Teaching system and method for conducting cardio-pulmonary resuscitation pressing through mobile phone gravity sensing

Abstract

The invention provides a teaching system and method for carrying out cardiopulmonary resuscitation pressing through mobile phone gravity sensing, and aims to develop a cardiopulmonary resuscitation (CPR) pressing teaching system through a gravity sensing function of a smart phone, and provide real-time feedback and guidance by monitoring parameters such as pressing strength, frequency and depth of a student in real time, so as to improve the teaching efficiency of cardiopulmonary resuscitation. And students are helped to master correct cardio-pulmonary resuscitation skills. In addition, a calibration and verification mechanism is added in the scheme, the accuracy and reliability of the teaching process are ensured, and the quality of real-time feedback is further enhanced on the basis, so that the teaching effect is improved. A data calibration and verification module is introduced to ensure the accuracy and reliability of the teaching system to reduce and correct errors in consideration that mobile phone hardware equipment may be affected by different factors such as sensor errors and improper mobile phone fixation in the use process. The module maintains the precision of the system through the modes of regular calibration, real-time verification, error correction and the like.

Description

Technical Field

[0001] The present invention relates to the field of cardiopulmonary resuscitation teaching, and in particular to a teaching system and method for performing cardiopulmonary resuscitation compression using mobile phone gravity sensing. Background Art

[0002] Cardiopulmonary resuscitation (CPR) is an important emergency rescue technique for patients with cardiac arrest, and its core includes chest compression and artificial ventilation. CPR compression requires accurately finding the junction of the middle and lower 1 / 3 of the sternum or the midpoint of the line connecting the two nipples as the compression position. This position is near the projection position of the heart in the chest cavity. Pressing here can effectively exert pressure on the heart and make the heart pump blood. CPR compression requires adults to press at least 5cm but not more than 6cm deep, and the frequency is 100~120 times per minute. However, in actual operation, trainees often find it difficult to accurately grasp the compression depth and frequency, resulting in compressions that are too shallow or too deep, and frequencies that are too fast or too slow, thus affecting the effectiveness of CPR.

[0003] The mainstream CPR training equipment on the market usually uses manikins equipped with pressure sensors. The correct compression depth and frequency feedback are set through the manikins, allowing students to continuously adjust and correct during practice. At the same time, students can also keep the compression frequency stable by counting numbers silently and observing the feedback on the manikins' display screen. However, in undergraduate teaching in medical schools, CPR-related courses are often optional courses, and not every student can receive systematic theoretical learning. At the same time, there is a lack of systematic operational training before internships, which leads to students' lack of proficiency in actual operations. In addition, cardiopulmonary resuscitation compressions require mastering the correct compression site, depth, frequency, and ensuring sufficient chest rebound. These key elements have high operational requirements, and beginners often find it difficult to master them accurately.

[0004] The existing Chinese utility model patent has a publication number of CN210574591U. This technology collects data by installing a chest compression identification device and an artificial lung pressure identification device on the chest of a simulated person, and transmits the compression operation information to a mobile terminal through a wireless communication device, providing real-time feedback on the trainee's training status. This method has the advantages of high intelligence and accurate feedback, but the equipment cost is high, and it also has high requirements for professional training venues and maintenance conditions. Trainers usually perform manual evaluations by observing the trainees' compression actions or using simple timing tools. This method relies on the subjective experience of trainees, and not only is the feedback not accurate enough, but it is also difficult to correct incorrect operations in real time.

[0005] Therefore, although the simulator equipped with pressure sensors meets the needs of CPR training to a certain extent, it still has the following shortcomings: High cost limits promotion: Traditional training equipment is expensive, especially for primary medical institutions and individual users.

[0006] Dependence on dedicated equipment: The simulator equipment is large and not portable, which limits its use in non-professional environments.

[0007] Real-time feedback is not comprehensive: Manual assessment cannot provide accurate and immediate data guidance on compression depth and frequency.

[0008] With the continuous improvement of smartphone hardware functions and their widespread popularity, especially the improvement of the performance of built-in gravity sensors, new possibilities have been provided for CPR training. By directly using the gravity sensing function of smartphones, the depth and frequency of chest compressions can be monitored and guided in real time, further reducing equipment costs, improving training effects, and making CPR training more portable and popular. Summary of the invention

[0009] In view of the deficiencies in the prior art, the present invention provides a teaching system and method for cardiopulmonary resuscitation compression using mobile phone gravity sensing, aiming to develop a cardiopulmonary resuscitation (CPR) compression teaching system using the gravity sensing function of smart phones, and provide real-time feedback and guidance by real-time monitoring of trainees' compression force, frequency, depth and other parameters, to help trainees master correct cardiopulmonary resuscitation skills. In addition, the solution also adds a calibration and verification mechanism to ensure the accuracy and reliability of the teaching process, and on this basis further enhances the quality of real-time feedback to improve teaching effectiveness.

[0010] In order to achieve the above object, the present invention adopts the following technical solutions: The teaching system for cardiopulmonary resuscitation using mobile phone gravity sensing includes: The gravity sensing module is used to collect the three-dimensional acceleration data of the trainee during CPR compression in real time through the gravity sensor of the smartphone, and calculate the depth, frequency and strength of the compression; A real-time feedback module, connected to the gravity sensing module, for receiving the compression data output by the gravity sensing module and providing real-time feedback in audio, visual and vibration modes according to a preset cardiopulmonary resuscitation compression standard; The compression frequency is calculated by monitoring the time interval between two consecutive compression peaks. The number of compressions per minute = 60 seconds / the time interval between two compression peaks (seconds). The compression depth is calculated by the change in acceleration data. Teaching guidance module, which is used to provide CPR standard operation videos, action breakdown and prompts, as well as error correction and improvement suggestions; The data calibration and verification module is used to perform initial calibration, dynamic calibration and error correction on the data output by the gravity sensing module to ensure the accuracy and reliability of the data; Hardware interfaces and support modules are used to ensure system compatibility on different models of smartphones, support the connection of external devices, and provide battery management and energy saving functions.

[0011] Preferably, the gravity sensing module further includes: A sensor data acquisition unit, for collecting three-dimensional acceleration data in real time using an accelerometer and a gyroscope of a smartphone; A data processing unit, used to process acceleration data, analyze compression frequency and depth, and perform real-time comparison according to standard setting range values; The feedback output unit is used to give prompts through sound or vibration when it is detected that the compression depth or frequency does not meet the standards.

[0012] Preferably, the real-time feedback module further includes: A real-time data monitoring unit, used to synchronize the student's pressing data with the data interface of the gravity sensing module in real time; A threshold judgment and feedback generation unit, used to judge whether the current operation meets the standard according to the standard of cardiopulmonary resuscitation compression, and generate corresponding feedback; Feedback logic design unit is used to ensure that feedback information is timely and effective.

[0013] Preferably, the teaching guidance module also includes: The video content and prompt voice integration unit is used to integrate teaching videos and voice prompts. Students can refer to the video demonstration when practicing and make corrections according to the system prompts. Intelligent prompt design unit, used to dynamically adjust the guidance content according to the actual operation of the students, to ensure the personalization and pertinence of the teaching process; The error monitoring and feedback unit is used to identify incorrect operations and provide timely correction suggestions through real-time analysis of trainees' pressing data.

[0014] Preferably, the data calibration and verification module further includes: Initial calibration unit, used to perform a basic calibration when the system starts up to ensure that the sensor works properly; Dynamic calibration unit, used for regular calibration and real-time adjustment during use to ensure accuracy under long-term use; An error correction unit, used to make corrections based on the monitored errors to ensure the accuracy of teaching feedback; The verification mechanism unit is used to verify the accuracy of the system through known standard data and promptly prompt trainees to adjust operations or equipment postures.

[0015] Preferably, the initial calibration unit further includes: The equipment monitoring and static acceleration acquisition subunit is used to perform static acceleration monitoring when the system is started and collect acceleration data in a stationary state; The system tilt angle confirmation subunit is used to determine whether the device is in a suitable posture; The calibration data storage subunit is used to save the initial calibration data as reference values, and the subsequent calibration process is adjusted based on these data.

[0016] Preferably, the dynamic calibration unit further includes: A calibration trigger condition subunit, used to set the trigger conditions for periodic calibration and pressing behavior calibration; The acceleration data verification subunit is used to re-collect the acceleration data of the device in a static state during dynamic calibration and compare it with the data collected during the initial calibration; The error correction algorithm subunit is used to automatically adjust the data acquisition algorithm and correct the error of the sensor according to the deviation between the acceleration data and the standard value; The posture correction subunit is used to prompt the trainee to readjust the angle of the device if the tilt angle of the device changes significantly during the pressing process; The calibration feedback subunit is used to remind trainees to adjust the device posture or pressing behavior through audio, visual or vibration feedback during the dynamic calibration process.

[0017] Preferably, the error correction unit further includes: Deviation monitoring subunit, used to monitor the change of acceleration data at each press and compare the difference between current data and historical data; The correction subunit is used to process real-time acceleration data through a smoothing algorithm to reduce errors caused by short-term fluctuations. When it is found that the data fluctuates too much, it automatically adjusts the calculation thresholds of frequency and depth to ensure the accuracy of feedback; Environmental adaptability adjustment subunit, used to dynamically adjust the sensitivity of the sensor under different environmental conditions to reduce the impact of environmental factors on measurement accuracy; The error correction feedback subunit is used to display error prompts on the screen, provide adjustment suggestions, and prompt trainees to make adjustments through voice and vibration if the error detected is beyond the normal range.

[0018] Preferably, the hardware interface and support module also includes: Compatibility support unit, used to support different models of smartphones and ensure accurate reading of sensor data; External device support unit, used to connect Bluetooth headsets and vibration device auxiliary equipment to provide more diverse feedback methods; The battery management and energy-saving unit is used to optimize system power consumption so that the device can continue to operate efficiently during long-term use.

[0019] The teaching method of the teaching system for cardiopulmonary resuscitation compression using mobile phone gravity sensing includes the following steps: Using the above teaching system, three-dimensional acceleration data of trainees performing cardiopulmonary resuscitation compressions is collected; Calculate the depth, frequency and strength of compression based on the collected data; Provides real-time feedback through audio, visual and vibration based on preset CPR compression standards; Provide standard cardiopulmonary resuscitation operation videos, action breakdown and tips, as well as error correction and improvement suggestions; Perform initial calibration, dynamic calibration and error correction on the data output by the gravity sensing module to ensure the accuracy and reliability of the data; According to the students' learning progress, teaching content and guidance are provided in stages until the students complete all learning tasks and pass the systematic comprehensive evaluation.

[0020] Compared with the prior art, the present invention has the following beneficial effects: The present invention provides a teaching system and method for cardiopulmonary resuscitation compression using mobile phone gravity sensing, aiming to develop a cardiopulmonary resuscitation (CPR) compression teaching system using the gravity sensing function of a smart phone, and provide real-time feedback and guidance by real-time monitoring of trainees' compression force, frequency, depth and other parameters, to help trainees master correct cardiopulmonary resuscitation skills. In addition, the solution also adds a calibration and verification mechanism to ensure the accuracy and reliability of the teaching process, and on this basis further enhances the quality of real-time feedback to improve the teaching effect.

[0021] The present invention takes into account that the mobile phone hardware device may be affected by various factors during use, such as sensor error, improper mobile phone fixation, etc. In order to ensure the accuracy and reliability of the teaching system, a data calibration and verification module is introduced to reduce and correct errors. This module maintains the accuracy of the system through regular calibration, real-time verification, error correction, etc. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0023] Figure 1 It is a schematic diagram of the overall flow of the teaching system of the present invention; Figure 2This is a schematic diagram of the gravity sensing module framework of the present invention; Figure 3 It is a schematic diagram of the framework of the real-time feedback module of the present invention; Figure 4 It is a schematic diagram of the teaching guidance module framework of the present invention; Figure 5 This is a schematic diagram of the data calibration and verification module framework of the present invention; Figure 6 It is a schematic diagram of the hardware interface and supporting module framework of the present invention. DETAILED DESCRIPTION

[0024] The present invention is further described in detail below with reference to the accompanying drawings.

[0025] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art can think of other obvious variations. The basic principles of the present invention defined in the following description can be used for other embodiments, variations, improvements, equivalents, and other technical solutions that do not deviate from the spirit and scope of the present invention.

[0026] See also Figure 1-Figure 6 The present invention provides a teaching system for cardiopulmonary resuscitation compression using mobile phone gravity sensing, including the following core modules: gravity sensing module, real-time feedback module, teaching guidance module, data calibration and verification module, hardware interface and support module.

[0027] Furthermore, the gravity sensing module includes a sensor data acquisition unit, a data processing unit, and a feedback output unit; the gravity sensing module will monitor the compression frequency, compression depth, and compression strength through the built-in gravity sensor in the smartphone and collect the three-dimensional acceleration data of the trainee when performing cardiopulmonary resuscitation in real time, and then calculate the compression depth, frequency, and strength.

[0028] Compression frequency monitoring: Real-time monitoring of students' compression frequency to ensure that the number of compressions meets the recommended standards (generally 100-120 times per minute).

[0029] Compression depth monitoring: Monitor the depth of compression to ensure that the compression depth meets the standard (the compression depth for adults is usually 5-6 cm).

[0030] Pressure monitoring: Monitor the pressure to ensure it is moderate, neither too light nor too heavy.

[0031] The sensor data acquisition unit is used to collect three-dimensional acceleration data in real time using the accelerometer and gyroscope of the smartphone; The data processing unit is used to process acceleration data, analyze compression frequency and depth, and perform real-time comparison according to standard setting range values; The feedback output unit is used to give a prompt through sound or vibration when it is detected that the compression depth or frequency does not meet the standard.

[0032] It should be noted that the compression depth and compression frequency are calculated using the following method: (1) Calculation of compression frequency: Compression frequency refers to the number of times a trainee performs CPR compressions per unit time, usually expressed as "number of compressions per minute". The frequency is calculated mainly by using an acceleration sensor to monitor the cycle of each compression.

[0033] Calculation process: 1. Data collection: Use the built-in accelerometer (3-axis) or gyroscope sensor of the smartphone to collect acceleration data along the vertical direction (Z-axis) in real time; based on the placement of the phone, assuming that the back of the phone is facing down, the sensor mainly monitors the acceleration of the up and down movement.

[0034] 2. Motion recognition: When pressing, each press will cause the acceleration of the phone to fluctuate (i.e. pressing and releasing). Through the acceleration data, the system can identify the start and end points of the press. Usually, the peak acceleration of the press corresponds to the highest point of the press, and the rebound part corresponds to the lowest point of the release.

[0035] 3. Cycle calculation: In the time series acceleration data, the time interval (cycle) between two consecutive compression peaks is found to calculate the duration of each compression.

[0036] 4. Frequency calculation: Calculate the frequency of compression (unit: times / minute) based on the time interval between each compression. The formula is: , Among them, T 周期 is the duration of each compression cycle in seconds, and f is the compression frequency in times / minute.

[0037] If the system detects that the compression cycle is 1.2 seconds, the compression frequency is 50 times / minute; the system will continue to monitor the frequency. If the frequency exceeds the standard range of 100-120 times / minute, it will prompt the trainee to reduce the frequency through audio feedback, visual feedback or vibration feedback in the threshold judgment and feedback generation unit.

[0038] (2) Calculation of compression depth: Compression depth refers to the distance the chest sinks when the student presses. The calculation of this parameter also relies on the acceleration sensor of the smartphone, combining the acceleration change of the smartphone during the compression process to calculate the distance the chest sinks.

[0039] Calculation process: 1. Data collection: The smartphone obtains acceleration data in the up and down directions through the accelerometer. Assuming that the student places the phone in the middle of the chest when pressing, the relative displacement between the phone and the chest determines the fluctuation of acceleration.

[0040] 2. Acceleration integration: The acceleration data captured by the acceleration sensor is converted into velocity data through integration, and then the displacement data, i.e. the pressing depth, is obtained through integration. The acceleration needs to be integrated twice: , Where a(t) is the acceleration at time t, v(t) is the speed of compression, and d(t) is the depth of compression.

[0041] 3. Depth calculation: The current compression depth is displayed in real time on the mobile phone screen. The system will judge whether the student presses too shallowly or too deeply based on the standard (the compression depth for adults is generally 5-6 cm).

[0042] 4. Depth feedback: If the depth is less than 5 cm, the system will prompt "Insufficient compression depth"; if it exceeds 6 cm, the system will prompt "Too deep compression depth".

[0043] Furthermore, the real-time feedback module is connected to the gravity sensing module to receive the compression data output by the gravity sensing module and provide real-time feedback through audio, visual and vibration methods according to the preset CPR compression standards to help trainees adjust their movements in time. The real-time feedback module includes a real-time data monitoring unit, a threshold judgment and feedback generation unit, and a feedback logic design unit. Among them: The real-time data monitoring unit is used to synchronize the student's pressing data with the data interface of the gravity sensing module in real time.

[0044] The threshold judgment and feedback generation unit is used to judge whether the current operation meets the standard according to the standard of cardiopulmonary resuscitation compression, and generate corresponding feedback to provide real-time feedback information; the feedback information includes audio feedback, visual feedback and vibration feedback. Specifically: Audio feedback: Use voice prompts or warnings to guide students to see if the compressions are in place (such as "The compression depth is not deep enough, increase the force" or "The compression frequency is too fast, please adjust"); Visual feedback: The mobile phone screen displays green (meets the standard), yellow (close to the standard) or red (does not meet the standard) indicators to intuitively show the trainee's current operating status; Vibration feedback: When the student's compression depth or frequency does not meet the standard, the phone will vibrate to prompt, enhancing the intuitiveness of the feedback.

[0045] The feedback logic design unit is used to ensure that feedback information is timely and effective; each feedback is based on the real-time data of the trainees' actions to ensure that the feedback information is timely and effective.

[0046] Furthermore, the teaching guidance module is one of the core modules of this system, which is used to provide standard cardiopulmonary resuscitation operation videos, action decomposition and prompts, as well as error correction and improvement suggestions; the teaching guidance module includes a video content and prompt voice integration unit, an intelligent prompt design unit, and an error monitoring and feedback unit. Among them: The video content and voice prompt integration unit is used to integrate teaching videos and voice prompts. Students can refer to video demonstrations when practicing and make corrections based on the system's prompts, such as insufficient compression depth or too fast frequency.

[0047] The intelligent prompt design unit is used to dynamically adjust the guidance content according to the students' actual operations to ensure the personalization and pertinence of the teaching process.

[0048] The error monitoring and feedback unit is used to identify incorrect operations and provide timely correction suggestions through real-time analysis of trainees' pressing data.

[0049] Furthermore, the data calibration and verification module is used to perform initial calibration, dynamic calibration and error correction on the data output by the gravity sensing module to ensure the accuracy and reliability of the data.

[0050] It should be further explained that the core goal of the data calibration and verification module is to ensure that the output data of the gravity sensor (accelerometer) is accurate and reliable. The following problems may occur during the use of the mobile phone, resulting in sensor data deviation (including hardware error and operation error). Hardware error is mainly due to the manufacturing error or aging of the sensor itself, which may lead to reduced measurement accuracy; operation error is mainly due to improper fixation of the mobile phone or tilt of the device during operation, which will affect the measurement results and lead to inaccurate calculation of depth or frequency.

[0051] Therefore, the data calibration and verification module design includes an initial calibration unit, a dynamic calibration unit, an error correction unit, and a verification mechanism unit; among them, Initial calibration unit, used to perform a basic calibration when the system starts up to ensure that the sensor works properly; Dynamic calibration unit, used for regular calibration and real-time adjustment during use to ensure accuracy under long-term use; An error correction unit, used to make corrections based on the monitored errors to ensure the accuracy of teaching feedback; The verification mechanism unit is used to verify the accuracy of the system through known standard data and promptly prompt trainees to adjust operations or equipment postures.

[0052] The initial calibration unit also includes: a device monitoring and static acceleration acquisition subunit, a system tilt angle confirmation subunit, and a calibration data storage subunit. Further: The device monitoring and static acceleration acquisition subunit is used to perform static acceleration monitoring when the system starts up, and collect acceleration data in a static state. This is a quick initialization step to ensure that the accelerometer and gravity sensor of the mobile phone work properly; the system will monitor the acceleration value of the device when it is stationary (i.e., gravity acceleration) through the accelerometer and use it as the baseline value. If the monitored acceleration deviates too much from the standard earth gravity acceleration (about 9.8 m / s²), the user will be prompted to restart or recalibrate the device.

[0053] The system tilt angle confirmation subunit is used to determine whether the device is in a suitable posture (for example, whether the device is placed stably on the chest). If the device angle deviation is large, the system will prompt the trainee to adjust the device angle. By monitoring the device's tilt angle (using a gravity sensor), the system confirms whether the device is placed correctly. If the tilt angle exceeds the set threshold (for example, more than 5 degrees), the system will ask the trainee to readjust it.

[0054] The calibration data storage subunit is used to save the initial calibration data (such as acceleration and tilt angle when the device is stationary) as a reference value, and the subsequent calibration process is adjusted based on this data.

[0055] The dynamic calibration unit includes: a calibration trigger condition subunit, an acceleration data verification subunit, an error correction algorithm subunit, a posture correction subunit and a calibration feedback subunit. Further: The calibration trigger condition subunit is used to set the trigger conditions for periodic calibration and press behavior calibration. Periodic calibration means that the system automatically performs a calibration process every time it performs a certain number of operations (for example, every 50 presses). Periodic calibration helps correct errors caused by device temperature changes or sensor drift. Press behavior calibration means that when the system detects abnormal press behavior (such as sudden changes in press frequency or a large deviation of the press depth from the standard value), it triggers dynamic calibration and adjusts the sensor sensitivity or algorithm.

[0056] The acceleration data verification subunit is used to re-collect the acceleration data of the device in a static state during dynamic calibration and compare it with the data collected during the initial calibration; if the current acceleration data deviation is large, the sensitivity of the sensor will be adjusted.

[0057] The error correction algorithm subunit is used to automatically adjust the data acquisition algorithm and correct the sensor error according to the deviation between the acceleration data and the standard value; if the sensitivity of the sensor is abnormal under certain environmental conditions, the acquisition threshold will be adjusted to reduce the impact of environmental factors.

[0058] The posture correction subunit is used to prompt students to readjust the angle of the device if the tilt angle of the device changes significantly during the pressing process (such as the phone is not placed stably) to avoid measurement errors caused by device posture problems.

[0059] The calibration feedback subunit is used to remind trainees to adjust the device posture or pressing behavior through audio, visual or vibration feedback during the dynamic calibration process to ensure the accuracy of the calibration data.

[0060] The error correction unit includes a deviation monitoring subunit, a correction subunit, an environmental adaptability adjustment subunit and an error correction feedback subunit. The deviation monitoring subunit is used to monitor the changes in acceleration data during each press and compare the difference between current data and historical data; if the error is found to exceed the preset threshold (such as the deviation exceeds 5%), the error correction algorithm subunit will be automatically started.

[0061] The correction subunit is used to process real-time acceleration data through a smoothing algorithm to reduce errors caused by short-term fluctuations. When it is found that the data fluctuates too much, it automatically adjusts the calculation thresholds of frequency and depth to ensure the accuracy of feedback.

[0062] The environmental adaptability adjustment subunit is used to dynamically adjust the sensitivity of the sensor under different environmental conditions (such as temperature changes, humidity, etc.) to reduce the impact of environmental factors on measurement accuracy.

[0063] The error correction feedback subunit is used to display error prompts on the screen, provide adjustment suggestions, and prompt trainees to make adjustments through voice and vibration if the error is detected to be beyond the normal range. Visual feedback: If the error detected is beyond the normal range, the system will display an error prompt on the screen (such as "The device posture is incorrect, please adjust") and provide adjustment suggestions; Audio feedback: The system will prompt students to make adjustments through voice prompts, such as "Please place the phone steadily"; Vibration feedback: If the error is large, the system will issue a short vibration prompt to remind students to recalibrate the device.

[0064] Furthermore, the hardware interface and support module is used to ensure the compatibility of the system on different models of smartphones, support the connection of external devices, and provide battery management and energy saving functions. The hardware interface and support module includes a compatibility support unit, an external device support unit, and a battery management and energy saving unit. Among them: Compatibility support unit, used to support different models of smartphones and ensure accurate reading of sensor data.

[0065] The external device support unit is used to connect auxiliary devices such as Bluetooth headsets and vibration devices to provide more diverse feedback methods.

[0066] The battery management and energy-saving unit is used to optimize system power consumption so that the device can continue to operate efficiently during long-term use.

[0067] Based on the above system, this application provides a teaching method for cardiopulmonary resuscitation compression using mobile phone gravity sensing, including the following steps: Using the above teaching system, three-dimensional acceleration data of trainees performing cardiopulmonary resuscitation compressions are collected; Calculate the depth, frequency and strength of compression based on the collected data; Provides real-time feedback through audio, visual and vibration based on preset CPR compression standards; Provide standard cardiopulmonary resuscitation operation videos, action breakdown and tips, as well as error correction and improvement suggestions; Perform initial calibration, dynamic calibration and error correction on the data output by the gravity sensing module to ensure the accuracy and reliability of the data; According to the students' learning progress, teaching content and guidance are provided in stages until the students complete all learning tasks and pass the systematic comprehensive evaluation.

[0068] Those skilled in the art should understand that the embodiments of the present invention described above and shown in the accompanying drawings are only examples and do not limit the present invention. The purpose of the present invention has been fully and effectively achieved. The functions and structural principles of the present invention have been demonstrated and explained in the embodiments, and the embodiments of the present invention may be deformed or modified in any way without departing from the principles.

Claims

1. A teaching system for cardiopulmonary resuscitation using mobile phone gravity sensing, characterized in that: include, The gravity sensing module is used to collect the three-dimensional acceleration data of the trainee during CPR compression in real time through the gravity sensor of the smartphone, and calculate the depth, frequency and strength of the compression; A real-time feedback module, connected to the gravity sensing module, for receiving the compression data output by the gravity sensing module and providing real-time feedback in audio, visual and vibration modes according to a preset cardiopulmonary resuscitation compression standard; The compression frequency is calculated by monitoring the time interval between two consecutive compression peaks. The number of compressions per minute = 60 seconds / the time interval between two compression peaks (seconds). The compression depth is calculated by the change in acceleration data. Teaching guidance module, which is used to provide CPR standard operation videos, action breakdown and prompts, as well as error correction and improvement suggestions; The data calibration and verification module is used to perform initial calibration, dynamic calibration and error correction on the data output by the gravity sensing module to ensure the accuracy and reliability of the data; Hardware interfaces and support modules are used to ensure system compatibility on different models of smartphones, support the connection of external devices, and provide battery management and energy saving functions.

2. The teaching system for performing cardiopulmonary resuscitation using mobile phone gravity sensing according to claim 1, characterized in that: The gravity sensing module also includes: A sensor data acquisition unit, for collecting three-dimensional acceleration data in real time using an accelerometer and a gyroscope of a smartphone; A data processing unit, used to process acceleration data, analyze compression frequency and depth, and perform real-time comparison according to standard setting range values; The feedback output unit is used to give prompts through sound or vibration when it is detected that the compression depth or frequency does not meet the standards.

3. The teaching system for performing cardiopulmonary resuscitation using mobile phone gravity sensing according to claim 1, characterized in that: The real-time feedback module also includes: A real-time data monitoring unit, used to synchronize the student's pressing data with the data interface of the gravity sensing module in real time; A threshold judgment and feedback generation unit, used to judge whether the current operation meets the standard according to the standard of cardiopulmonary resuscitation compression, and generate corresponding feedback; Feedback logic design unit is used to ensure that feedback information is timely and effective.

4. The teaching system for performing cardiopulmonary resuscitation using mobile phone gravity sensing according to claim 1, characterized in that: The teaching guidance module also includes: The video content and prompt voice integration unit is used to integrate teaching videos and voice prompts. Students can refer to the video demonstration when practicing and make corrections according to the system prompts. Intelligent prompt design unit, used to dynamically adjust the guidance content according to the actual operation of the students, to ensure the personalization and pertinence of the teaching process; The error monitoring and feedback unit is used to identify incorrect operations and provide timely correction suggestions through real-time analysis of trainees' pressing data.

5. The teaching system for performing cardiopulmonary resuscitation using mobile phone gravity sensing according to claim 1, characterized in that: The data calibration and verification module also includes: Initial calibration unit, used to perform a basic calibration when the system starts up to ensure that the sensor works properly; Dynamic calibration unit, used for regular calibration and real-time adjustment during use to ensure accuracy under long-term use; An error correction unit, used to make corrections based on the monitored errors to ensure the accuracy of teaching feedback; The verification mechanism unit is used to verify the accuracy of the system through known standard data and promptly prompt trainees to adjust operations or equipment postures.

6. The teaching system for performing cardiopulmonary resuscitation using mobile phone gravity sensing according to claim 5, characterized in that: The initial calibration unit also includes: The equipment monitoring and static acceleration acquisition subunit is used to perform static acceleration monitoring when the system is started and collect acceleration data in a stationary state; The system tilt angle confirmation subunit is used to determine whether the device is in a suitable posture; The calibration data storage subunit is used to save the initial calibration data as reference values, and the subsequent calibration process is adjusted based on these data.

7. The teaching system for performing cardiopulmonary resuscitation using mobile phone gravity sensing according to claim 5, characterized in that: The dynamic calibration unit also includes: A calibration trigger condition subunit, used to set the trigger conditions for periodic calibration and pressing behavior calibration; The acceleration data verification subunit is used to re-collect the acceleration data of the device in a static state during dynamic calibration and compare it with the data collected during the initial calibration; The error correction algorithm subunit is used to automatically adjust the data acquisition algorithm and correct the error of the sensor according to the deviation between the acceleration data and the standard value; The posture correction subunit is used to prompt the trainee to readjust the angle of the device if the tilt angle of the device changes significantly during the pressing process; The calibration feedback subunit is used to remind trainees to adjust the device posture or pressing behavior through audio, visual or vibration feedback during the dynamic calibration process.

8. The teaching system for performing cardiopulmonary resuscitation using mobile phone gravity sensing according to claim 5, characterized in that: The error correction unit also includes: Deviation monitoring subunit, used to monitor the change of acceleration data at each press and compare the difference between current data and historical data; The correction subunit is used to process real-time acceleration data through a smoothing algorithm to reduce errors caused by short-term fluctuations. When it is found that the data fluctuates too much, it automatically adjusts the calculation thresholds of frequency and depth to ensure the accuracy of feedback; Environmental adaptability adjustment subunit, used to dynamically adjust the sensitivity of the sensor under different environmental conditions to reduce the impact of environmental factors on measurement accuracy; The error correction feedback subunit is used to display error prompts on the screen, provide adjustment suggestions, and prompt trainees to make adjustments through voice and vibration if the error detected is beyond the normal range.

9. The teaching system for performing cardiopulmonary resuscitation using mobile phone gravity sensing according to claim 1, characterized in that: The hardware interface and support module also includes: Compatibility support unit, used to support different models of smartphones and ensure accurate reading of sensor data; External device support unit, used to connect Bluetooth headsets and vibration device auxiliary equipment to provide more diverse feedback methods; The battery management and energy-saving unit is used to optimize system power consumption so that the device can continue to operate efficiently during long-term use.

10. A teaching method for a teaching system for cardiopulmonary resuscitation using the gravity sensing function of a mobile phone as claimed in any one of claims 1 to 9, characterized in that: The following steps are involved: Using the teaching system described in any one of claims 1 to 9, collecting three-dimensional acceleration data of the trainee when performing cardiopulmonary resuscitation compression; Calculate the depth, frequency and strength of compression based on the collected data; Provides real-time feedback through audio, visual and vibration based on preset CPR compression standards; Provide standard cardiopulmonary resuscitation operation videos, action breakdown and tips, as well as error correction and improvement suggestions; Perform initial calibration, dynamic calibration and error correction on the data output by the gravity sensing module to ensure the accuracy and reliability of the data; According to the students' learning progress, teaching content and guidance are provided in stages until the students complete all learning tasks and pass the systematic comprehensive evaluation.

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