to synchronously acquire these environmental data. When the detection module 20 is working, the synchronous acquisition module 40 simultaneously activates the environmental acquisition sensors to start acquiring various data of the test environment, such as temperature, humidity, etc., and organizes these data into a test environment data set. Among them, the environmental acquisition sensors are devices used to acquire information related to the test environment. For example, a temperature sensor can acquire the environmental temperature, and a humidity sensor can acquire the environmental humidity, etc.; the test environment data set is a collection of various data about the test environment acquired by the environmental acquisition sensors, such as a collection of data such as temperature, humidity, and air pressure. By acquiring the test environment data through the synchronous acquisition module 40, it provides a data basis for the subsequent signal compensation by the central processing unit 50, so as to improve the accuracy of the detection results.

[0023] The central processing unit 50 is used to perform signal compensation on the digital signal and establish a test result after receiving the digital signal and the test environment data set. The signal compensation is to correct and compensate the digital signal according to the test environment data set.

[0024] Specifically, the central processing unit 50 receives the digital signals output by the signal processing module 30 and the test environment data set established by the synchronous acquisition module 40. According to the data in the test environment data set, the digital signals are corrected and compensated according to a preset algorithm, and finally the test results are established. For example, if the temperature affects the detection results, when the temperature sensor detects that the temperature is too high, the central processing unit 50 adjusts the digital signals according to the preset algorithm to improve the accuracy of the detection results. By integrating the environmental data and the detection data through the central processing unit 50, the digital signals are corrected and compensated, which improves the accuracy of the blood potassium detection results and makes the detection results more accurate and reliable.

[0025] As Figure 2 shown, it is another structural schematic diagram of a portable bedside blood potassium detector according to an embodiment of the present application. In addition to the above core components such as the acquisition module 10, the detection module 20, the signal processing module 30, the synchronous acquisition module 40, and the central processing unit 50, other additional function modules are added to further improve the functions of the blood potassium detector.

[0026] Further, the detection module 20 includes:

[0027] The first self-check and calibration module 21 is used to establish a historical data set of the electrode. The historical data set includes electrode current data, voltage data, and impedance data. Through the historical data set, the time decay analysis of the electrode performance is carried out to generate a performance calibration result.

[0028] The second self-check and calibration module 22 is used to perform detection backtracking and establish a backtracking data set. The backtracking data set is the measurement data under a preset time window. According to the backtracking data set, backtracking calibration is carried out to establish a backtracking calibration result.

[0029] The output module 23 is used to output an electrical signal after performing joint data correction through the backtracking calibration result and the performance calibration result.

[0030] Specifically, the performance of the electrode will decay as the usage time increases. For example, the electrode material may be contaminated or damaged, resulting in measurement errors. During the operation of the electrode, the first self-check and calibration module 21 continuously collects the current data, voltage data, and impedance data of the electrode, and forms a historical data set of the electrode with these data. Then, an algorithm is used to perform time decay analysis on this historical data set. This algorithm can be based on mathematical models such as linear regression models. By analyzing the changing trends of the current data, voltage data, and impedance data of the electrode over time, it judges the decay situation of the electrode performance and generates a performance calibration result for adjusting the output signal of the detection module 20. Through the time decay analysis of the electrode performance by the first self-check and calibration module 21, the change of the electrode performance can be detected in time. The generated performance calibration result can be used to adjust the working state of the electrode, improve the accuracy of electrode detection, and thus improve the reliability of the entire blood potassium detection.

[0031] The main function of the second self-check and calibration module 22 is to discover and correct potential biases in the historical data through retrospective analysis. First, a preset time window is set, and measurement data is collected within this time window to construct a retrospective data set. Then, an algorithm is used to process this retrospective data set. This algorithm can be a method based on statistical analysis, such as mean comparison, variance analysis, etc. By comparing with standard data or historical normal data, short-term fluctuations or abnormal data points are identified, and a retrospective calibration result is obtained. Through detection retrospective and retrospective calibration, potential biases or abnormal situations that may exist in the recent detection process can be discovered. The obtained retrospective calibration result helps to improve the accuracy of the current detection result and plays an optimizing and correcting role in the detection process.

[0032] The output module 23 obtains the performance calibration result of the first self-check and calibration module 21 and the retrospective calibration result of the second self-check and calibration module 22, and performs data calibration on these two results according to a pre-set combined calibration algorithm. This algorithm may be a weighted average algorithm, etc. After calibration, the final electrical signal is obtained and output. By performing combined data calibration on the two calibration results, the long-term change of the electrode performance (performance calibration result) and the accuracy of recent detection (retrospective calibration result) are comprehensively considered, improving the reliability of the output result of the entire detection module 20, and further providing a more accurate digital signal for subsequent signal processing and blood potassium detection results.

[0033] Furthermore, the output module 23 is used to perform the following steps:

[0034] Step P231: Analyze the occurrence frequency of performance decay points in the historical data set to establish a first influence identifier.

[0035] Step P232: Obtain the performance decay point closest to the current time node, establish an adjacent distance, and generate a second influence identifier according to the adjacent distance.

[0036] Step P233: After performing the performance correction result identification using the first influence identifier and the second influence identifier, the combined data correction is completed.

[0037] Specifically, the performance decay point is a point in the historical dataset of the electrode that indicates the point where the electrode performance begins to show an obvious downward trend (obvious changes in current data, voltage data, impedance data). For example, in the data of the electrode voltage changing with time, when the voltage suddenly drops by more than a certain threshold, that point can be regarded as the performance decay point. The output module 23 first obtains the historical dataset from the first self-check correction module 21, and this dataset includes electrode current data, voltage data, impedance data, etc. Then, it analyzes the occurrence frequency of the performance decay points in this dataset, counts the number of times the performance decay points occur, and establishes the first influence identifier based on the number of occurrences and the proportional relationship with the total number of data points, etc., to represent the degree of influence of the frequency of electrode performance decay on the detection result.

[0038] In the already determined historical dataset, find the performance decay point closest to the current time node through methods such as time sorting or index search, and then calculate the proximity distance between this performance decay point and the current time node. For example, in units of time, if the closest performance decay point is 5 days ago, then 5 days is the proximity distance. According to the pre-set distance-influence relationship algorithm, generate the second influence identifier based on this proximity distance. For example, the closer the distance, the greater the influence, and generate the corresponding identifier according to a certain mapping relationship. The second influence identifier is used to represent the degree of influence of the proximity of the closest performance decay point to the current on the detection result, and is an identifier for the degree of influence of the recent electrode performance on the detection result.

[0039] After obtaining the first influence identifier and the second influence identifier, apply these two identifiers to the performance correction result for identification, such as performing operations such as weighting the performance correction result according to the identifier, adjusting parameters, or marking specific information, etc., so as to complete the combined data correction and obtain the finally output corrected electrical signal.

[0040] In the above execution steps, by real-time tracking and correction of the electrode decay trend, the accuracy and reliability of blood potassium detection are significantly improved. It can not only correct the systematic error caused by electrode decay, but also optimize the detection signal in real time to ensure the stability of the blood potassium detector under long-term use.

[0041] Further, the output module 23 is also used to perform the following steps:

[0042] Step P234: Obtain the backtracking data volume according to the backtracking dataset, and establish a third influence identifier based on the backtracking data volume.

[0043] Step P235: Calculate the average interval of the backtracking data in the backtracking dataset, and establish a fourth impact identifier based on the average interval.

[0044] Step P236: After performing the backtracking calibration result identification based on the third impact identifier and the fourth impact identifier, perform weighted calculation with the identified performance correction result to complete the joint data correction.

[0045] Specifically, the backtracking data volume refers to the number of data entries in the backtracking dataset. The output module 23 obtains the backtracking dataset from the second self-check correction module 22, then counts the number of data therein to obtain the backtracking data volume, and then establishes a third impact identifier based on the size of the backtracking data volume. Exemplarily, different impact levels can be divided according to the range of the data volume. For example, when the backtracking data volume is less than 100, it is a low impact level, identified as 1; when it is between 100 and 500, it is a medium impact level, identified as 2; when it is greater than 500, it is a high impact level, identified as 3. The third impact identifier is used to represent the impact degree of the backtracking data volume on the backtracking calibration result.

[0046] In the obtained backtracking dataset, calculate the time interval between adjacent backtracking data, and then obtain the average value of these time intervals to get the average interval. Establish a fourth impact identifier according to a pre-set algorithm related to the average interval. For example, if the average interval is less than 0.5 seconds, it is identified as a high accuracy impact (such as identified as 3), indicating that a small average interval is beneficial for calibration; if it is between 0.5 seconds and 2 seconds, it is identified as a medium accuracy impact (identified as 2); if it is greater than 2 seconds, it is identified as a low accuracy impact (identified as 1). The fourth impact identifier characterizes the impact of the average interval on the backtracking calibration result and the detection result. If the average interval is too large or too small, it may affect the effectiveness of the calibration.

[0047] After obtaining the third impact identifier and the fourth impact identifier, apply them to the backtracking calibration result for identification. Similar to step P233, operations such as numerically adjusting the backtracking calibration result according to the identifier or marking relevant information can be performed. Then, perform weighted calculation on the identified backtracking calibration result and the identified performance correction result according to a pre-set weighting coefficient. For example, the weight of the identified backtracking calibration result is 0.4, and the weight of the identified performance correction result is 0.6. The final corrected result is obtained through weighted summation to complete the joint data correction.

[0048] Through the above steps for joint data correction, various influencing factors in the backtracking data volume, the average interval of backtracking data, and the performance correction result are comprehensively considered, making the final correction result more accurate and reliable, improving the accuracy of the electrical signal output by the detection module 20, and further enhancing the reliability of the entire blood potassium detection.

[0049] Further, the blood potassium detector according to the embodiment of the present application further includes:

[0050] An alarm module 61, configured to perform early warning trigger analysis on the test result, establish an early warning trigger level, configure an early warning signal according to the early warning trigger level, and perform early warning reporting after receiving the test result.

[0051] A communication module 62, configured to synchronously communicate and transmit the early warning signal.

[0052] Specifically, the alarm module 61 receives the test result from the central processing unit 50. Then, the test result is compared with a preset normal range value of blood potassium and an early warning threshold to determine the early warning trigger level. For example, the normal range of blood potassium concentration is 3.5 mmol / L to 5.5 mmol / L. If the detection result is lower or higher than this range, an early warning needs to be triggered, and the early warning trigger level is determined according to the degree of deviation. The early warning trigger level is a classification of the severity of the early warning. For example, it can be divided into three levels: mild, moderate, and severe. If the blood potassium concentration slightly deviates from the normal range, it is a mild early warning trigger level; if the degree of deviation is large, it is a moderate or severe level, and different levels correspond to different early warning signals. After determining the early warning trigger level, according to the configuration information stored inside the module, a corresponding early warning signal is configured for this level. For example, in the case of a mild early warning, it can be configured as a low-frequency beeping sound and a flashing yellow indicator light; in the case of a severe early warning, it is configured as a high-frequency beeping sound and a flashing red indicator light, and early warning reporting is performed according to the configured early warning signal.

[0053] The communication module 62 obtains the early warning signal configured by the alarm module 61. Then, according to the communication protocol adopted by the blood potassium detector (such as Bluetooth protocol, Wi-Fi protocol, or a custom communication protocol), the early warning signal is encoded and synchronously transmitted to a preset target device or system. For example, if the target device is the mobile phone or computer of the caregiver and Bluetooth communication is used, the communication module 62 converts the early warning signal into the Bluetooth signal format and then sends it to the relevant application program on the mobile phone or computer of the caregiver.

[0054] The addition of the alarm module 61 and the communication module 62 further enhances the functionality and practicality of the blood potassium detector. The alarm module 61 can timely remind the user or relevant devices through early warning trigger analysis and hierarchical early warning, ensuring that the user can take timely measures. The communication module 62 can timely notify the early warning signal to the remote device through synchronous transmission, realizing real-time monitoring of the detection result. Combining the alarm and the communication module 62 not only improves the real-time response ability of the blood potassium detector but also enhances the intelligence and remote controllability of the monitoring.

[0055] Further, the blood potassium detector according to the embodiment of the present application further includes:

[0056] A display module 71 for generating a visualization signal according to the test result, establishing a color rendering through the warning signal, and performing a visual display according to the color rendering and the visualization signal.

[0057] A storage module 72 for encrypting and storing the test result.

[0058] Specifically, the display module 71 obtains the test result from the central processing unit 50, and then uses an internal algorithm to convert the test result into a visualization signal. This algorithm can adopt different conversion methods according to different types of test results. For example, for the blood potassium concentration value, it directly converts it into a suitable digital format; for the change of blood potassium concentration over time, it uses a plotting algorithm to plot it as a line graph, etc. Then, the display module 71 obtains the warning signal from the alarm module 61 and performs a color rendering according to the level or content of the warning signal. For example, if the warning signal indicates that the blood potassium concentration is too high (severely abnormal), then a red font and a flashing effect are used to render and display the blood potassium concentration value. Finally, the visualized signal after color rendering is visually displayed on the display screen. Through the visual display of generating the visualization signal and performing the color rendering, users can more intuitively view the blood potassium test result and the degree of abnormality of the result, which is convenient for users to quickly understand the meaning of the test result without having to deeply interpret complex numbers or data.

[0059] After receiving the test result, the storage module 72 takes the test result as plaintext and inputs it into the encryption algorithm according to a pre-set encryption algorithm, such as the AES (Advanced Encryption Standard) algorithm. After being processed by the encryption algorithm, the test result in ciphertext form is obtained. Finally, the ciphertext is stored in the storage medium (such as internal flash memory, external memory card, etc.) of the blood potassium detector. Encrypting and storing the test result can protect the privacy information of the tested person, prevent the test result from being obtained or tampered with by unauthorized personnel, ensure the security and reliability of the blood potassium detector in terms of data storage, and at the same time facilitate users to manage and retrieve the data.

[0060] The display module 71 and the storage module 72 together improve the user experience and data management ability of the blood potassium detector, enabling the blood potassium detector to not only have a real-time monitoring function, but also be able to track the health trend in the long term, further improving the practicality of the blood potassium detector.

[0061] Furthermore, the blood potassium detector described in the embodiment of the present application further includes:

[0062] A data interaction module 81 for generating an instruction to update the disposable test strip if the detection requirement accuracy triggers a preset accuracy threshold.

[0063] Replacement module 82, which is used to receive the instruction to update the disposable test strip, call the disposable test strip with an electrode array, and perform the replacement of the disposable test strip.

[0064] Cross-certification module 83, which is used to output an electrical signal according to the cross-certification result of the electrodes after the electrodes of the replaced disposable test strip are powered.

[0065] Specifically, the main task of the data interaction module 81 is to monitor the measurement accuracy of the blood potassium detector and decide whether to replace the test strip. The data interaction module 81 continuously monitors the current detection requirement accuracy of the blood potassium detector. For example, the detection accuracy is evaluated by comparing the difference between the current detection result and the detection result of a known standard sample. When it is detected that the detection requirement accuracy exceeds the preset accuracy threshold, an instruction to update the disposable test strip is generated according to the internally preset rules. Among them, the preset accuracy threshold is a preset accuracy standard value or range. For example, the detection accuracy requirement for blood potassium concentration is within ±0.1 mmol / L. If the actual detection accuracy exceeds this range, such as the detection error reaches 0.2 mmol / L, the preset accuracy threshold is triggered and an instruction to update the disposable test strip is generated.

[0066] After receiving the instruction to update the disposable test strip from the data interaction module 81, the replacement module 82 first locates the disposable test strip with an electrode array in the area where the disposable test strip is stored. Then, it activates the replacement mechanism, removes the old disposable test strip, and installs the new disposable test strip in the appropriate position. Among them, the electrode array is an array structure composed of multiple electrodes included in the disposable test strip, and these electrodes play a key role in the detection process. For example, the blood potassium concentration is detected through characteristics such as the potential difference between different electrodes.

[0067] After the replacement module 82 completes the replacement of the disposable test strip, the cross-certification module 83 first powers the electrodes of the new disposable test strip. Then, a cross-certification algorithm is used to authenticate the electrodes. For example, the electrical characteristics (such as resistance, capacitance, etc.) between the electrodes are measured and compared with each other, or the electrodes are compared with a standard electrode model. According to the cross-certification result, it is converted into a corresponding electrical signal and output. For example, if the cross-certification result of the electrodes shows that the electrode performance is good, a stable electrical signal is output; if there is a problem, an abnormal electrical signal is output.

[0068] The addition of the above three modules further improves the intelligence and automation level of the blood potassium detector. The data interaction module 81 can automatically trigger the update of the test strip according to the accuracy of the detection requirement. The replacement module 82 realizes the automatic replacement of the test strip, while the cross-certification module 83 ensures the reliable performance of the test strip after each replacement. The combination of these functions not only improves the detection accuracy and efficiency, but also reduces the error of manual operation, effectively improving the long-term stability of the blood potassium detector.

[0069] Furthermore, the blood potassium detector described in the embodiment of the present application further includes:

[0070] The self-update module 90 is used to receive test feedback, call corresponding test data for defect identification based on the test feedback, generate a self-optimization database according to the defect identification result, and perform self-optimization management of the blood potassium detector according to the self-optimization database.

[0071] Specifically, the self-update module 90 receives feedback data from the detection process, and this data includes information such as the accuracy, repeatability, and detection time of the detection result. Then, according to the information in the test feedback, corresponding test data is called for defect identification. For example, if the feedback mentions that there is a deviation in the detection result, the self-update module 90 will call the test data related to this detection, such as electrode parameters, sample data, environmental parameters, etc. during the detection, and use a predefined defect identification algorithm to analyze the called test data. This algorithm may be based on methods such as data statistics and model comparison. For example, the current detection data is compared with the standard data model to find the data points with differences, so as to identify possible defects. According to the defect identification result, a self-optimization database is generated, and this database stores optimization parameters and improvement measures. For example, if it is identified that the electrode parameters are the cause of the detection result deviation, then the self-optimization database may contain data such as the corrected electrode parameter range and the method of adjusting the electrode parameters. Finally, the blood potassium detector is self-optimized and managed according to the data in the self-optimization database, and the parameter settings of the detector, such as the calibration curve and detection threshold, are automatically adjusted to improve the detection accuracy.

[0072] The introduction of the self-update module 90 enables the blood potassium detector to have intelligent adaptive capabilities, and can reduce detection errors caused by factors such as electrode aging, environmental changes, and equipment drift through continuous learning and optimization adjustment.

[0073] In summary, the portable bedside blood potassium detector provided by the embodiment of the present application has the following technical effects:

[0074] The portable bedside potassium blood detector described in the embodiments of the present application works through the collaboration of multiple modules, significantly improving the accuracy and stability of the detection process. First, the acquisition module 10 ensures the accurate transmission of blood samples, providing reliable samples for subsequent analysis. The detection module 20 converts the potassium ion information in the blood into an electrical signal through an electrochemical reaction, while the signal processing module 30 improves the signal quality through signal amplification and A / D conversion and converts it into digital data that is convenient for processing. The synchronous acquisition module 40 provides the basis for signal compensation by collecting environmental data in real time. The central processor 50 then precisely corrects the signal based on the environmental data, reducing errors caused by environmental factors and thus improving the measurement accuracy. In addition, the self-check correction module and the output module 23 in the detection module 20 jointly perform electrode performance decay analysis and retrospective calibration to ensure the long-term stable operation of the device. The addition of functions such as the alarm module 61, the display module 71, the storage module 72, and the data interaction module 81 enables the detection results to be presented in a timely manner and effectively managed through remote communication and storage. The self-update module 90 improves the intelligence level of the portable bedside potassium blood detector through continuous learning and optimization.

[0075] Overall, the embodiments of the present application significantly improve the accuracy, stability, and long-term reliability of potassium blood detection through environmental factor compensation, signal optimization processing, electrode performance optimization, environmental compensation, real-time data feedback, and self-update mechanisms, achieving high-precision, stable potassium blood concentration detection that adapts to different environments and meeting the requirements of bedside real-time detection.

[0076] Although the present application has been described in connection with specific features and their embodiments, it is obvious that various modifications and combinations can be made without departing from the spirit and scope of the present application. Accordingly, the present specification and the drawings are merely exemplary illustrations of the present application as defined by the appended claims and are considered to cover any and all modifications, variations, combinations, or equivalents within the scope of the present application. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application is intended to include these changes and modifications.

Claims

1. A portable bedside potassium blood detector, characterized in that, The blood potassium detector includes: A collection module, which is used to collect finger blood and then transport the finger blood to a disposable test strip through a test strip interface; A detection module, which is used to activate the power supply unit to supply power to the electrodes of the disposable test strip and then output an electrical signal; A signal processing module, which is used to receive the electrical signal, convert it through signal amplification and an A / D signal converter, and then output a digital signal; A synchronous collection module, which is used to synchronously activate the environmental collection sensor to perform test environment collection and establish a test environment data set when the detection module is working; A central processing unit, which is used to receive the digital signal and the test environment data set, perform signal compensation on the digital signal, and establish a test result. The signal compensation is to perform calibration compensation on the digital signal according to the test environment data set.

2. The portable bedside blood potassium detector according to claim 1, characterized in that, The detection module includes: A first self-check and calibration module, which is used to establish a historical data set of the electrodes. The historical data set includes electrode current data, voltage data, and impedance data, perform time decay analysis on the electrode performance through the historical data set, and generate a performance calibration result; A second self-check and calibration module, which is used to perform detection backtracking, establish a backtracking data set. The backtracking data set is the measurement data under a preset time window, perform backtracking calibration according to the backtracking data set, and establish a backtracking calibration result; An output module, which is used to perform joint data correction through the backtracking calibration result and the performance calibration result, and then output an electrical signal.

3. The portable bedside potassium blood detector according to claim 2, wherein, The output module is used for: Performing an analysis on the occurrence frequency of performance decay points in the historical data set to establish a first influence identifier; Obtaining the performance decay point closest to the current time node to establish a proximity distance, and generating a second influence identifier according to the proximity distance; Performing identification of the performance calibration result by using the first influence identifier and the second influence identifier, and then completing the joint data correction.

4. The portable bedside potassium blood detector according to claim 3, wherein, The output module is also used for: Obtaining the backtracking data volume according to the backtracking data set, and establishing a third influence identifier based on the backtracking data volume; Calculating the average interval of the backtracking data in the backtracking data set, and establishing a fourth influence identifier according to the average interval; Performing identification of the backtracking calibration result according to the third influence identifier and the fourth influence identifier, and then performing weighted calculation with the identified performance calibration result to complete the joint data correction.

5. The portable bedside potassium blood detector according to claim 1, wherein The blood potassium detector includes: An alarm module, which is used to receive the test result, perform early warning trigger analysis on the test result, establish an early warning trigger level, configure an early warning signal according to the early warning trigger level, and perform early warning reporting; A communication module, which is used to synchronously transmit the early warning signal for communication.

6. The portable bedside potassium blood detector according to claim 5, wherein, The blood potassium detector further includes: A display module, which is used to generate a visualization signal according to the test result, perform color rendering through the early warning signal, and perform visualization display according to the color rendering and the visualization signal; A storage module, which is used to encrypt and store the test result.

7. The portable bedside potassium blood detector according to claim 1, characterized in that, The blood potassium detector further includes: A data interaction module, which is used to generate an instruction to update the disposable test strip if the detection requirement accuracy triggers a preset accuracy threshold; A replacement module, configured to receive the instruction for updating the disposable test strip, call the disposable test strip with an electrode array, and perform the replacement of the disposable test strip; A cross-certification module, configured to output an electrical signal according to the cross-certification result of the electrodes after powering the electrodes of the disposable test strip after replacement.

8. A portable bedside potassium blood detector according to claim 1, characterized in that, The potassium blood detector further includes: A self-update module, configured to receive test feedback, call corresponding test data based on the test feedback for defect identification, generate a self-optimization database according to the defect identification result, and perform self-optimization management of the potassium blood detector according to the self-optimization database.

Images