Feedback data verification method and system for cardio-pulmonary resuscitation dummy

Abstract

The invention discloses a feedback data verification method and system for a cardio-pulmonary resuscitation dummy, and the method comprises the steps: collecting a reference parameter through a pressure sensor, carrying out the data analysis of the reference parameter, and obtaining a data analysis result, which comprises a pressing frequency, a pressing depth and a pressing position; verifying the feedback parameters based on the data analysis result; the invention relates to the technical field of medical emergency training equipment. A verification system which is known in precision, high in reliability and independent of a tested dummy system is established through the flexible sensor covering, the data collector and the data analysis terminal, a credible measurement basis is established, training data of trainees are measured, comparison is performed in combination with actual measurement parameters of the cardio-pulmonary resuscitation dummy, and the accuracy of the cardio-pulmonary resuscitation dummy is improved. The actual measurement parameters of the cardio-pulmonary resuscitation dummy are evaluated and calibrated through data differences, operation is convenient, and the cardio-pulmonary resuscitation dummy does not need to be disassembled.

Description

Technical Field

[0001] This application relates to the field of medical emergency training equipment technology, specifically to a method and system for verifying feedback data for a cardiopulmonary resuscitation manikin. Background Technology

[0002] Cardiopulmonary resuscitation (CPR) mannequins are designed to meet the training needs for first aid skills and knowledge. CPR mannequins are typically designed to be highly realistic, simulating various physiological states of the body during cardiac arrest, allowing trainees to practice in a safe environment and thus master correct first aid skills.

[0003] The mainstream equipment on the market uses methods such as pressure sensing, infrared sensing, and ultrasonic sensing, which are easily affected by the coupling interference of environmental temperature and humidity. This results in a pressing depth measurement error exceeding ±1.5mm and a frequency feedback distortion rate exceeding 18%. These measurement errors and distortions directly affect the trainee's perception of their own operational quality and may lead to the formation of incorrect muscle memory.

[0004] Secondly, existing CPR mannequins lack a traceable benchmark for verification, independent of the mannequin's own sensors. Specifications and testing methods vary significantly among manufacturers, lacking a unified measurement standard. Each manufacturer's equipment acts as both player and referee. The lack of authoritative standards for verifying the accuracy of compression data during operation leads to trainees training with incorrect equipment data, creating a vicious cycle of "incorrect feedback – misguided operation." Therefore, the market urgently needs a product capable of analyzing and verifying the data from such products.

[0005] In view of this, a method and system for verifying feedback data in a cardiopulmonary resuscitation manikin are proposed. Summary of the Invention

[0006] In view of the deficiencies in the existing technology, the technical problem solved by the present invention is: how to monitor the accuracy of feedback data from cardiopulmonary resuscitation manikins in a non-destructive and convenient manner.

[0007] To achieve the above objectives, in a first aspect, embodiments of this application provide a method for verifying feedback data in a cardiopulmonary resuscitation manikin, wherein:

[0008] The feedback parameter is defined as: the data measured and fed back by the cardiopulmonary resuscitation simulator itself;

[0009] The baseline parameter is defined as: the data obtained during the generation of the feedback parameter, that is, the data collected during the self-measurement of the cardiopulmonary resuscitation manikin;

[0010] The steps of this method include:

[0011] Reference parameters are collected by a pressure sensor, and the data analysis results are obtained after the reference parameters are analyzed. The data analysis results include the pressing frequency, pressing depth and pressing position.

[0012] Based on the data analysis results, the feedback parameters are verified.

[0013] Secondly, embodiments of this application provide a feedback data verification system for a cardiopulmonary resuscitation manikin, including a flexible sensor cover, a data acquisition device, and a data analysis terminal.

[0014] In the second aspect, the flexible sensor cover encapsulates a plurality of pressure sensors, which are arranged as multi-point thin-film pressure sensors. The flexible sensor cover is used to convert pressure information acting at different locations into electrical signals and transmit the electrical signals to a data acquisition device.

[0015] The data acquisition unit is used to receive electrical signals, filter out interference signals in the electrical signals through a filtering function, generate a data stream, and transmit it to the data analysis terminal. The transmission method includes Bluetooth.

[0016] The data analysis terminal is used to receive data streams and convert them into pressure heat maps for visualization.

[0017] Compared with the prior art, the advantages of this application are:

[0018] A calibration system with known accuracy and high reliability, independent of the tested manikin system, is built by using flexible sensor covers, data acquisition devices, and data analysis terminals. A reliable measurement benchmark is established to measure trainee training data and compare it with the actual measurement parameters of the cardiopulmonary resuscitation (CPR) manikin. The actual measurement parameters of the CPR manikin are evaluated and calibrated based on the data differences. The operation is convenient and does not require disassembly of the CPR manikin.

[0019] The specific features are as follows:

[0020] 1. Non-destructive verification: By covering the outside with a flexible sensing layer, no structural changes or damage are caused to the simulated human body.

[0021] 2. Objective benchmark: It provides a high-precision measurement benchmark independent of the tested mannequin system, solving the problem of equipment self-testing and self-certification.

[0022] 3. Comprehensive and efficient: It can simultaneously verify the three core parameters of pressing depth, frequency and position in real time, which is highly efficient.

[0023] 4. Intuitive results: The pressure distribution is visualized through a pressure heat map, which facilitates quick location of system errors.

[0024] 5. Easy to operate: The system can be set up quickly and the calibration process is simple, making it suitable for rapid equipment quality inspection before daily training. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 This is a schematic diagram of the cardiopulmonary resuscitation manikin verification process for this application;

[0027] Figure 2 This is a schematic diagram of the pressure sensor distribution in the flexible sensor cover of the embodiment of this application. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0029] The flowchart shown in the attached diagram is for illustrative purposes only and does not necessarily include all content and operations / steps, nor does it necessarily have to be performed in the order described. For example, some operations / steps can be broken down, combined, or partially merged, so the actual execution order may change depending on the actual situation.

[0030] The pressure sensors used in mainstream CPR manikins on the market are susceptible to interference from environmental temperature and humidity, resulting in compression depth measurement errors exceeding ±1.5mm and frequency feedback distortion rates reaching 18%, severely limiting training effectiveness. Furthermore, the specifications and testing methods of CPR manikin manufacturers vary widely, lacking unified measurement standards. There is a lack of authoritative standards to verify the accuracy of feedback data generated during operation, leading trainees to train with incorrect equipment data, creating a vicious cycle of "incorrect feedback – misguided operation."

[0031] In summary, current mainstream CPR manikins lack a real-time data cross-validation mechanism.

[0032] Therefore, in a first aspect, embodiments of this application provide a method for verifying feedback data in a cardiopulmonary resuscitation manikin.

[0033] In this method:

[0034] The feedback parameters (i.e., the actual measurement parameters of the cardiopulmonary resuscitation manikin) are defined as: the data measured and fed back by the cardiopulmonary resuscitation manikin itself;

[0035] The baseline parameter is defined as: the data obtained during the generation of the feedback parameter, that is, the data collected in this application during the self-measurement of the cardiopulmonary resuscitation manikin;

[0036] Error thresholds are defined as follows: compression depth error threshold is set at ±2mm, frequency error threshold is set at ±5 times / minute, and positional deviation error threshold is set at ±20mm. These error thresholds are set with reference to the tolerance standards for assessing the quality of adult cardiopulmonary resuscitation in the "Chinese Red Cross Cardiopulmonary Resuscitation Training Manual".

[0037] The steps of this method include:

[0038] Reference parameters are collected by a pressure sensor, and the data analysis results are obtained after the reference parameters are analyzed. The data analysis results include the pressing frequency, pressing depth and pressing position.

[0039] Based on the data analysis results, the feedback parameters are verified.

[0040] Therefore, it can be seen that by measuring the training data of trainees through pressure sensors and comparing it with the feedback parameters of the cardiopulmonary resuscitation (CPR) manifold, the feedback parameters of the CPR manifold can be evaluated and calibrated based on the data differences. The operation is convenient and does not require disassembling the CPR manifold.

[0041] In one exemplary embodiment, the pressure sensor has a measurement range of 4 to 6 times the compression range to ensure that the pressure sensor measures all data of the cardiopulmonary resuscitation (CPR) procedure.

[0042] In one exemplary embodiment, before acquiring the reference parameters via the pressure sensor, the following position calibration step is further included:

[0043] Step 1: Encapsulate the pressure sensor into a flexible sensor cover;

[0044] Step 2: Print a center calibration point and calibration auxiliary lines on the surface of the flexible sensor cover. The calibration auxiliary lines include horizontal and vertical lines that intersect vertically, and the intersection of the horizontal and vertical lines coincides with the center calibration point.

[0045] Step 3: Place the flexible sensor cover on the surface of the CPR manikin, aligning the horizontal line with the line connecting the two nipples of the CPR manikin, and aligning the center calibration point with the midpoint of the line connecting the two nipples of the CPR manikin.

[0046] In this position calibration method, the flexible sensor cover is fitted to the surface curve of the cardiopulmonary resuscitation mannequin to ensure the accuracy of the measurement results through environmental matching. At the same time, the positioning accuracy of the flexible sensor cover is ensured by the central calibration point and calibration auxiliary lines. The vertical lines are used to avoid the situation where the flexible sensor cover is difficult to locate effectively after covering the cardiopulmonary resuscitation mannequin, further ensuring the accuracy of the measurement results.

[0047] In one exemplary embodiment, the process of obtaining the pressing frequency includes:

[0048] Determine two adjacent pressure peaks: the peak values ​​of adjacent peaks or troughs; based on these two adjacent pressure peaks, calculate the current compression frequency. Specifically, one compression is considered as one cycle. Calculate the reciprocal of the time difference between two adjacent pressure peaks and convert the units accordingly, typically to 100-120 compressions per minute. This is the current compression frequency.

[0049] In an exemplary embodiment, the process of obtaining the pressing depth is as follows: the maximum value of the peak value of the above-mentioned wave is used as an indicator of the current pressing depth value of the pressing action.

[0050] In one exemplary embodiment, the pressure distribution location is used to determine whether the compression position has deviated. A pressure heatmap is generated from the collected data. This visually displays the pressure distribution location, enabling the determination of whether the compression position is correct and providing data support for statistical analysis of the number of correct / incorrect CPR compressions. Furthermore, it allows for precise identification of the cause and direction of deviation of errors.

[0051] In an exemplary embodiment, the process of verifying the feedback parameters described above includes:

[0052] Determine the baseline parameters and their error thresholds (see above for detailed error thresholds). When the error between the baseline parameters and the feedback parameters exceeds the corresponding error threshold, the cardiopulmonary resuscitation manikin feedback data is judged to be inaccurate. When the error between some baseline parameters and the feedback parameters is within the corresponding error threshold, while the error between the remaining parameters and the baseline parameters exceeds the corresponding error threshold, the cardiopulmonary resuscitation manikin feedback data is judged to be inaccurate. It should be noted that the baseline parameters include, but are not limited to, compression frequency, compression depth, and compression position.

[0053] In an exemplary embodiment, when acquiring the baseline parameters of the cardiopulmonary resuscitation (CPR) manikin, the initial data from the first 1 to 3 seconds is filtered. When the flexible sensor cover is placed on the CPR manikin, since the CPR manikin is not flat, the flexible sensor cover will deform. To prevent measurement errors, the initial data is calibrated and zeroed by filtering to ensure stable pressure sensor readings and eliminate electrical noise and installation stress interference during system startup.

[0054] Secondly, embodiments of this application also provide a feedback data verification system for a cardiopulmonary resuscitation manikin that implements the above-described method, including a flexible sensor cover, a data acquisition device, and a data analysis terminal;

[0055] The flexible sensor cover encapsulates several pressure sensors, arranged as a multi-point thin-film pressure sensor. The flexible sensor cover is used to convert pressure information acting at different locations into electrical signals and transmit the electrical signals to the data acquisition unit.

[0056] The data acquisition unit is used to receive electrical signals, filter out interference signals in the electrical signals through a filtering function, generate a data stream, and transmit it to the data analysis terminal. The transmission method includes Bluetooth.

[0057] The data analysis terminal is used to receive data streams and convert them into pressure heat maps for visualization.

[0058] In one exemplary embodiment, the sensing area of ​​the flexible sensor cover is 20*20 cm, the minimum sensing accuracy is 7.5*7.5 mm, and several pressure sensors are arranged in a matrix, as shown in the attached figure. Figure 2 As shown, the flexible sensor cover has a sampling resolution of 16*16, comprising a total of 256 completely independent detection units, i.e., 256 completely independent pressure sensors; it can detect linear pressure changes from 0 to 100 kg. The pressure response speed is <20ms. This fully meets the high-precision detection requirements for CPR compression detection. When a detection unit detects pressure, its own resistance value changes linearly. Based on this principle, by simply obtaining the change in the resistance value of the detection unit, the pressure change in the current sensing area can be determined.

[0059] In one exemplary embodiment, 256 pressure sensors in the flexible sensor cover are connected to a signal acquisition unit via 2*16 contact points. The signal acquisition unit supports 16-channel ADC conversion and simultaneously acquires 16 signals from the pressure sensors. The other 16 contact points are drive signals, driven by the control chip built into the signal acquisition unit.

[0060] In use, after calibrating the flexible sensor cover with the CPR manikin, the CPR manikin is activated. First, the first contact of the flexible sensor cover is powered separately, so that 16 electrical signal values ​​can be obtained simultaneously from the 16 detection points in the same column and recorded in the memory of the signal acquisition unit's built-in control chip. Then, the second contact is driven to obtain 16 electrical signal values ​​in the second column and record them. This process is repeated until all 16 contacts are scanned, resulting in a 16*16 electrical signal strength matrix. The MCU in the data acquisition unit preprocesses the raw voltage values ​​collected by the 16 ADCs and transmits the array containing data from 256 pressure sensing units to the data analysis terminal via Bluetooth module.

[0061] To further explain, based on a response time of 20ms per contact, scanning 256 contacts can be completed in just 320ms, and the data refresh rate can reach 3Hz to support high-frequency testing.

[0062] In one exemplary embodiment, the data analysis terminal is equipped with data analysis software that supports Bluetooth communication. Upon starting the data analysis software, after receiving 256 signal data points from the data acquisition unit, it converts them into a user-visible pressure heatmap and refreshes the heatmap at a refresh rate of no less than 5Hz. The pressure heatmap clearly shows the location and intensity of the force applied to the chest of the simulated human being being tested.

[0063] It should be noted that during the acquisition of the pressure heatmap, the pressure heatmap data from 1 to 3 seconds after the initiation of cardiopulmonary resuscitation manikin was filtered and processed.

[0064] To further explain, by analyzing the pressure heatmap in the data analysis terminal, the reciprocal of the time difference between two adjacent pressure peaks is used as the compression frequency for the current compression action. This frequency is compared with the compression frequency feedback parameters from the CPR manikin. If the error exceeds the corresponding error threshold, the CPR manikin's compression frequency feedback is determined to be incorrect. Similarly, the compression depth is determined by the maximum value of the pressure peaks, and compared with the compression depth feedback parameters from the CPR manikin. If the error exceeds the corresponding error threshold, the CPR manikin's compression depth feedback is determined to be incorrect. The pressure heatmap displays the pressure distribution location, and the compression position is determined to be offset based on this location, thus achieving compression position localization. The results of the CPR manikin's judgment on compression position offset are compared. If the error in the number of judgments exceeds the corresponding error threshold, the CPR manikin's judgment of compression position is determined to be incorrect. This provides data calibration support for the statistics of the number of correct / incorrect CPR compressions.

[0065] Furthermore, if any of the judgments regarding compression frequency, compression depth, or compression location are incorrect on the cardiopulmonary resuscitation (CPR) manipulative, the manipulative's feedback data is deemed inaccurate.

[0066] See below. Figure 1 As shown, the above method is illustrated from an execution level through a specific embodiment. The method includes the following steps:

[0067] S1. Position calibration: The flexible sensor cover is used to calibrate the position of the cardiopulmonary resuscitation manikin (the position calibration process is described above);

[0068] S2. Data Acquisition: When trainees conduct cardiopulmonary resuscitation (CPR) simulation training on the CPR manikin, baseline parameters are collected through a flexible sensor cover, and the CPR manikin simultaneously collects feedback parameters.

[0069] S3: Generate a pressure heat map: After filtering the baseline parameters through the data acquisition device (see above for details of the filtering process), the data is transmitted via Bluetooth to the data analysis terminal for display of the pressure heat map.

[0070] S4: Parameter Comparison and Error Calculation: Calculate the error value between the reference parameter and the feedback parameter (see above for details);

[0071] S5: Determine whether the error is within the corresponding error threshold. If no, proceed to S6; if yes, proceed to S7.

[0072] S6. The data provided by the cardiopulmonary resuscitation manikin is inaccurate.

[0073] S7. Determine that the data provided by the cardiopulmonary resuscitation manikin is accurate.

[0074] The terms "comprising" and "having," and any variations thereof, in the specification, claims, and accompanying drawings of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus. The terms "first," "second," and "third," etc., are used to distinguish different objects, etc., and do not indicate a sequence, nor do they limit "first," "second," and "third" to different types.

[0075] In the description of the embodiments of this application, terms such as "exemplary," "for example," or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "exemplary," "for example," or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary," "for example," or "for instance" is intended to present the relevant concepts in a concrete manner.

[0076] In the description of the embodiments of this application, unless otherwise stated, " / " means "or". For example, A / B can mean A or B. The "and / or" in the text is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of this application, "multiple" means two or more.

[0077] In some processes described in the embodiments of this application, multiple operations or steps are included in a specific order. However, it should be understood that these operations or steps may not be executed in the order they appear in the embodiments of this application, or they may be executed in parallel. The sequence number of the operation is only used to distinguish different operations, and the sequence number itself does not represent any execution order. In addition, these processes may include more or fewer operations, and these operations or steps may be executed sequentially or in parallel, and these operations or steps may be combined.

[0078] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device to execute the methods described in the various embodiments of this application.

[0079] The above are merely specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be determined by the scope of the claims.

Claims

1. A method for verifying feedback data in a cardiopulmonary resuscitation manikin, characterized in that, In this method: The feedback parameter is defined as: the data measured and fed back by the cardiopulmonary resuscitation simulator itself; The baseline parameter is defined as: the data obtained during the generation of the feedback parameter, that is, the data collected during the self-measurement of the cardiopulmonary resuscitation manikin; The steps of this method include: Reference parameters are collected by a pressure sensor, and the data analysis results are obtained after the reference parameters are analyzed. The data analysis results include the pressing frequency, pressing depth and pressing position. Based on the data analysis results, the feedback parameters are verified.

2. The method for verifying feedback data in a cardiopulmonary resuscitation manikin according to claim 1, characterized in that, The pressure sensor has a measurement range of 4 to 6 times the compression range to ensure that the pressure sensor measures all data of the cardiopulmonary resuscitation operation.

3. The method for verifying feedback data in a cardiopulmonary resuscitation manikin according to claim 1, characterized in that, Before acquiring the reference parameters via the pressure sensor, the following position calibration step is also included: Step 1: Encapsulate the pressure sensor into a flexible sensor cover; Step 2: Print a center calibration point and calibration auxiliary lines on the surface of the flexible sensor cover. The calibration auxiliary lines include horizontal and vertical lines that intersect perpendicularly, and the intersection of the horizontal and vertical lines coincides with the center calibration point. Step 3: Place the flexible sensor cover on the surface of the CPR manikin, aligning the horizontal line with the line connecting the two nipples of the CPR manikin, and aligning the center calibration point with the midpoint of the line connecting the two nipples of the CPR manikin.

4. The method for verifying feedback data in a cardiopulmonary resuscitation manikin according to claim 1, characterized in that, The process of obtaining the pressing frequency includes: Determine two adjacent pressure peaks: the peak value of an adjacent peak or an adjacent trough; calculate the frequency of the current pressing action based on the two adjacent pressure peaks.

5. The method for verifying feedback data in a cardiopulmonary resuscitation manikin according to claim 4, characterized in that, In the process of obtaining the pressing depth, the maximum value of the peak value is used as the indicator of the current pressing depth value of the pressing action.

6. The method for verifying feedback data in a cardiopulmonary resuscitation manikin according to claim 1, characterized in that, The pressing position is displayed in the form of a pressure heat map, which is used to determine whether the pressing position has shifted by the pressure distribution.

7. The method for verifying feedback data in a cardiopulmonary resuscitation manikin according to claim 1, characterized in that, The process of verifying the feedback parameters includes: Determine the baseline parameters and their error thresholds. When the error between the baseline parameters and the feedback parameters exceeds the corresponding error threshold, the cardiopulmonary resuscitation manikin feedback data is judged to be inaccurate. When the error between some baseline parameters and the feedback parameters is within the corresponding error threshold, while the error between the remaining parameters and the baseline parameters exceeds the corresponding error threshold, the cardiopulmonary resuscitation manikin feedback data is judged to be inaccurate.

8. The method for verifying feedback data in a cardiopulmonary resuscitation manikin according to claim 1, characterized in that, When acquiring the baseline parameters of the cardiopulmonary resuscitation manikin, the data from the initial 1 to 3 seconds are filtered.

9. A feedback data verification system for a cardiopulmonary resuscitation manikin, characterized in that, This includes flexible sensor covers, data acquisition devices, and data analysis terminals.

10. A feedback data verification system for a cardiopulmonary resuscitation manikin according to claim 9, characterized in that, The flexible sensor cover encapsulates several pressure sensors, arranged as multi-point thin-film pressure sensors. The flexible sensor cover is used to convert pressure information acting at different locations into electrical signals and transmit the electrical signals to the data acquisition unit. The data acquisition unit is used to receive electrical signals, filter out interference signals in the electrical signals through a filtering function, generate a data stream, and transmit it to the data analysis terminal. The transmission method includes Bluetooth. The data analysis terminal is used to receive data streams and convert them into pressure heat maps for visualization.

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