Cloud real-time interaction method for remote intelligent pulse diagnosis

Abstract

The invention discloses a cloud real-time interaction method for remote intelligent pulse diagnosis. The system has the functions of network and Bluetooth data interaction, data real-time display and data storage, and the doctor end and the patient end realize real-time interconnection with the cloud server through a TCP protocol. According to the cloud real-time interaction method, the traditional Chinese medicine'three parts and nine weather 'pulse diagnosis process is remotely achieved, meanwhile, cloud data mutual transmission delay is low, connection is stable, and the problem that double-end interaction of a traditional intelligent pulse diagnosis system is difficult is effectively solved; the bracelet can be an air bag pressurization type bracelet, a linear motor drive type bracelet, an intelligent material deformation type pulse detection bracelet and the like, and the application range is wide.

Description

Technical Field

[0001] The present invention relates to the field of intelligent pulse diagnosis in traditional Chinese medicine, and in particular to a cloud-based real-time interactive method for remote intelligent pulse diagnosis. Background Art

[0002] With the development of globalization and technology, the medical and health field is facing unprecedented opportunities and challenges. The traditional medical model is unable to cope with the problems of aging population, uneven medical resources, low diagnostic efficiency, etc. In this context, TCM remote pulse diagnosis and smart medicine came into being, aiming to use modern scientific and technological means to improve the quality and efficiency of medical services and achieve the optimal allocation of medical resources.

[0003] The development of intelligent pulse diagnosis technology benefits from technological breakthroughs in many fields. First, the continuous advancement of sensor technology provides key hardware support for intelligent pulse diagnosis. High-precision pressure sensors, displacement sensors, etc. can more accurately sense the subtle changes in the pulse, convert the pulse into digital signals, and provide a basis for subsequent analysis and processing. Secondly, the development of signal processing technology makes the extraction, analysis and feature extraction of pulse signals more accurate and efficient. Through filtering, amplification, denoising and other processing methods, interference signals can be removed and the key features of the pulse can be highlighted. Furthermore, the application of artificial intelligence and machine learning technology has brought revolutionary changes to intelligent pulse diagnosis. Through the study and training of a large amount of pulse data, artificial intelligence algorithms can establish a correlation model between pulse and disease, and realize automatic recognition and diagnosis of pulse.

[0004] In the medical field, intelligent pulse diagnosis technology is of great significance. On the one hand, it can provide doctors with more objective and accurate diagnostic basis, and assist doctors in making more scientific diagnosis and treatment decisions. Especially for the diagnosis of some difficult diseases, intelligent pulse diagnosis technology can provide additional information and clues to improve the accuracy of diagnosis. On the other hand, intelligent pulse diagnosis technology can realize remote diagnosis and health monitoring, and provide patients with more convenient medical services. Patients can use intelligent pulse diagnosis equipment to detect pulse at home and upload the data to the cloud. Doctors can analyze and diagnose remotely and give timely advice and treatment plans.

[0005] As a product of the combination of traditional Chinese medicine and modern technology, TCM remote pulse diagnosis aims to solve the limitations of traditional pulse diagnosis in terms of accuracy, repeatability and popularity. Smart healthcare can achieve rapid transmission and in-depth mining of medical information, break the limitations of time and space, and improve the efficiency and accuracy of medical services. The existing intelligent pulse diagnosis system lacks the function of remote real-time interaction between the doctor and the patient. Therefore, a remote real-time interaction method is urgently needed to solve this problem. Summary of the invention

[0006] The purpose of the present invention is to solve the problem that it is difficult for traditional intelligent pulse detection systems to achieve real-time interaction between patient-side users and doctor-side users, and to provide a cloud-based real-time interaction method for remote intelligent pulse diagnosis.

[0007] In order to achieve the above object, the present invention adopts the following technical scheme:

[0008] The present invention includes a patient end and a doctor end, and the two ends are interconnected and interacted in real time through a cloud server; the patient end receives fingering data from the doctor end through the cloud server and transmits pulse data to the doctor end, and the doctor end receives pulse data from the patient end through the cloud server and transmits fingering data to the patient end, thereby realizing real-time interaction of remote intelligent pulse diagnosis.

[0009] The patient side includes a patient-side pulse collection bracelet, a patient-side main control board, and a patient-side user module. The pulse collection bracelet collects pulse pressure signals at the three positions of Cun, Guan, and Chi on the radial part of the patient's wrist through three flexible pulse sensors. The pulse pressure signal is converted into a voltage signal through a signal processing and amplification module integrated on the main control board of the pulse collection bracelet. The main control board transmits the pulse signal to the patient-side user module through the Bluetooth module for real-time waveform display; the patient-side user module transmits the pulse signal to the doctor-side user module in real time through the cloud server, and at the same time receives the pulse taking and compression signal remotely applied by the doctor from the cloud server in real time, and feedback controls the quantitative inflation of the airbag to simulate the remote doctor's compression force in real time.

[0010] The doctor's side includes a doctor's pulse reproduction bionic hand, a doctor's main control board, and a doctor's user module. The main control board first collects the pulse taking and pressing pressure applied by the doctor's three fingers through three sensors, and then converts the force value into a voltage signal and transmits it to the patient's side through the cloud server. The patient's pulse pressure application device takes the pulse and presses, and transmits the measured pulse signal back to the doctor's side in real time. The doctor's side reproduces the real-time fluctuating pulse signal based on the equivalent relationship between the pulse signal amplitude and the voice coil motor voltage mechanics.

[0011] The pulse collection bracelet on the patient side receives the pulse taking and pressurization signal sent back by the doctor in real time through the cloud server, and controls the on and off of the solenoid valve integrated in the pulse collection bracelet through the patient-side main control board, and then controls the inflation of the small airbag installed on the strap, so that the doctor can remotely take the pulse and apply pressure.

[0012] The quantitative inflation of the airbag adopts a negative feedback control algorithm. Based on the data sent back by the pulse sensor, it extracts the static pressure value, compares the value with the pressure applied remotely by the doctor in real time, and feedback controls the state of the air valve to enable the doctor to accurately apply pressure remotely.

[0013] The pulse reproduction bionic hand on the doctor's side first calibrates the signal amplitude of the force value collected by the pulse sensor and the PWM duty cycle of the voice coil motor, and then loads different forces on the pulse sensor to determine the relationship between the signal of the pulse sensor on the patient's side and the PWM duty cycle that controls the quantitative action of the voice coil motor on the doctor's side, thereby realizing remote quantitative reproduction of the patient's remote pulse.

[0014] The main control boards on the patient side and the doctor side are designed with STM32F1 chip and HC-05 Bluetooth, and the Android application is matched with it. It communicates with the hardware through the Bluetooth serial interface. The patient-side and doctor-side user modules use the TCP protocol to communicate with the cloud server over the network, realizing two-way connection between the data on both ends and the cloud server.

[0015] The main control board includes pressure signal ADC conversion, Bluetooth communication, peripheral IO voltage quantitative output, reset and debugging, and power supply voltage amplification.

[0016] The user modules on the patient side and the doctor side dynamically display the Cun, Guan, and Chi pulse data received via Bluetooth as waveforms in real time. They also contain filtering options and perform filtering based on the median filtering algorithm to match the acquisition device in real time.

[0017] The patient-side and doctor-side user modules are developed using Android studio tools in the Windows system on a PC, and the cloud server development environment is python.

[0018] Compared with the prior art, the present invention has the following beneficial technical effects:

[0019] The present invention discloses a cloud-based real-time interactive method for remote intelligent pulse diagnosis. It has network and Bluetooth data interaction, real-time data display and data storage functions, and the doctor end and the patient end realize remote real-time interconnection with the cloud server through the TCP protocol. Both end main control boards are designed with STM32F1 chip and HC-05 Bluetooth module, communicate with hardware through Bluetooth serial interface, and the double-end user module uses TCP protocol to communicate with the cloud server over the network. The present invention remotely realizes the traditional Chinese medicine "three parts and nine lords" pulse diagnosis process, and at the same time, the cloud-based data mutual transmission delay is low and the connection is stable, which effectively solves the problem of difficult double-end interaction of traditional intelligent pulse diagnosis systems. The cloud-based real-time interactive method is suitable for different device solutions, such as airbag pressurization type, linear motor drive type, smart material variable type pulse detection bracelet, etc., and has a wide range of applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is the overall framework diagram of the patient-side software of the cloud-based real-time interactive method for remote intelligent pulse diagnosis described in the present invention;

[0021] Figure 2It is the overall framework diagram of the doctor-side software of the cloud-based real-time interactive method for remote intelligent pulse diagnosis described in the present invention;

[0022] Figure 3-a This is the first step of the process test of a cloud-based real-time interactive method for remote intelligent pulse diagnosis of the present invention;

[0023] Figure 3-b This is the second step of the process test of a cloud-based real-time interactive method for remote intelligent pulse diagnosis of the present invention;

[0024] Figure 3-c This is the third step of the process test of a cloud-based real-time interactive method for remote intelligent pulse diagnosis of the present invention;

[0025] Figure 3-d This is step 4 of the process test of a cloud-based real-time interactive method for remote intelligent pulse diagnosis of the present invention;

[0026] Figure 3-e This is step 5 of the process test of a cloud-based real-time interactive method for remote intelligent pulse diagnosis of the present invention;

[0027] Figure 3-f This is the sixth step of the process test of a cloud-based real-time interactive method for remote intelligent pulse diagnosis of the present invention;

[0028] Figure 3-g This is the seventh step of the process test of a cloud-based real-time interactive method for remote intelligent pulse diagnosis of the present invention;

[0029] Figure 3-h This is the eighth step of the process test of a cloud-based real-time interactive method for remote intelligent pulse diagnosis of the present invention;

[0030] Figure 3-i This is the ninth step of the process test of a cloud-based real-time interactive method for remote intelligent pulse diagnosis of the present invention;

[0031] Figure 3-j This is a cloud-based real-time interactive method for remote intelligent pulse diagnosis. DETAILED DESCRIPTION

[0032] In order to make the purpose, advantages and technical solutions of the present invention more obvious, the technical solutions in the embodiments of the present invention will be described in more complete and detailed manner below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0033] Reference Figure 1As shown in Figure 3, a cloud-based real-time interactive method for remote intelligent pulse diagnosis: first, the patient wears a pulse collection bracelet and logs in to the patient user module. The pulse collection bracelet collects pulse pressure signals at the three positions of Cun, Guan, and Chi on the radial part of the patient's wrist through three flexible pulse sensors; secondly, the pulse pressure signal is converted into a voltage signal through a signal processing and amplification module integrated on the main control board of the pulse collection bracelet; then, the main control board transmits the pulse signal to the patient user module through the Bluetooth module for real-time waveform display; then, the user module transmits the pulse signal to the cloud server; then, the cloud server sends the pulse signal to the cloud server. The signal is transmitted to the user module on the doctor's side; then, the user module on the doctor's side transmits the pulse signal to the main control board of the pulse reproduction bionic hand through the Bluetooth module; finally, the main control board controls the three voice coil motors located on the bionic hand to reproduce the pulse in real time according to the real-time changes of the pulse signal, thereby realizing the doctor's remote and real-time perception of the patient's pulse; conversely, the doctor's pulse reproduction bionic hand is designed with three-way finger technique acquisition sensors, which transmit the doctor's finger technique data back to the patient's pulse acquisition bracelet remotely and in real time through the above process, and the main control board controls the solenoid valve on the pulse acquisition bracelet to inflate and deflate the airbag in real time, thereby realizing the doctor's remote finger technique application to the patient in real time.

[0034] The patient-side and doctor-side user modules of the present invention are developed using Android studio tools in the Windows system on a PC, using Java as the development language; the cloud server development environment is python, using the python language. The operating environment requires the Android minimum SDK version to be 7.0, and the Android version used in the actual machine test is 14. The operating device requires a Bluetooth connection function, which can perform traditional Bluetooth serial protocol communication, and the application layer can use the Socket interface for TCP protocol network communication.

[0035] The pulse collection bracelet on the patient side and the pulse reproduction bionic hand on the doctor side are both designed with STM32F1 chip and HC-05 Bluetooth module. The Android application is matched with it, communicates with the hardware through the Bluetooth serial interface, and uses the TCP protocol to communicate with the cloud server. The cloud server is built in the Alibaba Cloud server.

[0036] The user modules of the patient and doctor end both include network and Bluetooth data interaction, real-time data display and data storage functions. Network data interaction includes receiving the "Cun, Guan, Chi" pulse data sent by the patient end through the cloud server, and sending the pulse diagnosis and compression data collected by the pulse reproduction bionic hand of the doctor end through the cloud server to the corresponding patient end; the Bluetooth data interaction function can receive the collected pulse diagnosis and compression data from the doctor end device, and send the "Cun, Guan, Chi" pulse data sent from the cloud to the doctor end device at the same time. The data transmission delay is low, the connection is stable, and duplex communication can be performed, and the received data can be spliced ​​and divided into data packets; the data display can dynamically display the "Cun, Guan, Chi" pulse data received through the cloud as three waveform graphs in real time, and it also contains filtering options, which can match the collection device for filtering, and formulate a suitable dynamic window to display the waveform according to the actual data range and receiving frequency; the network data interaction module uploads the data received through Bluetooth to the cloud server in real time, and receives the data sent by the corresponding user end at the same time, and optimizes the use of network connection communication according to the actual design interaction mode; the data storage can choose to save the waveform data when receiving Bluetooth pulse data, and can visualize the stored data.

[0037] The pulse collection bracelet on the patient side adopts a three-way pulse sensor design, and through the flexible pressurization of the airbag, it can realize the effective collection of pulse signals at the three points of Cun, Guan, and Chi on the radial artery of the human wrist; it adopts a watchband structure design, and through the air pump, solenoid valve, and airbag, the doctor can remotely take the pulse and apply pressure; it adopts a negative feedback control algorithm, based on the data sent back by the pulse sensor, extracts the static pressure value, compares the value with the pressure applied remotely by the doctor in real time, and feedback controls the air valve state to realize the doctor's remote and precise application of pressure.

[0038] The patient-side user module is used to upload the pulse diagnosis data in real time via Bluetooth-cloud and display the collected "Cun, Guan, Chi" pulse waveforms on the Android device in real time. At the same time, the pulse diagnosis and compression data of the doctor's side is sent to the Android device through the cloud server, and then sent to the pulse collection bracelet on the patient side via Bluetooth, realizing the remote pulse pressure application function.

[0039] The pulse reproduction bionic hand at the doctor's end includes bionic skin, bionic blood vessels, bionic hands, voice coil motors and finger position acquisition sensors. The pulse taking and pressing pressure applied by the doctor's three fingers is firstly collected through three sensors, and then the force value is converted into a voltage signal and transmitted to the patient end. The pulse pressure application device at the patient end takes the pulse and presses, and transmits the measured pulse signal back to the doctor end in real time. The doctor end reproduces the real-time fluctuating pulse signal according to the equivalent relationship between the pulse signal amplitude and the voltage mechanics of the voice coil motor; the signal amplitude of the force value collected by the pulse sensor and the PWM duty cycle of the voice coil motor are first calibrated, and then different forces are loaded on the pulse sensor, so as to determine the relationship between the sensor signal and the PWM duty cycle that controls the quantitative action of the voice coil motor in this device, so as to realize the quantitative reproduction of the patient's remote pulse.

[0040] The doctor-side user module receives the "Cun, Guan, and Chi" pulse data sent from the patient-side through the cloud server, displays the pulse data waveform in real time when receiving it, and sends the pulse data to the doctor-side pulse reproduction bionic hand via Bluetooth in real time for pulse reproduction; at the same time, the pulse diagnosis and compression data collected by the doctor-side pulse reproduction bionic hand is received via Bluetooth, and sent to the corresponding patient-side user module through the cloud server, realizing the remote pulse reproduction function.

[0041] Step 1: After the client software is installed using the .apk file, the interface is displayed for the first time when it is opened. Figure 3-a As shown, click the REFRESH button in the upper right corner, a system permission granting pop-up window will pop up, click OK to grant Bluetooth usage permission. If the user device has not bound a Bluetooth device, the interface will switch. If Bluetooth is not turned on, it will display "Bluetooth disabled"; click the upper right menu bar and select Bluetooth settings to open the system Bluetooth interface of the user device, and select the corresponding Bluetooth device in the available devices for pairing and binding.

[0042] Step 2: After pairing and binding is completed, the interface will be as follows Figure 3-b As shown, the Bluetooth device list options are displayed in the middle of the interface. The first line of each option displays the device name in large fonts, and the second line is the hardware Mac address.

[0043] Step 3. The "Server Connection" button at the bottom of the interface is the cloud server connection button. When the cloud server is working, click this button to connect or disconnect with the server. Figure 3-c To prevent the server from being unable to respond effectively due to clicking too quickly, this button has a click interval limit. If you click too quickly, a short notification will pop up to inform the user that the click is too fast and the operation is invalid.

[0044] Step 4: Enter the Bluetooth device connection operation. The user can click the "HC-05" option in the middle area of ​​the interface to connect the corresponding Bluetooth device. After clicking, the interface switches to the data display interface, such as Figure 3-dAs shown. This interface contains the following main controls: the clear button in the upper right corner, click it to clear the waveform display and running status text area; there are three pulse waveform display areas in the middle area, which dynamically display the pulse waveform data at the "Cun, Guan, and Chi" points collected by the corresponding hardware; there are two text display areas on the left and right below, the left text area displays the software running status, mainly including the Bluetooth connection status and the network connection status, and the right text area is the peer end connected to the cloud server, that is, the connection information of the doctor end; the four buttons at the bottom, from left to right, are "Start / Pause", "Save", "Filter", and "Get List"; after successfully connecting to the cloud server, it will display "Identity information added successfully", as shown Figure 3-d As shown, it means that the corresponding identity is added to the cloud server and can be used by subsequent cloud server connection transaction logic.

[0045] Step 5. Click the Clear button in the upper right corner to clear the waveform display and text display on this interface. Figure 3-e Click the "Start / Pause" button below to control the switch of Bluetooth data reception and the dynamic update of the waveform display area. Click "Start" to start Bluetooth data reception and dynamically update the waveform display. Click "Pause" to turn off Bluetooth data reception and stop updating the waveform display. When paused, you can perform operations such as single-finger sliding and double-finger zooming in the three waveform display areas. Figure 3-e As shown, the upper red curve has been slid with one finger, and the lower blue curve has been zoomed in with two fingers. Clicking the "Filter" button can control the filter switch. This function needs to match the working conditions of the corresponding hardware acquisition. When using it, you need to analyze the target scene and change the corresponding code to change the filtering algorithm.

[0046] Step 6, the "Save" button is a switch button, which switches to whether to save when clicking the "Pause" button, that is, switching to the save state, and then clicking "Pause" to turn off Bluetooth data reception, saves the three waveform data received from the start of Bluetooth connection or the last start to the pause. Figure 3-f As shown in the figure, when the save is turned on or canceled, a short notification pops up below to inform the user that the save state has been turned on or canceled. When the save state is turned on, when the "Pause" button is clicked to save, a short notification "Save Successfully" pops up below to inform the user that the target data has been successfully saved.

[0047] Step 7. After saving successfully, click the "Data Record" option in the bottom navigation bar to enter the data record navigation interface. Figure 3-g As shown; click the "Refresh" button below to refresh the list display of the data saving record area. Each list option is the saving time of the saved record, which is displayed in the format of "year-month-day hour: minute: second".

[0048] Step 8. Click the corresponding list option, "2024-06-29 17:56:30" option, and a floating window will pop up, such as Figure 3-h As shown, a waveform graph of the saved data is displayed in the floating window; zooming and sliding operations can be performed in the floating window, and after zooming in, the window can be slid in all directions to view the waveform data of the area of ​​interest.

[0049] Step 9. When the doctor is connected to the remote intelligent pulse diagnosis system, click the "Get List" button to check whether there is a corresponding doctor on the cloud server. If there is no matching doctor online, the cloud server connection status text will be displayed as "No customer online". Figure 3-i As shown; if there is a doctor side that can be matched, its "IP address" and port number will be displayed, and the text display in the button will change to "Re-acquire list". Click again to interact with the cloud server to update the list options.

[0050] Step 10. Click the list option and select the corresponding doctor terminal for pairing. Figure 3-j As shown, when the pairing is successful, the interface will clearly display that the pairing is successful. At this time, the original "Get List" button will change to "Disconnect Matching". Click the "Disconnect Matching" button to disconnect the connection with the corresponding doctor and return to the state after obtaining the list. Then click "Re-obtain List" to return to the initial "Obtain List" state and re-match.

[0051] The present invention solves the problem of two-end interaction in the current traditional intelligent pulse diagnosis system and can be widely used in daily health monitoring, telemedicine and clinical pulse diagnosis.

[0052] The above content is only for explaining the technical idea of ​​the invention of this application and cannot be used as a basis for limiting the protection scope of the invention. Any modifications and substitutions made in the technical scheme according to the design concepts and technical features proposed in the present invention are within the protection scope of the claims of the present invention.

Claims

1. A cloud-based real-time interactive method for remote intelligent pulse diagnosis, characterized in that: It includes the patient side and the doctor side, and the two sides are interconnected and interacted in real time through the cloud server; the patient side receives the finger movement data from the doctor side through the cloud server and transmits the pulse data to the doctor side, and the doctor side receives the pulse data from the patient side through the cloud server and transmits the finger movement data to the patient side, thus realizing real-time interaction of remote intelligent pulse diagnosis.

2. The cloud-based real-time interactive method for remote intelligent pulse diagnosis according to claim 1, characterized in that: The patient end includes a patient-end pulse collection bracelet, a patient-end main control board, and a patient-end user module. The pulse collection bracelet collects pulse pressure signals at three positions of the radial part of the patient's wrist, namely, Cun, Guan, and Chi, through three flexible pulse sensors. The pulse pressure signals are converted into voltage signals through a signal processing and amplification module integrated on the main control board of the pulse collection bracelet. The main control board transmits the pulse signal to the patient-end user module through a Bluetooth module for real-time waveform display; the patient-end user module transmits the pulse signal to the doctor-end user module in real time through a cloud server, and at the same time receives the pulse taking and compression signals remotely applied by the doctor from the cloud server in real time, and feedback controls the quantitative inflation of the airbag to simulate the remote doctor's compression force in real time.

3. The cloud-based real-time interactive method for remote intelligent pulse diagnosis according to claim 1, characterized in that: The doctor end includes a doctor end pulse reproduction bionic hand, a doctor end main control board, and a doctor end user module. The main control board first collects the pulse taking and pressing pressure applied by the doctor's three fingers through a three-way sensor, and then converts the force value into a voltage signal and transmits it to the patient end through a cloud server. The patient end pulse pressure application device takes the pulse and presses, and transmits the measured pulse signal back to the doctor end in real time. The doctor end reproduces the real-time fluctuating pulse signal based on the equivalent relationship between the pulse signal amplitude and the voltage mechanics of the voice coil motor.

4. The cloud-based real-time interactive method for remote intelligent pulse diagnosis according to claim 2, characterized in that: The pulse collection bracelet on the patient side receives the pulse taking and pressurization signal sent back by the doctor side in real time through the cloud server, and controls the on and off of the solenoid valve integrated in the pulse collection bracelet through the main control board on the patient side, thereby controlling the inflation of the small airbag installed on the strap, so that the doctor can remotely take the pulse and apply pressure.

5. The cloud-based real-time interactive method for remote intelligent pulse diagnosis according to claim 2, characterized in that: The quantitative inflation of the airbag adopts a negative feedback control algorithm, which extracts the static pressure value based on the data sent back by the pulse sensor, compares the value with the pressure applied remotely by the doctor in real time, and feedback controls the valve state to enable the doctor to accurately apply the pressure remotely.

6. The cloud-based real-time interactive method for remote intelligent pulse diagnosis according to claim 3, characterized in that: The doctor-side pulse reproduction bionic hand first calibrates the signal amplitude of the force value collected by the pulse sensor and the PWM duty cycle of the voice coil motor, then loads different forces on the pulse sensor, determines the relationship between the signal of the patient-side pulse sensor and the PWM duty cycle that controls the quantitative action of the doctor-side voice coil motor, and realizes remote quantitative reproduction of the patient's remote pulse.

7. The cloud-based real-time interactive method for remote intelligent pulse diagnosis according to claim 2 or 3, characterized in that: The patient-side and doctor-side main control boards are designed with STM32F1 chips and HC-05 Bluetooth, and the Android application is matched with them. They communicate with the hardware through the Bluetooth serial interface. The patient-side and doctor-side user modules use the TCP protocol to communicate with the cloud server over the network, realizing two-way connection between the dual-end data and the cloud server.

8. The cloud-based real-time interactive method for remote intelligent pulse diagnosis according to claim 7, characterized in that: The main control board includes pressure signal ADC conversion, Bluetooth communication, peripheral IO voltage quantitative output, reset and debugging, and power supply voltage amplification.

9. The cloud-based real-time interactive method for remote intelligent pulse diagnosis according to claim 2 or 3, characterized in that: The patient-side and doctor-side user modules dynamically display the Cun, Guan, and Chi pulse data received via Bluetooth in real time as a waveform graph, and also contain filtering options, and perform filtering based on the median filtering algorithm and real-time matching of the collection device.

10. The cloud-based real-time interactive method for remote intelligent pulse diagnosis according to claim 2 or 3, characterized in that: The patient-side and doctor-side user modules are developed using Android studio tools in the Windows system on a PC, and the cloud server development environment is python.

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