WO2022042558A1 - Ecg波形显示方法及其介质和电子设备 - Google Patents

Ecg波形显示方法及其介质和电子设备 Download PDF

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Publication number
WO2022042558A1
WO2022042558A1 PCT/CN2021/114341 CN2021114341W WO2022042558A1 WO 2022042558 A1 WO2022042558 A1 WO 2022042558A1 CN 2021114341 W CN2021114341 W CN 2021114341W WO 2022042558 A1 WO2022042558 A1 WO 2022042558A1
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Prior art keywords
wearing part
wearing
ecg
information
average
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PCT/CN2021/114341
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English (en)
French (fr)
Inventor
杨斌
王朔
陈文娟
熊浩
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华为技术有限公司
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Priority to US18/042,916 priority Critical patent/US20230309896A1/en
Priority to EP21860393.4A priority patent/EP4190230A4/en
Priority to BR112023003475A priority patent/BR112023003475A2/pt
Priority to JP2023512741A priority patent/JP2023539582A/ja
Publication of WO2022042558A1 publication Critical patent/WO2022042558A1/zh

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Definitions

  • the present application relates to the field of electronic technology, and in particular, to an ECG waveform display method and its medium and electronic equipment.
  • An electrocardiogram can reflect a user's health state, for example, an ECG can reflect a heart disease (such as arrhythmia) and the like.
  • ECG electrocardiogram
  • a heart disease such as arrhythmia
  • health detection functions such as ECG detection can be integrated on wearable devices such as smart watches to monitor the user's heart rate and other physical signs, so as to realize the user's physical status. It can effectively avoid the obstacles of the conduction electronic equipment of the heart or the pathological changes of the myocardium.
  • the ECG waveform is directly related to the position of the left and right hands of the user wearing the wearable device. For example, if a user wears the wearable device on their left hand and then touches the electrodes of the wearable device with their right hand, the ECG waveform produced by the wearable device is a positive waveform. Without changing any configuration of the wearable device, if the user wears the wearable device on the right hand and then touches the electrodes of the wearable device with his left hand, the ECG waveform generated by the wearable device is a wrong reverse waveform.
  • the inertial measurement unit built in the wearable device can detect and obtain the deflection angle of the smart wearable device when the user wears it, so as to recognize that the user wears the wearable device on the left hand. Still right hand.
  • the user wears the wearable device for the first time and keeps it still, and immediately uses the ECG detection function it is impossible to judge whether the wearable device is worn by the left and right hands, so it is impossible to determine whether the ECG waveform is displayed normally.
  • the ECG waveform generated by the wearable device is compared with a preset reference waveform, so as to identify Whether the user wears the wearable device on the left or right hand.
  • a preset reference waveform so as to identify Whether the user wears the wearable device on the left or right hand.
  • the characteristics of the ECG waveform generated by the wearable device are similar to those generated when the user with a normal heart position wears the wearable device on the right hand. Misjudgments are prone to occur.
  • the embodiments of the present application provide an ECG detection method and device, a medium and an electronic device based on left and right hand recognition.
  • an embodiment of the present application provides an ECG waveform display method, the method comprising:
  • the electronic device starts the ECG waveform detection application and collects the ECG waveform
  • the electronic device reads the wearing part data between the electronic device and the user's wrist; the wearing part data is obtained by identifying the wearing part of the IMU;
  • the electronic device determines first wearing part information according to the wearing state data, where the first wearing part information includes a determined state and an uncertain state; the determined state is a first determined state or a second determined state;
  • the electronic device obtains the second wearing part information between the electronic device and the user's wrist through the ECG wearing part identification;
  • the electronic device displays the ECG waveform on the display screen according to a display mode corresponding to the definite state.
  • the embodiment of the present application can reduce the misjudgment rate of judging whether the ECG waveform is displayed in the normal display mode, and improve the accuracy of the ECG waveform displayed in the normal display mode.
  • the display screen is displayed in a manner corresponding to the definite state.
  • Displays ECG waveforms including:
  • the electronic device displays the ECG waveform on the display screen in a normal display manner.
  • the display screen is displayed in a manner corresponding to the definite state.
  • Displays ECG waveforms including:
  • the electronic device adjusts the ECG waveform so that the ECG waveform is displayed on the display screen in a normal display manner .
  • the above-mentioned method further includes: in the case that the first wearing part information and the second wearing part information are in a determined state but not the same, performing at least one more ECG wearing Part identification is performed to obtain third wearing part information, and the electronic device displays the ECG waveform on the display screen according to the display mode corresponding to the determined state indicated by the third wearing part information.
  • the IMU wearing part identification and the ECG wearing part identification are used at the same time, and when the wearing information determined by the two are different, the number of ECG wearing part identifications and the proportion of ECG detection confidence are increased, which improves to a certain extent.
  • the above-mentioned method further includes: when the first wearing part information is in an uncertain state, performing ECG wearing part identification to obtain fourth wearing part information, and the electronic The device displays the ECG waveform on the display screen according to the display mode corresponding to the determined state indicated by the fourth wearing position information.
  • the above-mentioned method further includes: in the case that the first wearing part information and the fourth wearing part information are the same and are in an uncertain state, performing at least one more ECG wearing Part identification is performed to obtain fifth wearing part information, and the electronic device displays the ECG waveform on the display screen according to the display mode corresponding to the determined state indicated by the fifth wearing position information.
  • the IMU wearing part identification and the ECG wearing part identification are used at the same time, and when the wearing information determined by the two are different, the number of ECG wearing part identifications and the proportion of ECG detection confidence are increased, which improves to a certain extent.
  • the electronic device determines the first wearing position information according to the wearing state data, including
  • the position reliability of the first wearing part is obtained according to the wearing state data, and the first wearing part information is determined at least according to the position reliability of the first wearing part.
  • the obtaining the position reliability of the first wearing part according to the wearing state data, and at least determining the information of the first wearing part according to the position reliability of the first wearing part including :
  • the first wearing part information is determined according to the first average wearing part position reliability.
  • the wearing part data includes an acceleration value and an attitude angle detected by the IMU, and the obtaining the position reliability of the first wearing part according to the wearing state data includes:
  • the position reliability of the first wearing part is obtained according to the acceleration value and the attitude angle detected by the IMU.
  • the obtaining the position reliability of the first wearing part according to the acceleration value and the attitude angle detected by the IMU includes:
  • the output result of the trained IMU wearing part identification model is the first wearing part position reliability.
  • the second wearing part information obtained by identifying the ECG wearing part includes:
  • the position reliability of the second wearing part is obtained by identifying the wearing part of the ECG, and the second wearing position information is determined at least according to the position reliability of the second wearing part.
  • the second wearing part position reliability is obtained through the ECG wearing part identification, and the second wearing position information is determined at least according to the second wearing part position reliability, including:
  • the second wearing part information is obtained according to the second average wearing part position reliability.
  • the obtaining the position reliability of the second wearing part by identifying the wearing part of the ECG includes:
  • the position reliability of the second wearing part is determined according to the waveform characteristic information of the ECG waveform.
  • the waveform characteristic information of the ECG is input into the trained ECG wearing part recognition model, and the output result obtained from the trained ECG wearing part recognition model is the second wearing part position information.
  • the waveform characteristic information of the ECG waveform includes:
  • QRS area ratio of QR width to RS width, QR height, RS height, P wave amplitude, P wave area (including positive and negative), T wave width and T wave area.
  • performing at least one ECG wearing part identification to obtain third wearing part information includes:
  • the position reliability of the second wearing part and the position reliability of the third wearing part are iteratively processed to obtain the third average wearing part position reliability; wherein, the position reliability of the second wearing part is obtained according to the previous ECG wearing part identification, and the third average wearing part position reliability is obtained. 2.
  • the position reliability of the wearing part corresponds to the information of the second wearing part;
  • the third wearing part information is determined according to the third average wearing part position reliability.
  • the determined state is that the wearing state between the electronic device and the user's wrist is a right-hand wearing state or a left-hand wearing state.
  • an implementation of the present application provides a readable medium, where an instruction is stored on the readable medium, and when the instruction is executed on an electronic device, the instruction causes the machine to execute the ECG waveform display method described in the first aspect above.
  • an electronic device including:
  • memory for storing instructions for execution by one or more processors of the electronic device
  • the processor which is one of the processors of the electronic device, is configured to execute the ECG waveform display method of the first aspect.
  • FIG. 1A shows an application scenario diagram of an ECG waveform display method according to some embodiments of the present application.
  • FIG. 1B shows an application scenario diagram of an ECG waveform display method according to some embodiments of the present application.
  • FIG. 1C shows an application scenario diagram of an ECG waveform display method according to some embodiments of the present application.
  • FIG. 2 shows a structural block diagram of a smart watch according to some embodiments of the present application.
  • FIG. 3 shows a schematic flowchart of a method for displaying an ECG waveform according to some embodiments of the present application.
  • FIG. 4 shows a schematic diagram of a time area of an acquisition period with a preset interval of 200 milliseconds and a step size of 150 milliseconds, according to some embodiments of the present application.
  • Fig. 5 shows a schematic diagram of waveforms of the difference and standard value of attitude angle and the difference and standard value of acceleration changing with time according to some embodiments of the present application.
  • FIG. 6 shows an example of an ECG wearing part identification prompt information display interface diagram according to some embodiments of the present application.
  • FIG. 7 shows a schematic diagram of a segment of ECG waveform according to some embodiments of the present application.
  • FIG. 8 shows an example of an ECG waveform display interface diagram in an abnormal display mode according to some embodiments of the present application.
  • FIG. 9 shows an example of an ECG waveform display interface diagram in a normal display mode according to some embodiments of the present application.
  • SoC electronic on-chip
  • Illustrative embodiments of the present application include, but are not limited to, ECG waveform display methods, media, and electronic devices therefor.
  • FIG. 1A , FIG. 1B and FIG. 1C are diagrams illustrating application scenarios of an ECG waveform display method according to some embodiments of the present application.
  • the wearable device 100 can execute the ECG waveform display method provided by the present application.
  • the wearable device 100 has a built-in ECG detection module, a plurality of electrodes, and an inertial measurement unit (Inertial measurement unit, IMU). Take the wearable device 100 including two electrodes as an example, denoted as the A electrode and the B electrode, wherein, as shown in FIG. shown) is disposed on the lower surface of the wearable device 100 .
  • IMU inertial measurement unit
  • the wearable device 100 when the user wears the wearable device 100 with the built-in ECG detection module for ECG function detection, for example, the user wears the wearable device 100 on his left wrist, at this time, the user's left wrist and the wearable The B electrode on the lower surface of the device 100 is in contact, and the user acts on the icon of the ECG waveform detection APP (Application) that performs ECG detection.
  • the wearable device 100 detects the click operation or After receiving the command to open the ECG APP, start the ECG detection function.
  • the user can use his right finger to contact the A electrode 200 on the side of the wearable device 100.
  • the A electrode 200 and the B electrode form an electrode pair, which can collect detailed information of the user's ventricular depolarization waveform falling through the heart tissue .
  • the ECG detection module performs analog-to-digital conversion, filtering and other processing on the electrical signals collected by the A electrode 200 and the B electrode to generate a single-lead ECG signal of the user.
  • the wearable device 100 displays the user's ECG waveform generated by the ECG detection module on the display screen. As shown in FIG.
  • the ECG waveform is displayed in a normal display manner, for example, the peak of the ECG waveform faces the left-hand side, but when the smart watch 100 is worn by the user on the left-hand wrist, the ECG waveform is The peak of the ECG is facing the right-hand side, so it does not look normal, and the ECG waveform is displayed on the display in an abnormal way.
  • the wearable device 100 determines whether the user wears it on the left hand or the right hand according to the built-in IMU, and further determines whether the user wears it on the left hand or the right hand according to the ECG waveform generated by the ECG detection module, and then according to the ECG waveform generated by the ECG detection module.
  • the judgment result displays the ECG waveform on the display screen in a normal display mode, as shown in Figure 1C, for the convenience of the user.
  • the wearable device 100 can also analyze the user's electrocardiogram according to the ECG waveform generated by the ECG detection module, and display the analysis result on its display screen in the form of text, or play it out in the form of voice , so that users can more intuitively understand the health of their hearts.
  • the wearable device 100 can separately collect ECG data, judge the left and right hands, and display the final ECG waveform or produce an electrocardiogram report according to the judgment results of the left and right hands.
  • FIG. 1A , FIG. 1B and FIG. 1C show the smart watch 100
  • the electronic device suitable for the ECG waveform display method of the present application may be other wrist-worn devices, such as a smart bracelet or other wrist devices. Worn specialized equipment with electrocardiogram measurement capabilities.
  • the processing process described in this application can be performed on a smart bracelet, smart phone, or other devices that can be worn on the wrist, or it can be performed on a smart bracelet, smart phone, Or other wrist-worn devices wirelessly or wiredly connected to mobile phones, tablet computers, PDAs (personal digital assistants, PDAs), laptops and other devices.
  • PDAs personal digital assistants, PDAs
  • FIG. 2 shows a structural block diagram of a smart watch 100 according to some embodiments of the present application.
  • the smart watch 100 includes a touch display screen 101 , a processor 102 , an ECG detection module 103 , electrodes 104 a , electrodes 104 b , a capacitive sensor 105 , an IMU 104 , an infrared spectrum detection unit (Infrared Spectroscopy, IR) 106 , an inertial Measurement unit (Inertial measurement unit, IMU) 107, memory 108, communication module 109, etc.
  • IR Infrared Spectroscopy
  • IMU inertial Measurement unit
  • the touch display screen 101 can be used as a touch panel to collect a user's touch operation on it, and drive a corresponding connection device according to a preset program. For example, a touch operation of the user clicking on the ECG APP icon of the smart watch 100 with a finger is collected.
  • the touch display screen 101 can also be used to display information input by the user or prompt information provided to the user and various menus on the smart watch 100 . For example, the user's ECG waveform detected by the smart watch 100, the user's electrocardiogram report, and the like are displayed.
  • the processor 102 includes a plurality of processing units, and can run the software code of the ECG waveform display method provided by some embodiments of the present application, for example, the wearing position information is determined through the IMU wearing position identification and the ECG wearing position identification, so as to determine whether the ECG waveform is Normal display mode, if the ECG waveform is not in the normal display mode, adjust the ECG waveform to the ECG waveform of the normal display mode, the user's ECG report, etc.
  • the ECG detection module 103 is used to process the electrical signals of the human body detected by the electrodes 104a and 104b into an ECG waveform.
  • the ECG detection module 103 may include one or more filters, or the ECG detection module 103 may be connected with one or more filters.
  • One or more filters may be configured to filter the human body electrical signals detected by the electrodes 104a and 104b.
  • the ECG detection module 103 may be configured with the frequency domain bandwidth of one or more filters.
  • the frequency bandwidth of the filter is 0.5-40Hz
  • the filter can filter its input signal (such as the electrical signals detected by the electrodes 104a and 104b) to obtain electrical signals in the range of 0.5-40Hz, and electrical signals of other frequencies are Filtered.
  • the above function of processing electrical signals detected by electrodes 104a and 104b into ECG waveforms may be performed by other components, components or circuits, which may be independent of processor 103 different parts.
  • Other components, components or circuits may be constructed by separate devices (such as semiconductor devices), for example, other components, components or circuits may be integrated circuits (ICs), microcircuits (microcircuits) with integrated ECG detection functions ), chip (chip), microchip (microchip), etc., which are not limited in this application.
  • the capacitance sensor 105 can be used to detect the capacitance between the human body and the smart watch 100 , and the capacitance can reflect whether the contact between the human body and the smart watch 100 is good.
  • the capacitance sensor 105 is disposed on the electrode 104a and/or the electrode 104b, the capacitance sensor 105 can detect the capacitance between the human body and the electrode 104a and/or the electrode 104b.
  • the capacitance detected by the capacitance sensor 105 When the capacitance detected by the capacitance sensor 105 is too large or too small, it means that the human body is in poor contact with the electrode 104a and/or the electrode 104b; when the capacitance detected by the capacitance sensor 105 is moderate, it means that the human body is in contact with the electrode 104a and/or the electrode 104b better. Whether the contact between the human body and the electrodes is good or not will affect the detection of electrical signals by the electrodes, thereby affecting the generation of ECG waveforms. Therefore, when the smart watch 100 generates ECG waveforms, it can determine whether the user wears the smart watch according to the capacitance detected by the capacitance sensor 106D. Watch 100.
  • the infrared spectrum detection unit 106 is used to detect the wearing state according to the different reflection values of different substances.
  • the inertial measurement unit 107 is used to measure the three-axis attitude angle (or angular rate) and acceleration of the object.
  • the inertial measurement unit 107 includes three single-axis accelerometers and three single-axis gyroscopes, the accelerometers detect acceleration signals of objects in three independent axes in the carrier coordinate system, and the gyroscopes detect the carrier relative to the navigation coordinate system The angular velocity signal of the object is measured, and the angular velocity and acceleration of the object in the three-dimensional space are measured, and the posture of the object is calculated based on this.
  • the wearing position information of the smart watch 100 on the user's wrist can be detected.
  • the memory 108 is used to store software programs and data, and the processor 103 executes various functional applications and data processing of the smart watch 100 by running the software programs and data stored in the memory 108 .
  • the memory 108 may store the ECG waveform of the human body generated by the ECG detection module 103, the capacitance between the human body and the electrode 104a and/or the electrode 104b collected by the capacitive sensor 105, and the inertial measurement unit 107 Measured attitude angle, acceleration and other data.
  • the communication module 109 can be used to make the smart watch 100 communicate with other electronic devices and connect to the network through other electronic devices.
  • the smart watch 100 can establish a connection with the server through the communication module 109,
  • the generated ECG data is sent to the server, and the server analyzes the user's cardiac function according to the received ECG data, generates an electrocardiogram report, and sends the generated report to the smart watch 100 through the communication module 109 .
  • FIG. 2 is only an exemplary structure for realizing the function of the smart watch 100 in the technical solution of the present application, and the smart watch 100 having other structures and capable of realizing similar functions is also applicable to the technical solution of the present application. There is no restriction here.
  • FIG. 3 shows a schematic flowchart of a method for displaying an ECG waveform according to some embodiments of the present application; as shown in FIG. 3 , specifically, it includes:
  • the smart watch 100 When the user wears the smart watch 100 on the left hand as the set position, that is, when the user wears the smart watch 100 on the left wrist, the smart watch 100 will display the ECG waveform on the display screen in a normal display manner, for example, the ECG waveform
  • the smart watch 100 When the user wears the smart watch 100 on his right wrist and does not execute the ECG waveform display method provided by the embodiment of the present application, the smart watch 100 will display the ECG waveform on the display screen in an abnormal display manner.
  • the waveforms displayed on the display screen in a normal display mode and in an abnormal display mode are in opposite directions, for example, the peak of the ECG waveform faces the right-hand side, as an example to illustrate.
  • Step 301 the smart watch 100 starts the ECG waveform detection application, and collects the ECG waveform.
  • the smart watch 100 has an ECG waveform detection function, an application corresponding to the ECG waveform detection function in the smart watch 100 is started, and the smart watch 100 enables the ECG waveform detection function. For example, when the user clicks the ECG waveform detection APP with a finger, as shown in FIG. 1A , or when the user sends a command to open the ECG waveform detection APP to the smart watch 100 by voice, the smart watch 100 detects the click for opening the ECG waveform detection APP After operating or receiving the command to open the ECG APP, when the user's hand contacts the electrodes on the side of the smart watch, the ECG waveform detection application is started, and the smart watch 100 starts ECG waveform detection and collects ECG waveforms.
  • Step 302 The smart watch 100 determines the wearing state between the smart watch 100 and the user's wrist.
  • the ECG waveform is collected, and the wearing state and the wearing position are judged, so that the ECG waveform of the smart watch 100 is displayed on the display screen in a normal display manner.
  • the wearing state detection function of the smart watch 100 is implemented according to the difference in impedance values of the capacitor in the wearing state and the non-wearing state. For example, when the user wears the smart watch 100, it is detected that the surface impedance of the human body is in the range of 2-10 k ⁇ , and the smart watch 100 obtains the wearing state between the smart watch 100 and the user's wrist. When the user does not wear the smart watch 100 , the detected impedance value of the human body surface is generally greater than 1 M ⁇ , and the smart watch 100 obtains that the relationship between the smart watch 100 and the user's wrist is in an unworn state.
  • the smart watch 100 reads the wearing state data between the smart watch 100 and the user's wrist; and determines the wearing state between the smart watch 100 and the user's wrist. Specifically, it includes: the smart watch 100 reads the wearing status flag bit in the register of the smart watch 100 to obtain the wearing status between the smart watch 100 and the user's wrist. For example, before the smart watch 100 starts the ECG waveform detection application; the smart watch 100 determines the value of the wearing state flag bit flag_wear in the flag register according to the different impedance values of the capacitor in the wearing state and the non-wearing state.
  • the smart watch 100 When the user wears the smart watch 100, it is detected that the surface impedance of the human body is in the range of 2 to 10 k ⁇ , and the wearing status flag flag_wear in the flag register in the smart watch 100 is assigned as 1, and the smart watch 100 reads the register of the smart watch 100.
  • the wearing state flag bit When the wearing state flag bit is 1, the smart watch 100 obtains the wearing state between the smart watch 100 and the user's wrist.
  • the detected impedance value of the human body surface is generally greater than 1M ⁇ , and the wearing status flag flag_wear in the flag register in the smart watch 100 is assigned to 0, and the smart watch 100 reads the register of the smart watch 100.
  • the wearing state flag bit in When the wearing state flag bit in is 0, the smart watch 100 obtains the non-wearing state between the smart watch 100 and the user's wrist.
  • the infrared spectrum detected by the infrared spectrum detection device is different in the wearing state and the non-wearing state by using the principle of different reflection values of infrared rays to different substances. Therefore, the smart watch 100 can also realize the wearing state detection function of the smart watch 100 by means of the infrared spectrum detection device.
  • Step 303 The smart watch 100 determines whether it is in a wearing state. If yes, go to step 304; if no, it means that the watch is not in the wearing state, in this case, the IMU wearing part detection cannot be activated. Therefore, if the judgment result of step 303 is no, the current process ends.
  • Step 304 the smart watch 100 determines the information of the first wearing part by identifying the wearing part of the IMU.
  • the IMU obtains the data of the attitude angle of the gyroscope over time, the acceleration of the accelerometer over time, and the smart watch 100 according to the attitude angle and acceleration over time. From the time-varying data, the IMU wearing part detection confidence (as an example of the first wearing part position reliability) is obtained, and the IMU wearing part detection information (as an example of the first wearing part information) is obtained according to the IMU wearing part detection confidence.
  • the IMU wearing position detection confidence is used to determine the authenticity probability of the left-hand wearing position, the right-hand wearing position, and the uncertain wearing position.
  • the IMU wearing position detection confidence may be left-hand wearing confidence, right-hand wearing confidence, and uncertain wearing position detection confidence.
  • the sum of the left-hand wearing confidence, the right-hand wearing confidence and the detection confidence of the uncertain wearing position is 1.
  • the confidence of wearing on the left hand is 0.8
  • the confidence of wearing on the right is 0.1
  • the confidence of the position of the uncertain wearing part is 0.1.
  • the wearing information is determined to be worn on the left hand.
  • the wearing position information can be left-handed, right-handed, or uncertain wearing position.
  • the IMU wearing position detection confidence may also be in the form of a percentage, which is not limited in this application. It can be understood that the sum of the left-hand wearing confidence, the right-hand wearing confidence and the uncertain wearing part position confidence in the same detection may be 100%.
  • the IMU wearing part detection information (an example of the first wearing part information) is determined according to the acceleration value and the attitude angle detected by the IMU, including:
  • the smart watch 100 processes the attitude angle data that changes with time every preset time interval, for example, 200 milliseconds, and obtains the standard deviation and mean value of the attitude angle during each preset interval.
  • the acceleration can be the change of the accelerometer on the X, Y, and Z axes
  • the attitude angle can be the change of the gyroscope on the Pitch (Y axis), Roll (X axis), and Yaw (Z axis).
  • FIG. 4 shows a schematic diagram of a time region of an acquisition period with a preset interval of 200 milliseconds and a step size of 150 milliseconds, according to some embodiments of the present application. As shown in FIG.
  • the smart watch 100 processes the data of the gyroscope and the accelerometer once at a preset time interval, for example, 200 milliseconds, wherein the continuous data of 200 milliseconds has an overlapping area of 50 milliseconds.
  • FIG. 5 shows a difference and standard value of attitude angle and the difference of acceleration according to some embodiments of the present application.
  • the waveform diagram of the change of the value and the standard value over time includes: the first column: the change of the mean value of the X-axis attitude angle, the change of the standard deviation of the X-axis attitude angle, the change of the mean value of the X-axis acceleration, the change of the standard deviation of the X-axis acceleration ;
  • the second column the change of the mean value of the Y-axis attitude angle, the change of the standard deviation of the Y-axis attitude angle, the change of the mean value of the Y-axis acceleration, the change of the standard deviation of the Y-axis acceleration;
  • the third column the change of the mean value of the Z-axis attitude angle, the standard deviation of the Z-axis attitude angle Change, the average value of Z-axis acceleration, and the standard deviation of Z-axis acceleration, the gyroscope has attitude angles on the three axes of X, Y, and Z, which are used to determine the direction of the moving object.
  • the attitude angle data of the left hand and the right hand measured by the instrument are different.
  • the average change of the attitude angle on the three axes of X, Y, and Z reflects the average value of the attitude angle in a certain period of time.
  • the attitude angle standard deviation reflects the distribution and dispersion of attitude angle values in a certain period of time, and the average and standard deviation of the attitude angle can reflect the wearing position.
  • Acceleration is a vector whose direction is the direction in which the object's velocity changes (amount), in the same direction as the resultant external force. If a force is applied to the left or right, i.e. different accelerations are given, its velocity will change (both velocity and direction), however acceleration to the left and acceleration to the right obviously cause different effects.
  • the direction of force applied by the left and right hands during the movement is often different, and the directions of acceleration and acceleration are different.
  • the wearing part can be determined according to the average value and standard deviation of the acceleration.
  • the distribution rules and judgment criteria of the left and right hands are obtained through the training of the algorithm model.
  • the following is an exemplary description of the IMU wearing part identification model.
  • the IMU wearing part recognition model is trained to obtain a trained IMU wearing part recognition model that conforms to the preset loss function.
  • the trained IMU wearing part recognition model, and the output result of the trained IMU wearing part recognition model is the IMU wearing part detection confidence and/or the IMU wearing part detection information.
  • the IMU wearing position detection confidence may be the left hand wearing IMU wearing position detection confidence, the right hand wearing the IMU wearing position detection confidence, and the uncertain wearing position detection confidence.
  • the detection information of the wearing position of the IMU can be worn on the left hand, on the right hand, or the wearing position is uncertain.
  • the confidence level of the IMU wearing on the left hand is 0.8
  • the confidence level of the IMU wearing on the right hand is 0.2
  • the confidence level of the indeterminate wearing part is 0.4
  • the confidence level of the IMU wearing part detection can be a decimal or a percentage, but it is not limited to this.
  • the wearing part data may include the left and right wearing flag hand_flag_imu, the value of the left and right wearing flag hand_flag_imu is determined according to the wearing state of the left hand, and the value of the left and right wearing flag hand_flag_imu may be 0, 1, or 2. Among them, 0 means it is not sure whether to wear it on the left hand or the right hand, 1 means it is worn on the left hand, and 2 means it is worn on the right hand.
  • the smart watch 100 reads the value of the left and right hand wearing flag hand_flag_imu, and determines the wearing position information.
  • a plurality of IMU wearing part detection confidences are obtained according to the acceleration value and attitude angle detected by the IMU; the multiple IMU wearing part detection confidences are processed according to the first iterative formula to obtain the IMU average wearing part position confidence ( As an example of the first average wearing part position reliability); the IMU wearing part detection information is determined according to the IMU average wearing part position reliability.
  • the first iteration formula can be:
  • CI1_average represents the IMU average wearing position reliability
  • CI_imui represents the IMU wearing part detection confidence, that is, the single confidence CI_imui
  • a1 and b1 are natural numbers
  • the sum of a1 and b1 is 1, and a1 is greater than b1
  • the symbol " *" means multiplication
  • the value range of CI_average is [0,1].
  • a1 takes 0.6 and b2 takes 0.4.
  • determining the IMU wearing part detection information according to the IMU wearing part detection confidence level measured in a single time specifically includes:
  • the detection confidence of the IMU wearing part is greater than the first threshold (for example, 0.7), it is determined to be worn on the left hand; when the detection confidence of the IMU wearing part is less than the second threshold (for example, 0.3), it is determined to be worn on the right hand; when the IMU is worn on the right hand.
  • the wearing position detection confidence is between the first threshold and the second threshold interval (eg, 0.3 to 0.7), it is determined that the wearing position is uncertain; wherein, the first threshold is greater than the second threshold.
  • CI_imu indicates the confidence level of the IMU wearing position detection
  • hand_flag is the wearing position flag bit.
  • the smart watch reads the wearing part mark to determine the IMU wearing part detection information.
  • the IMU average wearing part position reliability when the IMU average wearing part position reliability is greater than a third threshold (for example, 0.7), it is determined that the left hand is worn, and when the IMU average wearing part position reliability is less than the fourth threshold (for example, 0.3) is determined to be worn on the right hand; when the IMU average wearing part position reliability is between the third threshold and the fourth threshold interval (for example, 0.3 to 0.7), it is determined that the wearing part is uncertain; wherein, the third threshold is greater than the fourth threshold threshold.
  • a third threshold for example, 0.7
  • the fourth threshold for example, 0.3
  • CI1_average indicates the average wearing position reliability of the IMU
  • hand_flag is the wearing position flag.
  • the smart watch reads the wearing part mark to determine the IMU wearing part detection information.
  • Step 305 The smart watch 100 determines whether the first wearing part information is in a confirmed state, if so, go to step 306; if not, go to step 311;
  • the IMU wearing part detection information is used as an example of the first wearing part information.
  • the smart watch 100 judges that the IMU wearing part detection information is in a definite state, and needs to be further verified by the recognition result obtained by the ECG wearing part identification to obtain a more accurate wearing part detection result, that is, step 306 is executed.
  • the smart watch 100 determines that the IMU wearing part detection information is in an uncertain state, and directly obtains the wearing part identification result through the identification result obtained by the ECG wearing part identification, that is, step 311 is executed.
  • Step 306 Display ECG wearing part identification prompt information on the display screen of the smart watch 100 to instruct the user to choose whether to perform ECG wearing part identification, so as to ensure that the ECG waveform is displayed in a normal state.
  • FIG. 6 shows an example of a display interface diagram of ECG waveform detection prompt information according to some embodiments of the present application.
  • the display screen of the smart watch 100 displays a prompt message “Further ECG wearing part identification is required to ensure that the ECG waveform is displayed normally!”, and two options: “Countdown for 3 seconds” and “Cancel”. "Countdown 3 seconds” means that the ECG wearing part recognition will start automatically when the time is up.
  • performing ECG waveform analysis after IMU detection will improve the success rate of wrist recognition and provide the user with a display of normal ECG waveforms. Therefore, the ECG waveform is automatically entered in the manner of "counting down 3 seconds".
  • the smart watch 100 does not obtain the ECG wearing part identification request, and cancels the prompt message “Further ECG wearing part identification is required to ensure that the ECG waveform is displayed normally!”, and two options: “Countdown 3 seconds", "Cancel” is displayed.
  • the user can also click the "Cancel” icon after clicking the "Cancel” icon for a period of time, and then click the "ECG wearing part recognition” icon to enable ECG wearing part recognition.
  • the ECG wearing part identification prompt information is not displayed on the display screen of the smart watch 100 to instruct the user to choose whether to perform ECG wearing part recognition, but the smart watch 100 directly recognizes the IMU wearing part after performing the IMU wearing part recognition. Automatic recognition of ECG wearing parts.
  • the judgment result of the left and right hands is obtained according to the wearing position information obtained by the ECG wearing position identification and the ECG wearing position detection confidence, or the wearing position information obtained according to the IMU wearing position identification and the IMU wearing position detection confidence are comprehensively considered.
  • the right and left hand judgment results are obtained according to the wearing position information and the ECG wearing position detection confidence obtained from the ECG wearing position identification.
  • Step 307 The smart watch 100 obtains the ECG wearing part identification request, and determines the second wearing part information through the ECG wearing part identification.
  • clicking on the ECG wearing part identification icon enables ECG wearing part identification.
  • a countdown of 3 seconds indicates that the ECG wearing part identification will be automatically started when the time is up.
  • the ECG wearing position detection confidence is obtained according to the waveform characteristic information of the ECG waveform; including:
  • the ECG wearing part information (an example of the second wearing position information) is determined from the ECG average wearing part position reliability.
  • it includes:
  • the detection confidence of multiple ECG wearing parts is obtained
  • the ECG average is obtained according to the IMU average wearing part position reliability (as an example of the first average wearing part position reliability), a plurality of ECG wearing part detection confidences (as an example of the second wearing part position reliability) and the second iterative formula wearing part detection confidence (as an example of the second average wearing part position reliability);
  • the ECG wearing position detection information is obtained according to the ECG average wearing position detection confidence.
  • the second iteration formula is:
  • CI2_average represents the reliability of the average wearing part of the ECG
  • CI1_average represents the reliability of the average wearing part of the IMU
  • CI_ecgi represents the detection confidence of the wearing part of the ECG
  • a2 and b2 are natural numbers
  • the sum of a2 and b2 is 1, and a2 is less than b2
  • the weight coefficient in front of the confidence is determined according to the length of the interval. For example, the longer the detection time from IMU wearing part recognition, the larger b2.
  • a2 takes 0.4 and b2 takes 0.6.
  • the value range of CI_ecgi is [0,1].
  • the proportion of IMU prediction is increased, thereby improving the accuracy and reducing the time used for ECG acquisition.
  • the proportion of IMU prediction is increased, thereby improving the accuracy and reducing the time used for ECG acquisition.
  • the smart watch 100 displays the prompt information of the user's input of the physical condition on the display interface of the display screen;
  • the proportion b2 of IMU prediction is increased.
  • the average ECG wearing position detection confidence when the average ECG wearing position detection confidence is greater than the fifth threshold, it is determined that the ECG is worn on the left hand; when the ECG average wearing position detection confidence is less than the sixth threshold, it is determined that the ECG is worn on the right hand; when the ECG wears on the average When the confidence of the part detection is between the fifth threshold and the sixth threshold, it is determined that the wearing part is uncertain; wherein, the fifth threshold is greater than the sixth threshold.
  • T1_ECG and T1_exg are greater than or equal to T1_exg.
  • the value of CI_ecgi is [T1_ECG, 1], [0, T1_exg), corresponding to the left hand and the right hand, respectively
  • hand_flag_ecg corresponds to the value of 1 and 2
  • the value of CI_ecgi is in the interval [T1_exg, T1_ECG]
  • T1_ECG If the value of T1_ECG is 0.5, the value of T1_exg is 0.3, the value of CI_ecgi is in the interval [0.5, 1] corresponding to the left hand, and the value of hand_flag_ecg is 1; the value of CI_ecgi is in the interval [0, 0.3), corresponding to the right hand, and the value of hand_flag_ecg is 2, The value of CI_ecgi is in the interval [0.3, 0.5], and the state of the left and right hands is uncertain.
  • the smart watch 100 can obtain ECG wearing position detection information by reading hand_flag_ecg.
  • the ECG wearing part detection confidence is processed by the third iterative formula to obtain the ECG average wearing part position reliability (as an example of the second average wearing part position reliability) , and the ECG wearing part detection information is obtained according to the ECG average wearing part position reliability.
  • the third iteration formula is:
  • CI2_average represents the ECG average wearing part position reliability
  • CI_ecgi represents the ECG wearing part detection confidence
  • a2 and b2 are natural numbers
  • the sum of a2 and b2 is 1, and a2 is less than b2, considering the ECG wearing part identification and IMU wearing part
  • the identification may be separated for a period of time, and the weight coefficient in front of the confidence is determined according to the length of the interval. For example, the longer the distance from the IMU wearing part identification detection time, the larger the b2. For example, a2 takes 0.4 and b2 takes 0.6.
  • the value range of CI_ecgi is [0,1].
  • the ECG wearing part detection information is obtained according to the position reliability of the ECG wearing part once.
  • the left and right hands are identified according to the EGG waveform.
  • the function of the ECG wearing part identification algorithm is to determine the part of the user wearing the smart wearable device by analyzing the ECG waveform shape in the initial stage of the user detection. Extract the ECG waveform (R wave, QRS complex width, etc.) within t (for example, 1 to 2s) to realize left and right hand judgment. Specifically, including:
  • the waveform feature information of the ECG waveform is input into the trained ECG wearing part recognition model, and the output result of the trained ECG wearing part recognition model is the ECG wearing part detection confidence.
  • the ECG wearing part detection information is determined according to the ECG wearing part detection confidence.
  • the ECG wearing position detection information can be left-handed or right-handed, and the ECG wearing position detection confidence can be the left-handed ECG-wearing confidence or the right-handed ECG-wearing confidence.
  • the extracted waveform feature information of ECG can be: QRS wave area, ratio of QR width to RS width, QR height, RS height, P wave amplitude, P wave area (including positive and negative), T Wave width, T wave area.
  • Fig. 7 shows a schematic diagram of an ECG waveform according to some embodiments of the present application, as shown in Fig. 7, including: QRS wave area, ratio of QR width to RS width, QR height, RS height, P wave amplitude, P wave Area (including positive and negative), T wave width, T wave area.
  • the principal component is reconstructed for the signal, and the top three principal component features with the largest variation in the waveform feature information are selected, and the selected principal component features are input into the trained ECG wearing part recognition model, so as to realize Judging by the left and right hands, and obtaining the confidence CI_ecgi at the same time.
  • Step 308 the smart watch 100 determines whether the information on the first wearing part is the same as the information on the second wearing part, if so, go to step 309 ; if not, go to step 310 .
  • the IMU wearing part detection information is taken as an example of the first wearing part information; the ECG wearing part detection information is taken as an example of the second wearing part information.
  • the IMU wearing part detection information is the same as the ECG wearing part detection information, which means that the results of the IMU wearing part recognition and the ECG wearing part recognition are consistent, and it can be determined that the IMU wearing part detection information and the ECG wearing part detection information are the left and right wearing states in the determined state. Or right-handed state. Therefore, the smart watch 100 can proceed to step 309 .
  • the difference between the IMU wearing part detection information and the ECG wearing part detection information means that the results of the IMU wearing part recognition and the ECG wearing part recognition are inconsistent, and it cannot be determined that the IMU wearing part detection information and the ECG wearing part detection information are left and right wearing in a certain state. The state is still the right hand wearing state. Because the ECG wearing part identification is relatively accurate, it is necessary to further perform the ECG wearing part identification to obtain the wearing part identification result, and the smart watch 100 can continue to perform step 310 .
  • Step 309 The smart watch 100 displays the ECG waveform on the display screen according to the display mode corresponding to the determined state.
  • the left hand is the preset wearing position information determined by the smart phone 100 according to the hardware structures such as the A electrode and the B electrode during setting. It can be understood that in other embodiments, the preset wearing position information can also be the right hand. wear. If the wearing position information is the preset wearing position information, the ECG waveform is displayed on the display screen in a normal display mode. It can be understood that, in other embodiments, the preset wearing position information may also be worn on the left hand. If the IMU wearing part detection information and the ECG wearing part detection information are left-hand wearing information or right-hand wearing information, it is a determined state.
  • the intelligent The watch 100 displays the ECG waveform on the display screen in a normal display manner.
  • the preset wearing part information is left-hand wearing. If the IMU wearing part detection information and the ECG wearing part detection information are the same as the left-hand wearing information, the smart watch 100 displays the ECG waveform on the display screen according to the normal display mode corresponding to the left-hand wearing.
  • the smart watch 100 adjusts the abnormal display mode to the normal display mode on the display screen.
  • the ECG waveform is displayed above.
  • the preset wearing part information is left-handed. If the IMU wearing part detection information and the ECG wearing part detection information are different from the hand wearing information, the smart watch 100 adjusts the abnormal display mode to the normal display mode and displays the ECG waveform on the display screen .
  • FIG. 8 shows an example of a display interface diagram of an abnormal display mode of an ECG waveform according to some embodiments of the present application. Because when the user wears the smart watch 100 on his left wrist, the smart watch 100 will display the ECG waveform on the display screen in a normal display manner, and when the user wears the smart watch 100 on his right wrist, the smart watch 100 will The ECG waveform is displayed in the negative direction of the coordinate axis, that is, toward the right-hand side. As shown in FIG. 8 , the display state of the ECG waveform on the display screen of the smart watch 100 is an abnormal display mode.
  • FIG. 9 shows an example of a display interface diagram of a normal display mode of an ECG waveform according to some embodiments of the present application.
  • the display state of the ECG waveform on the display screen of the smart watch 100 is the normal display mode. That is, multiply the waveform data in Figure 9 by minus 1, the waveform is inverted, and the ECG waveform is displayed in the positive direction of the coordinate axis, that is, toward the left-hand side.
  • the present application determines the wearing position information through IMU wearing position identification and ECG wearing position identification, so as to determine whether the ECG waveform is in the normal display mode, and if the ECG waveform is not in the normal display mode, the ECG waveform is adjusted to the normal display mode. In this way, it can reduce the misjudgment rate of wearing part recognition through IMU, and reduce the problem that it takes too long to recognize the wearing part through ECG. While shortening the recognition time, it can improve the recognition of the wearing part and the ECG waveform in a normal state. displayed accuracy.
  • Step 310 The smart watch 100 performs at least one ECG wearing part identification again to obtain the third wearing part information, and the smart watch 100 displays the ECG waveform on the display screen according to the display mode corresponding to the determined state indicated by the third wearing part information.
  • the smart watch 100 if the wearing position information obtained by the smart watch 100 according to the IMU wearing position identification is different from the wearing position information obtained according to the ECG wearing position identification, the smart watch 100 continues to perform at least one ECG wearing position identification to obtain the ECG wearing position detection information (as the first Three examples of wearing part information) and ECG wearing part detection confidence.
  • the manner of determining the wearing state according to the result of the further performed EGC wearing part identification may have the following exemplary embodiments.
  • At least one ECG wearing part identification is performed again to obtain the third wearing part information, that is, the number of ECG wearing part identifications is increased, and a plurality of ECG wearing part detection confidences ( As an example of the second wearing part position reliability) and the ECG average wearing part detection confidence (as an example of the second average wearing part position reliability), the ECG average wearing part detection confidence (as the third average wearing part position reliability) is re-obtained ); determine the ECG wearing position detection information (as an example of the third wearing position information) according to the obtained ECG average wearing position detection confidence.
  • CI3_average indicates the detection confidence of the average ECG wearing position again
  • CI2_average indicates the detection confidence of the average ECG wearing position
  • CIN_CI_ecgi indicates the ECG wearing position detection confidence corresponding to the increased number of ECG waveform detections
  • a3 and b3 are natural numbers
  • a3 and b3 The sum is 1, and a3 is less than b3.
  • T1_CI3 and T1_ci3, and T1_ECG is greater than or equal to T1_CI3.
  • the value of CI3_average is in the interval [T1_ci3, T1_CI3]
  • the state of the left and right hands is uncertain.
  • hand_flag_ecg when the value of hand_flag_ecg and the value of hand_flag are both 1 or 2, the corresponding ECG waveform is displayed.
  • the number of judgments based on the IMU is small and the prediction cannot be made correctly, so the proportion of waveform feature prediction is increased, and the accuracy rate of the judgment based on the waveform is higher than that based on the wearing part of the IMU. Accuracy, thereby improving the accuracy of the wearing position of the left and right hands and the ECG displayed in the normal display mode.
  • IMU wearing part recognition and ECG wearing part recognition are used at the same time, and when the wearing information determined by the two are different, the number of ECG wearing part recognition and the proportion of ECG detection confidence are increased, which improves the wearing part and ECG to a certain extent.
  • At least one third wearing part position reliability can also be obtained directly by performing at least one ECG wearing part identification number of times again, and the third wearing position information can be determined according to the at least one third wearing part position reliability.
  • ECG wearing part identification again to obtain an ECG wearing part detection confidence (as an example of the third wearing part position reliability), and determine the third wearing position information according to the ECG wearing part detection confidence.
  • ECG wearing part detection confidence as an example of the third wearing part position reliability
  • the ECG wearing part detection confidence is processed by the fifth iterative formula to obtain the ECG average wearing part position reliability (as an example of the third average wearing part position reliability), and the ECG wearing part detection is obtained according to the ECG average wearing part position reliability. information.
  • CI3_average a3*CI3_average+b3*CIN_CI_ecgi (Formula 5)
  • CI3_average indicates the re-obtained confidence of the average wearing position of the ECG
  • CIN_CI_ecgi indicates the detection confidence of the ECG wearing position corresponding to the increased number of ECG waveform detections
  • a3 and b3 are natural numbers
  • the sum of a3 and b3 is 1, and a3 is less than b3.
  • step S311 it returns to the judgment of step S05 , and if the judgment result of this step is no, the process of step S311 is entered.
  • Step 311 the smart watch 100 performs ECG wearing part identification to obtain fourth wearing part information.
  • At least one ECG wearing part detection confidence level (as an example of the fourth wearing part position confidence level) may be obtained directly by performing at least one ECG wearing part identification number of times again, and the determination is based on the at least one ECG wearing part detection confidence level.
  • ECG wearing position detection information (as an example of fourth wearing position information).
  • ECG wearing part identification again to obtain an ECG wearing part detection confidence (as an example of the fourth wearing part position confidence), and determine ECG wearing part detection information according to the ECG wearing part detection confidence.
  • the ECG wearing part detection confidence is processed by the sixth iterative formula to obtain the ECG average wearing part position reliability (as an example of the fourth average wearing part position reliability), according to the ECG average wearing part position
  • the reliability is obtained by ECG wearing part detection information (fourth wearing part information).
  • CI6_average a6*CI6_average+b6*CIN_CI_ecgi (Formula 6)
  • CI6_average means to obtain the average ECG wearing position detection confidence again
  • CIN_CI_ecgi means the ECG wearing position detection confidence corresponding to the increased ECG waveform detection times
  • a6 and b6 are natural numbers
  • the sum of a6 and b6 is 1, and a6 is less than b6.
  • Step 312 the smart watch 100 determines whether the fourth wearing position information is in a confirmed state, if so, go to step 313 ; if not, go to step 314 .
  • Step 313 The smart watch 100 displays the ECG waveform on the display screen according to the display mode corresponding to the determined state.
  • step 313 and step 309 are based on the same concept, and are not repeated here.
  • Step 314 The smart watch 100 performs at least one ECG wearing part identification again to obtain fifth wearing part information, and the smart watch 100 displays the ECG waveform on the display screen according to the display mode corresponding to the determined state indicated by the fifth wearing part information.
  • At least one ECG wearing part detection confidence level (as an example of the fifth wearing part position confidence level) may be obtained directly by performing at least one ECG wearing part identification number of times again, and the determination is based on the at least one ECG wearing part detection confidence level. Fifth wearing position information.
  • ECG wearing part identification again to obtain an ECG wearing part detection confidence (as an example of the fifth wearing part position reliability), and determine the fifth wearing position information according to the ECG wearing part detection confidence.
  • ECG wearing part detection confidence as an example of the fifth wearing part position reliability
  • the ECG wearing part detection confidence is processed through the seventh iterative formula to obtain the ECG average wearing part position reliability (as an example of the fifth average wearing part position reliability), according to the ECG average wearing part position
  • the reliability is obtained by ECG wearing part detection information (fifth wearing part information).
  • CI7_average represents the re-obtained ECG average wearing position detection confidence
  • CIN_CI_ecgi represents the ECG wearing position detection confidence corresponding to the increased ECG waveform detection times
  • a7 and b7 are natural numbers
  • the sum of a7 and b7 is 1, and a7 is less than b7.
  • the process of determining the fifth wearing position information according to the ECG wearing position detection confidence is similar in concept to the process of obtaining the wearing position information according to Equation 1, Equation 2 or Equation 3, and will not be repeated here.
  • Embodiments of the present application also provide a readable medium, where an instruction is stored on the readable medium, and when the instruction is executed on a machine, the machine executes the above-mentioned ECG waveform display method.
  • the above-mentioned storage medium may be located in at least one network server among multiple network servers of a computer network.
  • the above-mentioned storage medium may include but is not limited to: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic Various media that can store program codes, such as discs or optical discs.
  • the embodiment of the present application also provides an electronic device, the electronic device includes:
  • memory for storing instructions for execution by one or more processors of the electronic device
  • the processor is one of the processors of the electronic device, and is used for executing the above-mentioned method for configuring firewall rules.
  • the electronic device has the function of realizing the above-mentioned ECG waveform display method.
  • the functions can be implemented by hardware, or by executing corresponding software by hardware.
  • the hardware or software includes one or more modules corresponding to the above-mentioned functions.
  • FIG. 10 shows a block diagram of a SoC (System on Chip, system on chip) 1000 .
  • SoC 1000 includes: interconnect unit 1050, which is coupled to application processor 1010; system proxy unit 1070; bus controller unit 1080; integrated memory controller unit 1040; A processor 1020, which may include integrated graphics logic, a graphics processor, an audio processor, and a video processor; a static random access memory (SRAM) unit 1030; and a direct memory access (DMA) unit 1060.
  • interconnect unit 1050 which is coupled to application processor 1010; system proxy unit 1070; bus controller unit 1080; integrated memory controller unit 1040;
  • a processor 1020 which may include integrated graphics logic, a graphics processor, an audio processor, and a video processor; a static random access memory (SRAM) unit 1030; and a direct memory access (DMA) unit 1060.
  • SRAM static random access memory
  • DMA direct memory access
  • the coprocessor 1020 includes a special purpose processor such as, for example, a network or communications processor, a compression engine, a GPGPU, a high throughput MIC processor, an embedded processor, or the like.
  • a special purpose processor such as, for example, a network or communications processor, a compression engine, a GPGPU, a high throughput MIC processor, an embedded processor, or the like.
  • Embodiments disclosed herein may be implemented in hardware, software, firmware, or a combination of these implementation methods.
  • Embodiments of the present application may be implemented as a computer program or program code executing on a programmable system including at least one processor, a storage system (including volatile and nonvolatile memory and/or storage elements) , at least one input device, and at least one output device.
  • Program code may be applied to input instructions to perform the functions of the ECG waveform display methods described herein and to generate output information.
  • the output information can be applied to one or more output devices in a known manner.
  • a processing system includes any system having a processor such as, for example, a digital signal processor (DSP), microcontroller, application specific integrated circuit (ASIC), or microprocessor.
  • DSP digital signal processor
  • ASIC application specific integrated circuit
  • the program code may be implemented in a high-level procedural language or an object-oriented programming language to communicate with the processing system.
  • the program code may also be implemented in assembly or machine language, if desired.
  • the mechanisms described in this application are not limited in scope to any particular programming language. In either case, the language may be a compiled language or an interpreted language.

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Abstract

一种ECG波形显示方法，该方法包括：电子设备开启ECG波形检测应用程序，采集ECG波形；读取电子设备与用户手腕之间的佩戴部位数据；佩戴部位数据是通过IMU佩戴部位识别得到的；电子设备根据佩戴状态数据确定第一佩戴部位信息，第一佩戴部位信息包括确定状态和不确定状态；确定状态是第一确定状态或第二确定状态；电子设备通过ECG佩戴部位识别得到电子设备与用户手腕之间的第二佩戴部位信息；在第一佩戴部位信息和第二佩戴部位信息相同且为确定状态的情况下，电子设备根据确定状态对应的显示方式在显示屏上显示ECG波形。如此，可以降低判断ECG波形是否以正常显示方式显示的误判率，提高ECG波形以正常显示方式显示的准确性。

Description

ECG波形显示方法及其介质和电子设备
本申请要求于2020年08月25日提交中国专利局、申请号为202010862902.1、申请名称为“ECG波形显示方法及其介质和电子设备”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及电子技术领域，特别涉及ECG波形显示方法及其介质和电子设备。
背景技术
心电图(electrocardiogram，ECG)可以反映用户的健康状态，比如，ECG可以反映心脏的疾病(比如心率失常)等等。随着智能腕带、智能手表等可穿戴设备的不断发展，目前，在智能手表等可穿戴设备上可以集成ECG检测等健康检测功能，以监测用户的心率等身体体征，从而实现对用户身体状态的预知，以有效的避免心脏的传导电子设备障碍或者心肌发生病变。
由于用户在使用可穿戴设备进行ECG检测时，ECG波形与用户佩戴可穿戴设备的左右手位置直接相关。例如，如果用户将可穿戴设备佩戴在左手上，然后用其右手触摸可穿戴设备的电极，可穿戴设备产生的ECG波形为正向波形。在不改变可穿戴设备的任何配置的条件下，如果用户将可穿戴设备佩戴在右手上，然后用其左手触摸可穿戴设备的电极，可穿戴设备产生的ECG波形为错误的反向波形。
为了确定用户将可穿戴设备佩戴在左手还是右手，可以依据可穿戴设备中内置的惯性测量单元，检测并获取用户在佩戴时智能穿戴设备的偏转角度，从而识别出用户将可穿戴设备佩戴在左手还是右手。然而当用户首次佩戴可穿戴设备并保持静止的状态下，即刻使用ECG检测功能，则无法判断左右手佩戴，因而无法确定ECG波形是否正常显示。
在另外的为了确定用户将可穿戴设备佩戴在左手还是右手的方案中，在用户启动可穿戴设备的ECG检测功能时，依据可穿戴设备产生的ECG波形与预设的参考波形进行比较，从而识别用户将可穿戴设备佩戴在左手还是右手。然而在用户心脏偏右的情况下，用户将可穿戴设备佩戴在左手时，可穿戴设备产生的ECG波形特征与心脏位置正常的用户将可穿戴设备佩戴在右手时产生的ECG波形的特征相近，容易出现误判。
发明内容
本申请实施例提供了一种根据左右手识别的ECG检测方法及装置、介质及电子设备。
第一方面，本申请实施例提供了一种ECG波形显示方法，该方法包括：
电子设备开启ECG波形检测应用程序，采集ECG波形；
所述电子设备读取电子设备与用户手腕之间的佩戴部位数据；所述佩戴部位数据是通过IMU佩戴部位识别得到的；
所述电子设备根据所述佩戴状态数据确定第一佩戴部位信息，所述第一佩戴部位信息包括确定状态和不确定状态；所述确定状态是第一确定状态或第二确定状态；
所述电子设备通过ECG佩戴部位识别得到所述电子设备与用户手腕之间的第二佩戴部位信息；
在所述第一佩戴部位信息和所述第二佩戴部位信息相同且为确定状态的情况下，所述电子设备根据所述确定状态对应的显示方式在显示屏上显示ECG波形。
本申请实施例可以降低判断ECG波形是否以正常显示方式显示的误判率，提高ECG波形以正常显示方式显示的准确性。
在上述第一方面的一种可能的实现中，在所述第一佩戴部位信息和所述第二佩戴部位信息相同且为确定状态的情况下，根据所述确定状态对应的方式在显示屏上显示ECG波形，包括：
在第一佩戴部位信息及第二佩戴部位信息与预设佩戴部位信息相同的情况下，所述电子设备以正常显示方式在显示屏上显示ECG波形。
在上述第一方面的一种可能的实现中，在所述第一佩戴部位信息和所述第二佩戴部位信息相同且为确定状态的情况下，根据所述确定状态对应的方式在显示屏上显示ECG波形，包括：
在第一佩戴部位信息及第二佩戴部位信息与预设佩戴部位信息不相同的情况下，所述电子设备对所述ECG波形进行调整以使得所述ECG波形以正常显示方式在显示屏上显示。
在上述第一方面的一种可能的实现中，上述方法还包括：在所述第一佩戴部位信息和所述第二佩戴部位信息为确定状态但不相同的情况下，再执行至少一次ECG佩戴部位识别以得到第三佩戴部位信息，并且，所述电子设备根据所述第三佩戴部位信息表示的确定状态对应的显示方式在显示屏上显示ECG波形。
本申请实施例中，同时利用IMU佩戴部位识别和ECG佩戴部位识别，且在两者确定的佩戴信息不相同的时候，增加ECG佩戴部位识别次数和ECG检测置信度比重，在一定程度上提高了佩戴部位和ECG波形以正常状态显示的准确度。
在上述第一方面的一种可能的实现中，上述方法还包括：在所述第一佩戴部位信息为不确定状态的情况下，执行ECG佩戴部位识别以得到第四佩戴部位信息，所述电子设备根据所述第四佩戴位置信息表示的确定状态对应的显示方式在显示屏上显示ECG波形。
在上述第一方面的一种可能的实现中，上述方法还包括：在所述第一佩戴部位信息和所述第四佩戴部位信息相同且为不确定状态的情况下，再执行至少一次ECG佩戴部位识别以得到第五佩戴部位信息，所述电子设备根据所述第五佩戴位置信息表示的确定状态对应的显示方式在显示屏上显示ECG波形。
本申请实施例中，同时利用IMU佩戴部位识别和ECG佩戴部位识别，且在两者确定的佩戴信息不相同的时候，增加ECG佩戴部位识别次数和ECG检测置信度比重，在一定程度上提高了佩戴部位和ECG波形以正常状态显示的准确度。
在上述第一方面的一种可能的实现中，所述电子设备根据所述佩戴状态数据确定第一佩戴部位信息，包括
根据所述佩戴状态数据得到第一佩戴部位置信度，并至少根据所述第一佩戴部位置信度确定第一佩戴部位信息。
在上述第一方面的一种可能的实现中，所述根据所述佩戴状态数据得到第一佩戴部位置信度，并至少根据所述第一佩戴部位置信度确定第一佩戴部位信息，包括：
根据所述佩戴状态数据得到多个第一佩戴部位置信度；
将多个第一佩戴部位置信度根据第一迭代公式处理得到第一平均佩戴部位置信度；
根据所述第一平均佩戴部位置信度确定第一佩戴部位信息。
在上述第一方面的一种可能的实现中，所述佩戴部位数据包括IMU检测到的加速度值和姿态角，所述根据所述佩戴状态数据得到第一佩戴部位置信度，包括：
根据IMU检测到的加速度值和姿态角得到第一佩戴部位置信度。
在上述第一方面的一种可能的实现中，所述根据IMU检测到的加速度值和姿态角得到第一佩戴部位置信度，包括：
将当前获取的加速度计在X、Y、Z轴上的加速度标准差和均值，陀螺仪在X、Y、Z轴上的姿态角的标准差和均值输入已训练好的IMU配戴部位识别模型，已训练好的IMU配戴部位识别模型的输出结果为第一佩戴部位置信度。
在上述第一方面的一种可能的实现中，所述通过ECG佩戴部位识别得到第二佩戴部位信息，包括：
通过ECG佩戴部位识别得到第二佩戴部位置信度，并至少根据所述第二佩戴部位置信度确定第二佩戴位置信息。
在上述第一方面的一种可能的实现中，所述通过ECG佩戴部位识别得到第二佩戴部位置信度，并至少根据所述第二佩戴部位置信度确定第二佩戴位置信息，包括：
根据所述佩戴状态数据得到多个第一佩戴部位置信度；
将多个第一佩戴部位置信度根据第一迭代公式处理得到第一平均佩戴部位置信度；
根据所述第一平均佩戴部位置信度确定第一佩戴部位信息；
根据ECG佩戴部位识别得到多个第二佩戴部位置信度；
根据第一平均佩戴部位置信度、多个第二佩戴部位置信度和第二迭代公式得到第二平均佩戴部位置信度；
根据第二平均佩戴部位置信度得到第二佩戴部位信息。
在上述第一方面的一种可能的实现中，所述通过ECG佩戴部位识别得到第二佩戴部位置信度，包括：
根据ECG波形的波形特征信息确定所述第二佩戴部位置信度。
在上述第一方面的一种可能的实现中，将ECG的波形特征信息输入已训练好的ECG佩戴部位识别模型，得到已训练好的ECG佩戴部位识别模型的输出结果是第二佩戴部位置信度。
在上述第一方面的一种可能的实现中，所述第一迭代公式为：CI1_average＝a1*CI1_average+b1*CI_imui，其中，CI1_average表示第一平均佩戴部位置信度，CI_imui表示第一佩戴部位置信度，a1和b1为自然数，a1和b1之和为1，且a大于b。
在上述第一方面的一种可能的实现中，所述第二迭代公式为：CI2_average＝a2*CI1_average+b2*CI_ecgi，其中，CI2_average表示第二平均佩戴部位置信度，CI_ecgi表示第二佩戴部位置信度，a2和b2为自然数，a2和b2之和为1，且a2小于b2。
在上述第一方面的一种可能的实现中，所述ECG波形的波形特征信息包括：
QRS波面积，QR宽度与RS宽度比值，QR高度，RS高度，P波幅值，P波面积(含有正负)，T波宽度和T波面积。
在上述第一方面的一种可能的实现中，所述再执行至少一次ECG佩戴部位识别以得到第三佩戴部位信息，包括：
将第二佩戴部位置信度和第三佩戴部位置信度进行迭代处理，得到第三平均佩戴部位置信度；其中，第二佩戴部位置信度是根据此前ECG佩戴部位识别得到的，第二佩戴部位置信度与第二佩戴部位信息对应；
根据所述第三平均佩戴部位置信度确定第三佩戴部位信息。
在上述第一方面的一种可能的实现中，所述确定状态为电子设备与用户手腕之间的佩戴状态为右手佩戴状态或者左手佩戴状态。
第二方面，本申请实施里提供了一种可读介质，所述可读介质上存储有指令，该指令在电子设备上执行时使机器执行上述第一方面的所述的ECG波形显示方法。
第三方面，本申请实施里提供了一种电子设备，包括：
存储器，用于存储由电子设备的一个或多个处理器执行的指令，以及
处理器，是电子设备的处理器之一，用于执行第一方面的所述的ECG波形显示方法。
附图说明
图1A根据本申请的一些实施例，示出了一种ECG波形显示方法的应用场景图。
图1B根据本申请的一些实施例，示出了一种ECG波形显示方法的应用场景图。
图1C根据本申请的一些实施例，示出了一种ECG波形显示方法的应用场景图。
图2根据本申请的一些实施例，示出了一种智能手表的结构框图。
图3根据本申请的一些实施例，示出了一种根据ECG波形显示方法的流程示意图。
图4根据本申请的一些实施例，示出了一种预设间隔为200毫秒的，步长为150毫秒的采集周期的时间区域示意图。
图5根据本申请的一些实施例，示出了一种姿态角的差值和标准值以及加速度的差值和标准值随时间变化的波形示意图。
图6根据本申请的一些实施例，示出了一种ECG佩戴部位识别提示信息显示界面图示例。
图7根据本申请的一些实施例，示出了一段ECG波形示意图。
图8根据本申请的一些实施例，示出了一种非正常显示方式的ECG波形显示界面图示例。
图9根据本申请的一些实施例，示出了一种正常显示方式的ECG波形显示界面图示例。
图10根据本申请一些实施例，示出了一种片上电子设备(SoC)的框图。
具体实施方式
本申请的说明性实施例包括但不限于ECG波形显示方法及其介质和电子设备。
下面将结合附图对本申请的实施例作进一步地详细描述。
图1A、图1B和图1C根据本申请的一些实施例，示出了一种ECG波形显示方法的应用场景图。在图1A、图1B和图1C所示的实施例中，可穿戴设备100可以执行本申请提供的ECG波形显示方法。可穿戴设备100内置有ECG检测模组、多个电极以及惯性测量单元(Inertial measurement unit，IMU)。以可穿戴设备100包括两个电极为例，分别记为A电极和B电极，其中，如图1B所示，A电极200被设置在可穿戴设备100壳体的侧面，B电极(图中未示出)被设置在可穿戴设备100的下表面。在一些实施例中，当用户佩戴内置ECG检测模组的可穿戴设备100进行心电功能检测时，例如用户将可穿戴设备100佩戴在其左手手腕处，此时，用户的左手手腕与可穿戴设备100下表面的B电极接触，用户作用于进行心电检测的ECG波形检测APP(Application，应用)的图标。例如，用户通过手指点击ECG波形检测APP，如图1A所示，或用户通过语音的方式向可穿戴设备100发送打开ECG APP的命令时，可穿戴设备100检测到针对开ECG APP的点击操作或接收到打开ECG APP的命令，启动心电检测功能。用户可用其右手手指与可穿戴设备100侧面的A电极200接触，如图1B所示，A电极200和B电极形成一个电极对，能够采集用户心室去极化波形下降穿过心脏组织的详细信息。ECG检测模组对A电极200和B电极采集的电信号进行模数转换、滤波等处理，生成用户的单导联ECG信号。可穿戴设备100将ECG检测模组生成的用户的ECG波形显示在显示屏上。如图1B所示，因为智能手表100被设置为右手佩戴时ECG波形以正常显示方式显示，例如，ECG波形的波峰朝向左手侧，但是当智能手表100被用户戴在左手手腕的时候，ECG波形的波峰朝向右手侧，所以看起来不正常,ECG波形以非正常显示方式显示在显示屏上。本申请实施例中，可穿戴设备100根据内置的IMU确定出用户是将其佩戴在左手还是右手，并且根据ECG检测模组生成的ECG波形进一步判断用户是将其佩戴在左手还是右手，进而根据判断结果将ECG波形以正常显示方式显示在显示屏上，如图1C所示，以方便用户查看。
如此，相比较于相关技术中仅仅根据IMU进行左右手判断，或者仅仅根据采集到的ECG波形进行左右手判断的方案，可以避免仅仅根据IMU进行左右手判断导致判断的错误率较高的问题，也可以避免仅仅根据ECG波形进行左右手判断导致耗时过长的问题，在缩短判断时间的同时，提高了左右手识别和ECG波形以正常状态显示的准确率。
在一些实施例中，可穿戴设备100还可以根据ECG检测模组生成的ECG波形对用户的心电图进行分析，将分析的结果以文字的形式显示在其显示屏上，或者以语音的形式播放出来，使用户可以更直观地了解到其心脏的健康情况。
在图1所示的实施例中，可穿戴设备100可以单独进行ECG数据的采集、左右手的判断，以及根据左右手的判断结果进行最终的ECG波形的显示或者生产心电图报告。
可以理解的是，图1A、图1B和图1C虽然示出了智能手表100，但是适用于本申 请的ECG波形显示方法的电子设备可以为其他腕部佩戴设备，例如智能手环或者其他腕部佩戴的具有心电图测量功能的专用设备。
根据本申请所描述的处理过程，例如根据数据进行计算和判断的过程，可以在智能手环、智能电话、或其他可腕部佩戴的设备上进行，也可以在与智能手环、智能电话、或其他可腕部佩戴的设备无线或者有线连接的手机、平板电脑、掌上电脑(personal digital assistant，PDA)、笔记本电脑等设备上进行。
下面以可穿戴设备100为智能手表100为例，对用户佩戴能够执行本申请提供的ECG波形显示方法的技术方案进行详细介绍。
图2根据本申请的一些实施例，示出了一种智能手表100的结构框图。如图2所示，智能手表100包括触摸显示屏101、处理器102、ECG检测模组103、电极104a、电极104b、电容传感器105、IMU104、红外光谱检测单元(Infrared Spectroscopy，IR)106、惯性测量单元(Inertial measurement unit，IMU)107、存储器108、通信模块109等。
触摸显示屏101，一方面，该触摸显示屏可以作为触控面板，以采集用户在其上的触摸操作，并根据预先设定的程式驱动响应的连接装置。例如，采集用户通过手指点击智能手表100的ECG APP图标的触摸操作。另一方面，触摸显示屏101同时可以用于显示用户输入的信息或者提供给用户的提示信息以及智能手表100上的各种菜单。例如，显示通过智能手表100检测的用户的ECG波形、用户的心电图报告等等。
处理器102包括多个处理单元，可以运行本申请一些实施例提供的ECG波形显示方法的软件代码，例如，通过IMU佩戴部位识别和ECG佩戴部位识别确定佩戴部位信息，从而判断处ECG波形是否为正常显示方式，如果ECG波形不是正常显示方式，则将ECG波形调整为正常显示方式的ECG波形、用户的心电图报告等等。
ECG检测模组103，用于将电极104a和电极104b检测到的人体的电信号处理成ECG波形。比如，ECG检测模组103内部可以包括一个或多个滤波器，或者ECG检测模组103可以与一个或多个滤波器连接。一个或多个滤波器可以被配置为对电极104a和电极104b所检测到的人体电信号进行滤波处理，比如，ECG检测模组103可以配置一个或多个滤波器的频域带宽，若滤波器的频率带宽是0.5-40Hz，该滤波器可以对其输入信号(比如电极104a和电极104b检测到的电信号)进行滤波处理，得到处于0.5-40Hz范围内的电信号，其它频率的电信号被过滤掉。在一些实施例中，上文中将电极104a和电极104b检测到的电信号处理成ECG波形的功能可以由其它部件、组件或电路执行，该其它部件、组件或电路可以是与处理器103独立的不同的部件。其它部件、组件或电路可以是由分离的器件(比如半导体器件)所搭建而成，比如，其它部件、组件或电路可以是集成ECG检测功能的集成电路(integrated circuit，IC)、微电路(microcircuit)、芯片(chip)、微芯片(microchip)等等，本申请对此不作限定。
电容传感器105，可以用于检测人体与智能手表100之间的电容，该电容可以反映人体与智能手表100之间是否接触良好。当电容传感器105设置于电极104a和/或电极104b上时，电容传感器105可以检测人体与电极104a和/或电极104b之间的电容。当电容传感器105检测到的电容过大或过小时，说明人体与电极104a和/或电极104b接触较差；当电容传感器105检测到的电容适中时，说明人体与电极104a和/或 电极104b接触较好。由于人体与电极之间的接触是否良好会影响电极检测电信号，进而影响ECG波形的生成，所以智能手表100在生成ECG波形时，可以根据电容传感器106D检测到的电容，判断用户是否佩戴好智能手表100。
红外光谱检测单元106，用于根据不同物质的反射值不同进行佩戴状态检测.。
惯性测量单元107用于测量物体的三轴姿态角(或角速率)以及加速度。在一些实施例中，惯性测量单元107包括三个单轴的加速度计和三个单轴的陀螺，加速度计检测物体在载体坐标系统独立三轴的加速度信号，而陀螺检测载体相对于导航坐标系的角速度信号，测量物体在三维空间中的角速度和加速度，并以此计算出物体的姿态，在本申请的一些实施例中，可以检测出智能手表100在用户手腕上的佩戴部位信息。
存储器108用于存储软件程序以及数据，处理器103通过运行存储在存储器108的软件程序以及数据，执行智能手表100的各种功能应用以及数据处理。例如，在本申请的一些实施例中，存储器108可以存储ECG检测模组103生成的人体的ECG波形、电容传感器105采集的人体与电极104a和/或电极104b之间的电容，以及惯性测量单元107测量的姿态角、加速度等数据。
通信模块109可以用来使智能手表100和其他电子设备进行通信，并通过其他电子设备连接网络，例如，在本申请的一些实施例中，智能手表100可以通过通信模块109与服务器建立连接，将其生成的ECG数据发送给服务器，服务器根据接收到的ECG数据对用户的心脏功能进行分析，生成心电图报告，并将生成的报告通过通信模块109发送给智能手表100。
可以理解，图2所示的仅仅是实现本申请技术方案中智能手表100的功能的一种示例性结构，具有其他结构并能实现类似的功能的智能手表100也适用于本申请的技术方案，在此不做限制。
下面针对用户使用智能手表100进行ECG检测为例，对本申请的技术方案进行详细介绍。图3根据本申请的一些实施例，示出了一种根据ECG波形显示方法的流程示意图；如图3所示，具体地，包括：
以用户将智能手表100佩戴在左手为设定部位佩戴，即以用户将智能手表100佩戴在其左手手腕处，智能手表100会将ECG波形以正常显示方式显示在显示屏上，例如，ECG波形的波峰朝向左手侧，而用户将智能手表100佩戴在其右手手腕处，且未执行本申请实施例提供的ECG波形显示方法，会导致智能手表100将ECG波形以非正常显示方式显示在显示屏上，以正常显示方式显示在显示屏上和以非正常显示方式显示在显示屏上的波形方向相反，例如，ECG波形的波峰朝向右手侧，为例进行说明。
步骤301：智能手表100开启ECG波形检测应用程序，采集ECG波形。
在一些实施例中，智能手表100具备ECG波形检测功能，启动智能手表100中ECG波形检测功能对应的应用程序，智能手表100开启ECG波形检测功能。例如，用户通过手指点击ECG波形检测APP，如图1A所示，或用户通过语音的方式向智能手表100发送打开ECG波形检测APP的命令时，智能手表100检测到针对开ECG波形检测APP的点击操作或接收到打开ECG APP的命令，当用户的手与智能手表侧面的电极接触，即开启ECG波形检测应用程序，智能手表100开始ECG波形检测，采集ECG波形。
步骤302：智能手表100确定智能手表100与用户手腕之间的佩戴状态。
智能手表100开启ECG波形检测应用程序后，采集ECG波形，并进行佩戴状态和佩戴部位判断，以使得智能手表100的ECG波形以正常显示方式显示在显示屏上。
在一些实施例中，根据电容在佩戴状态和未佩戴状态的阻抗值不同，实现智能手表100的佩戴状态检测功能。例如，当用户佩戴智能手表100时，检测到人体表面阻抗值在2～10kΩ区间，智能手表100得到智能手表100与用户手腕之间为佩戴状态。当用户未佩戴智能手表100时，检测到的人体表面的阻抗值一般大于1MΩ，智能手表100得到智能手表100与用户手腕之间为未佩戴状态。
此外，在其他一些实施例中，智能手表100读取智能手表100与用户手腕之间的佩戴状态数据；确定智能手表100与用户手腕之间的佩戴状态。具体的，包括：智能手表100读取智能手表100的寄存器中的佩戴状态标志位，得到智能手表100与用户手腕之间的佩戴状态。例如，在智能手表100开启ECG波形检测应用程序之前；智能手表100根据电容在佩戴状态和未佩戴状态的阻抗值不同，确定标志寄存器中的佩戴状态标志位flag_wear的值。当用户佩戴智能手表100时，检测到人体表面阻抗值在2～10kΩ区间，将智能手表100中的标志寄存器中的佩戴状态标志位flag_wear赋值为1，智能手表100读取智能手表100的寄存器中的佩戴状态标志位为1时，智能手表100得到智能手表100与用户手腕之间为佩戴状态。当用户未佩戴智能手表100时，检测到的人体表面的阻抗值一般大于1MΩ，将智能手表100中的标志寄存器中的佩戴状态标志位flag_wear赋值为0，智能手表100读取智能手表100的寄存器中的佩戴状态标志位为0时，智能手表100得到智能手表100与用户手腕之间为未佩戴状态。
此外，与上述实施例不同的是，在其他一些实施例中，利用红外线对不同物质的反射值不同的原理，红外光谱检测器件检测到的佩戴状态和非佩戴状态的红外光谱不同。由此，智能手表100还可以借助红外光谱检测器件来实现智能手表100的佩戴状态检测功能。
步骤303：智能手表100判断是否为佩戴状态。若是，则转至步骤304；若否，则表明手表未处于佩戴状态，在这种情况下无法激活IMU佩戴部位检测。因此，若步骤303判断结果为否，当前则结束。
步骤304：智能手表100通过IMU佩戴部位识别确定第一佩戴部位信息。
在一些实施例中，当用户佩戴智能手表100后，IMU获取陀螺仪的姿态角随时间变化的数据，加速度计的加速度随时间变化的数据，智能手表100根据姿态角随时间变化的数据和加速度随时间变化的数据，得到IMU佩戴部位检测置信度(作为第一佩戴部位置信度的实例)，根据IMU佩戴部位检测置信度得到IMU佩戴部位检测信息(作为第一佩戴部位信息的实例)。以下对IMU佩戴部位检测置信度进行具体说明。可以理解，IMU佩戴部位检测置信度用于确定左手佩戴置、右手佩戴、不确定佩戴的真实度概率。IMU佩戴部位检测置信度可以为左手佩戴置信度、右手佩戴置信度、不确定佩戴部位检测置信度。左手佩戴置信度、右手佩戴置信度和不确定佩戴部位检测置信度之和为1。例如，左手佩戴置信度为0.8，右手佩戴置信度为0.1，不确定佩戴部位置信度为0.1。根据最高置信度确定佩戴信息为左手佩戴。佩戴部位信息可以为左手佩戴、右手佩戴、不确定佩戴部位。在一些实施例中，IMU佩戴部位检测置信度也可以为百分比的形式，本申请不作限制。可以理解，同一次检测的左手佩戴置信度、右 手佩戴置信度和不确定佩戴部位置信度之和可以为100％。
具体的，根据IMU检测到的加速度值和姿态角确定IMU佩戴部位检测信息(第一佩戴部位信息的实例)，包括：
智能手表100每间隔预设时间，例如200毫秒，处理一次随时间变化的姿态角数据，得到每个预设间隔时间内的姿态角的标准差和均值。
加速度可以是加速度计在X、Y、Z轴上的变化，姿态角可以是陀螺仪在Pitch(Y轴)、Roll(X轴)、Yaw(Z轴)的变化。例如，图4根据本申请的一些实施例，示出了一种预设间隔为200毫秒的，步长为150毫秒的采集周期的时间区域示意图。如图4所示，当用户佩戴手表后，智能手表100每间隔预设时间，例如200毫秒，处理一次陀螺仪和加速度计的数据，其中，连续的200ms的数据有50ms的重叠区域。
在一些实施例中，针对每200ms中，加速度计在X、Y、Z轴上的加速度变化，陀螺仪的Pitch(Y轴)、Roll(X轴)、Yaw(Z轴)等姿态角的变化，进行归一化处理，然后计算对应的加速度和姿态角的标准差、均值等参数，图5根据本申请的一些实施例，示出了一种姿态角的差值和标准值以及加速度的差值和标准值随时间变化的波形示意图，如图5所示，包括：第一列：X轴姿态角均值变化、X轴姿态角标准差变化、X轴加速度均值变化、X轴加速度标准差变化；第二列：Y轴姿态角均值变化、Y轴姿态角标准差变化、Y轴加速度均值变化、Y轴加速度标准差变化；第三列：Z轴姿态角均值变化、Z轴姿态角标准差变化、Z轴加速度均值变化、Z轴加速度标准差变化，陀螺仪具有X、Y、Z三个轴上的姿态角，用于确定运动物体的方向，用户的左手和右手运动方向不同，从而陀螺仪测得的左手和右手的姿态角数据不同，同一时间段内，X、Y、Z三个轴上的姿态角均值变化是反映了在某一时间段内，姿态角的平均值。姿态角标准差是反映了在某一时间段内姿态角值的分布、离散情况，姿态角的平均值和标准差能够反映出佩戴部位。
加速度是矢量，它的方向是物体速度变化(量)的方向，与合外力的方向相同。如果向左或向右施以力，即给予了不同的加速度，则其速度会发生变化(包含了速率及方向)，然而向左的加速度和向右的加速度显然引起了不同的效果。左右手在运动的过程中的施力方向往往不同，加速度和加速度的方向不同，根据加速度的平均值和标准差可以确定出佩戴部位。
左右手的分布规律和判定标准则是通过算法模型训练得到。下面对IMU配戴部位识别模型进行示例性说明。
将加速度计在X、Y、Z轴上的加速度标准差和均值，陀螺仪在Y轴、X轴、Z轴的姿态角的标准差和均值、左右手状态标签输入IMU配戴部位识别模型，通过训练IMU配戴部位识别模型得到符合预设损失函数的已训练好的IMU配戴部位识别模型。
将当前获取的加速度计在X、Y、Z轴上的加速度标准差和均值，陀螺仪在Pitch(Y轴)、Roll(X轴)、Yaw(Z轴)的姿态角的标准差和均值输入已训练好的IMU配戴部位识别模型，已训练好的IMU配戴部位识别模型的输出结果为IMU佩戴部位检测置信度和/或IMU佩戴部位检测信息。可以理解，IMU佩戴部位检测置信度可以为左手佩戴IMU佩戴部位检测置信度、右手佩戴IMU佩戴部位检测置信度、不确定佩戴部位检测置信度。IMU佩戴部位检测信息可以为左手佩戴、右手佩戴、不确定佩戴部位。 例如，IMU左手佩戴检测置信度为0.8，IMU右手佩戴检测置信度为0.2，不确定佩戴部位检测置信度为0.4，IMU佩戴部位检测置信度可以为小数也可以为百分数，但不限于此。
佩戴部位数据可以为包括左右佩戴标志hand_flag_imu，根据左手佩戴状态确定左右手佩戴标志hand_flag_imu的值，左右佩戴标志hand_flag_imu取值可以为0,1,2。其中，0表示不确定是左手佩戴还是右手佩戴，1表示左手佩戴，2表示右手佩戴。智能手表100读取左右手佩戴标志hand_flag_imu的值，确定佩戴部位信息。
在一些实施例中，根据IMU检测到的加速度值和姿态角得到多个IMU佩戴部位检测置信度；将多个IMU佩戴部位检测置信度根据第一迭代公式处理得到IMU平均佩戴部位置信度(作为第一平均佩戴部位置信度的实例)；根据IMU平均佩戴部位置信度确定IMU佩戴部位检测信息。
可以理解，第一迭代公式可以为：
CI1_average＝a1*CI1_average+b1*CI_imui     (公式1)
其中，CI1_average表示IMU平均佩戴部位置信度，CI_imui表示IMU佩戴部位检测置信度，即单次的置信度CI_imui，a1和b1为自然数，a1和b1之和为1，且a1大于b1，符号“*”表示相乘，CI_average的取值范围为[0,1]。例如，a1取0.6，b2取0.4。
在一些实施例中，根据单次测得的IMU佩戴部位检测置信度确定IMU佩戴部位检测信息具体的，包括：
当IMU佩戴部位检测置信度大于第一阈值(例如，0.7)时，则判定为左手佩戴，当IMU佩戴部位检测置信度小于第二阈值(例如，0.3)时，则判定为右手佩戴；当IMU佩戴部位检测置信度在第一阈值和第二阈值区间(例如，0.3至0.7)时，则判定为不确定佩戴部位；其中，第一阈值大于第二阈值。
例如，CI_imu表示IMU佩戴部位检测置信度，hand_flag为佩戴部位标志位，当CI_imu取值大于0.7时，则判定为左手佩戴，hand_flag赋值为1；当CI_imu取值小如0.3时，则判定为右手佩戴，hand_flag＝2；当CI_imu取值在区间[0.3,0.7]时，则判定为不确定佩戴部位，hand_flag＝0。智能手表读取佩戴部位标志位，即可确定IMU佩戴部位检测信息。
此外，在一些实施例中，当IMU平均佩戴部位置信度大于第三阈值(例如，0.7)时，则判定为左手佩戴，当IMU平均佩戴部位置信度小于第四阈值(例如，0.3)时，则判定为右手佩戴；当IMU平均佩戴部位置信度在第三阈值和第四阈值区间(例如，0.3至0.7)时，则判定为不确定佩戴部位；其中，第三阈值大于第四阈值。
例如，CI1_average表示IMU平均佩戴部位置信度，hand_flag为佩戴部位标志位，当CI1_average取值大于0.7时，则判定为左手佩戴，hand_flag赋值为1；当CI1_average取值小如0.3时，则判定为右手佩戴，hand_flag＝2；当CI1_average取值在区间[0.3,0.7]时，则判定为不确定佩戴部位，hand_flag＝0。智能手表读取佩戴部位标志位，即可确定IMU佩戴部位检测信息。
步骤305：智能手表100判断第一佩戴部位信息是否为确定状态，若是，则转至步骤306；若否，则转至步骤311；
IMU佩戴部位检测信息作为第一佩戴部位信息的实例。智能手表100判断IMU佩戴部位检测信息是确定状态，还需要进一步通过ECG佩戴部位识得到的识别结果进行验证，以得到较为准确的佩戴部位检测结果，即执行步骤306。智能手表100判断IMU佩戴部位检测信息是不确定状态，则直接通过ECG佩戴部位识得到的识别结果得到佩戴部位识别结果，即执行步骤311。
步骤306：在智能手表100的显示屏上显示ECG佩戴部位识别提示信息，以指示用户选择是否进行ECG佩戴部位识别，以确保ECG波形以正常状态显示。
图6根据本申请的一些实施例，示出了一种ECG波形检测提示信息显示界面图示例。如图6所示，智能手表100的显示屏显示提示信息“需要进一步进行ECG佩戴部位识别，以确保ECG波形显示正常！”，和两个选项：“倒计时3秒”，“取消”。“倒计时3秒”表示时间到即自动开始ECG佩戴部位识别。根据本申请的实施方式，在IMU检测之后进行ECG波形将侧将提高手腕识别的成功率，并为用户提供正常的心电图波形的显示，因此采用“倒计时3秒”这样的方式自动地进入ECG波形检测，除非用户强行中止。若用户点击“取消”图标，则智能手表100未获取到ECG佩戴部位识别请求，且取消提示信息“需要进一步进行ECG佩戴部位识别，以确保ECG波形显示正常！”，和两个选项：“倒计时3秒”，“取消”的显示。
此外，与上述实施例不同的是，在其他一些实施例中，用户也可以根据自身需求，在点击“取消”图标一段时间之后，点击“ECG佩戴部位识别”图标，开启ECG佩戴部位识别。
此外，在其他一些实施例中，在智能手表100的显示屏上不显示ECG佩戴部位识别提示信息，以指示用户选择是否进行ECG佩戴部位识别，而是智能手表100在进行IMU佩戴部位识别后直接自动进行ECG佩戴部位识别。
如此，在一些实施例中，根据ECG佩戴部位识别得到的佩戴部位信息和ECG佩戴部位检测置信度，得到左右手判断结果，或者综合考虑根据IMU佩戴部位识别得到的佩戴部位信息和IMU佩戴部位检测置信度以及根据ECG佩戴部位识别得到的佩戴部位信息和ECG佩戴部位检测置信度，得到左右手判断结果。
步骤307：智能手表100获取到ECG佩戴部位识别请求，通过ECG佩戴部位识别确定第二佩戴部位信息。
在一些实施例中，点击ECG佩戴部位识别图标，开启ECG佩戴部位识别。
此外，在其他一些实施例中，如图6所示，倒计时3秒”表示时间到即自动开始ECG佩戴部位识别。
在一些实施例中，在智能手表100获取到ECG波形检测请求后，根据ECG波形的波形特征信息得到ECG佩戴部位检测置信度；包括：
根据IMU佩戴部位检测置信度和ECG佩戴部位检测置信度得到ECG平均佩戴部位置信度(作为第二平均佩戴部位置信度的实例)；
根据ECG平均佩戴部位置信度确定ECG佩戴部位信息(第二佩戴位置信息的实例)。
具体的，在一些实施例中，包括：
根据ECG波形的波形特征信息得到多个ECG佩戴部位检测置信度；
根据IMU平均佩戴部位置信度(作为第一平均佩戴部位置信度的实例)、多个ECG 佩戴部位检测置信度(作为第二佩戴部位置信度的实例)和第二迭代公式得到ECG平均佩戴部位检测置信度(作为第二平均佩戴部位置信度的实例)；
根据ECG平均佩戴部位检测置信度得到ECG佩戴部位检测信息。
第二迭代公式为：
CI2_average＝a2*CI1_average+b2*CI_ecgi     (公式2)
其中，CI2_average表示ECG平均佩戴部位置信度，CI1_average表示IMU平均佩戴部位置信度，CI_ecgi表示ECG佩戴部位检测置信度，a2和b2为自然数，a2和b2之和为1，且a2小于b2，考虑到ECG佩戴部位识别与IMU佩戴部位识别可能会间隔一段时间，根据间隔时间的长短确定置信度前面的权重系数，例如，距离IMU佩戴部位识别检测时间越长，b2越大。例如，a2取0.4，b2取0.6。CI_ecgi取值范围为[0,1]。可以理解，在其他一些实施例中，当用户为心律失常患者，ECG波形存在畸形，则增加IMU预判比重，从而提高准确性，减少ECG采集所用时间。具体的，包括：
智能手表100在显示屏的显示界面显示用户输入身体状况的提示信息；
若获取到用户在智能手表100的显示界面输入在的心律失常信息，增加IMU预判比重b2。
在一些实施例中，当ECG平均佩戴部位检测置信度大于第五阈值时，则判定为左手佩戴，当ECG平均佩戴部位检测置信度小于第六阈值时，则判定为右手佩戴；当ECG平均佩戴部位检测置信度在第五阈值和第六阈值区间时，则判定为不确定佩戴部位；其中，第五阈值大于第六阈值。
例如，设定左右分界阈值为T1_ECG和T1_exg,T1_ECG大于等于T1_exg。其中，CI_ecgi取值为[T1_ECG,1]、[0,T1_exg)，分别对应左手、右手，hand_flag_ecg分别对应赋值1和2，CI_ecgi取值在区间[T1_exg，T1_ECG]，左右手状态不确定。若T1_ECG取值为0.5,T1_exg取值为0.3，CI_ecgi取值在区间[0.5,1]对应左手，hand_flag_ecg对应为1；CI_ecgi取值在区间[0,0.3)，对应右手，hand_flag_ecg对应为2，CI_ecgi取值在区间[0.3，0.5]，左右手状态不确定。在一些实施例中，智能手表100读取hand_flag_ecg即可得到ECG佩戴部位检测信息。
此外，在其他一些实施例中，与上述实施方式不同，紧将ECG佩戴部位检测置信度通过第三迭代公式处理得到ECG平均佩戴部位置信度(作为第二平均佩戴部位置信度的实例)，根据ECG平均佩戴部位置信度得到ECG佩戴部位检测信息。
第三迭代公式为：
CI2_average＝a2*CI2_average+b2*CI_ecgi    (公式3)
其中，CI2_average表示ECG平均佩戴部位置信度，CI_ecgi表示ECG佩戴部位检测置信度，a2和b2为自然数，a2和b2之和为1，且a2小于b2，考虑到ECG佩戴部位识别与IMU佩戴部位识别可能会间隔一段时间，根据间隔时间的长短确定置信度前面的权重系数，例如，距离IMU佩戴部位识别检测时间越长，b2越大。例如，a2取0.4，b2取0.6。CI_ecgi取值范围为[0,1]。
此外，在其他一些实施例中，根据一次ECG佩戴部位置信度得到ECG佩戴部位检测信息。
下面对如何获取ECG佩戴部位检测置信度进行示例性说明，在一些实施例中，当 用户佩戴智能手表100后，在用户佩戴智能手表100后根据EGG波形进行左右手识别。ECG配戴部位识别算法的功能是通过对用户检测起始阶段的ECG波形形态进行分析判断用户佩戴智能穿戴设备的部位。提取t(例如1～2s)时间内的ECG波形(R波、QRS波群宽度等)，实现左右手判断。具体的，包括：
获取用户佩戴智能手表100后的一段(例如1s时长)ECG波形；
确定获取的一段ECG波形的波形特征信息；
将ECG波形的波形特征信息输入已训练好的ECG佩戴部位识别模型，得到已训练好的ECG佩戴部位识别模型的输出结果是ECG佩戴部位检测置信度。根据ECG佩戴部位检测置信度确定ECG佩戴部位检测信息。ECG佩戴部位检测信息可以为左手佩戴还是右手佩戴，ECG佩戴部位检测置信度可以为左手佩戴ECG置信度或者右手佩戴ECG置信度。
可以理解，在ECG检测中，提取的ECG的波形特征信息可以为：QRS波面积，QR宽度与RS宽度比值，QR高度，RS高度，P波幅值，P波面积(含有正负)，T波宽度，T波面积。图7根据本申请的一些实施例，示出了一段ECG波形示意图，如图7所示，包括：QRS波面积，QR宽度与RS宽度比值，QR高度，RS高度，P波幅值，P波面积(含有正负)，T波宽度，T波面积。根据主元分析对信号进行主元重构，选择波形特征信息中变动最大的前3项主元特征，将选取的主元特征输入到已训练好的ECG佩戴部位识别模型，实现根据ECG波形的左右手判断，同时获得置信度CI_ecgi。
步骤308：智能手表100判断第一佩戴部位信息与第二佩戴部位信息是否相同，若是，则转至步骤309；若否，则转至步骤310。
IMU佩戴部位检测信息作为第一佩戴部位信息的实例；ECG佩戴部位检测信息作为第二佩戴部位信息的实例。IMU佩戴部位检测信息与ECG佩戴部位检测信息相同意味着IMU佩戴部位识别和ECG佩戴部位识别的结果一致，可以确定地认定IMU佩戴部位检测信息与ECG佩戴部位检测信息为确定状态中的左右佩戴状态或者右手佩戴状态。因此，智能手表100可以继续执行步骤309。IMU佩戴部位检测信息与ECG佩戴部位检测信息不相同意味着IMU佩戴部位识别和ECG佩戴部位识别的结果不一致，无法确定地认定IMU佩戴部位检测信息与ECG佩戴部位检测信息为确定状态中的左右佩戴状态还是右手佩戴状态。因为ECG佩戴部位识别较准确，因此，需要再进一步的进行ECG佩戴部位识别得到佩戴部位识别结果，智能手表100可以继续执行步骤310。
步骤309：智能手表100根据确定状态对应的显示方式在显示屏上显示ECG波形。
本申请实施例中，左手为智能手机上100在设置时根据A电极和B电极等硬件结构确定的预设佩戴部位信息，可以理解，在其他实施例中，预设佩戴部位信息还可以为右手佩戴。若佩戴部位信息为预设佩戴部位信息，则ECG波形以正常显示方式显示在显示屏上。可以理解，在其他实施例中，预设佩戴部位信息还可以为左手佩戴。IMU佩戴部位检测信息和ECG佩戴部位检测信息为左手佩戴信息或者右手佩戴信息则为确定状态。
在一些实施例中，在IMU佩戴部位检测信息(作为第一佩戴部位信息的实例)及ECG佩戴部位检测信息(作为第二佩戴部位信息的实例)与预设佩戴部位信息相同的情况下，智能手表100以正常显示方式在显示屏上显示ECG波形。
例如,预设佩戴部位信息为左手佩戴，若IMU佩戴部位检测信息和ECG佩戴部位检测信息与左手佩戴信息相同，智能手表100根据左手佩戴对应的正常显示方式在显示屏上显示ECG波形。
可以理解，在其他一些实施例中，在IMU佩戴部位检测信息及ECG佩戴部位检测信息与预设佩戴部位信息不相同的情况下，智能手表100将非正常显示方式调整为正常显示方式在显示屏上显示ECG波形。
例如，预设佩戴部位信息为左手佩戴，若IMU佩戴部位检测信息和ECG佩戴部位检测信息与做手佩戴信息不同，智能手表100将非正常显示方式调整为正常显示方式在显示屏上显示ECG波形。
图8根据本申请的一些实施例，示出了一种ECG波形非正常显示方式的显示界面图示例。因为以用户将智能手表100佩戴在其左手手腕处，智能手表100会将ECG波形以正常显示方式显示在显示屏上，而用户将智能手表100佩戴在其右手手腕处，会导致智能手表100将ECG波形显示在坐标轴负方向，即朝着右手侧方向。如图8所示，ECG波形在智能手表100的显示屏上的显示状态为非正常显示方式。
图9根据本申请的一些实施例，示出了一种ECG波形正常显示方式的显示界面图示例。如图9所示，ECG波形在智能手表100的显示屏上的显示状态为正常显示方式。即将图9中的波形数据乘以负1，波形反转，将ECG波形显示在坐标轴正方向，即朝着左手侧方向。
本申请通过IMU佩戴部位识别和ECG佩戴部位识别确定佩戴部位信息，从而判断处ECG波形是否为正常显示方式，如果ECG波形不是正常显示方式，则将ECG波形调整为正常显示方式。如此，可以降低紧紧通过IMU佩戴部位识别的误判率，降低紧紧通过ECG佩戴部位识别导致耗时过长的问题，在缩短识别时间的同时，提高了佩戴部位识别和ECG波形以正常状态显示的准确率。
步骤310：智能手表100再执行至少一次ECG佩戴部位识别以得到第三佩戴部位信息，并且，智能手表100根据第三佩戴部位信息表示的确定状态对应的显示方式在显示屏上显示ECG波形。
在一些实施例中，智能手表100根据IMU佩戴部位识别得到的佩戴部位信息与根据ECG佩戴部位识别得到的佩戴部位信息不同，则继续执行至少一次ECG佩戴部位识别得到ECG佩戴部位检测信息(作为第三佩戴部位信息的实例)和ECG佩戴部位检测置信度。根据更进一步执行的EGC佩戴部位识别的结果来确定佩戴状态的方式可以有以下示例性的实施方式。
在一种实施方式中，再执行至少一次ECG佩戴部位识别以得到第三佩戴部位信息，即增加ECG佩戴部位识别次数，根据增加的ECG佩戴部位识别次数得到的多个ECG佩戴部位检测置信度(作为第二佩戴部位置信度实例)和ECG平均佩戴部位检测置信度(作为第二平均佩戴部位置信度的实例)重新得到ECG平均佩戴部位检测置信度(作为第三平均佩戴部位置信度)；根据重新得到的ECG平均佩戴部位检测置信度确定ECG佩戴部位检测信息(作为第三佩戴位置信息的实例)。
重新得到ECG平均佩戴部位检测置信度计算公式：
CI3average＝a3*CI2_average+b3*CIN_CI_ecgi   (公式4)
其中，CI3_average表示重新得到ECG平均佩戴部位检测置信度，CI2_average表示ECG平均佩戴部位检测置信度，CIN_CI_ecgi表示增加的ECG波形检测次数对应的ECG佩戴部位检测置信度，a3和b3为自然数，a3和b3之和为1，且a3小于b3。
设定左右分界阈值为T1_CI3和T1_ci3,T1_ECG大于等于T1_CI3。其中，CI3_average取值为[T1_CI3,1]、[0,T1_ci3)，分别对应左手(hand_flag_ecg＝1)、右手(hand_flag_ecg＝2)，CI3_average取值在区间[T1_ci3，T1_CI3]，左右手状态不确定。
例如，当hand_flag_ecg取值与hand_flag取值均为1或2时，则显示对应的ECG波形。如hand_flag＝1(hand_flag_ecg＝hand_flag＝1)时，则正向显示ECG波形；当hand_flag＝2(hand_flag_ecg＝hand_flag＝2)时，则反向显示ECG波形，即ECG波形数据乘以-1。
可以理解，在一些实施例中，在当用户佩戴手表立即测量时，根据IMU判断次数少，无法正确预测，则增加波形特征预判比重，根据波形判断的准确率高于根据IMU佩戴部位识别的准确率，从而提高左右手佩戴位置和ECG以正常显示方式显示的准确率。
如此，同时利用IMU佩戴部位识别和ECG佩戴部位识别，且在两者确定的佩戴信息不相同的时候，增加ECG佩戴部位识别次数和ECG检测置信度比重，在一定程度上提高了佩戴部位和ECG波形以正常状态显示的准确度。
此外，在其他一些实施例中，也可以直接通过再执行至少一次ECG佩戴部位识别次数得到至少一个第三佩戴部位置信度，根据至少一个第三佩戴部位置信度确定第三佩戴位置信息。
例如，再执行一次ECG佩戴部位识别得到一个ECG佩戴部位检测置信度(作为第三佩戴部位置信度的实例)，根据ECG佩戴部位检测置信度确定第三佩戴位置信息。
例如，将ECG佩戴部位检测置信度通过第五迭代公式处理得到ECG平均佩戴部位置信度(作为第三平均佩戴部位置信度的实例)，根据ECG平均佩戴部位置信度得到ECG佩戴部位检测信息。
重新得到ECG平均佩戴部位检测置信度计算公式(作为第五迭代公式的实例)：
CI3_average＝a3*CI3_average+b3*CIN_CI_ecgi     (公式5)
其中，CI3_average表示重新得到ECG平均佩戴部位检测置信度，CIN_CI_ecgi表示增加的ECG波形检测次数对应的ECG佩戴部位检测置信度，a3和b3为自然数，a3和b3之和为1，且a3小于b3。
接下来，参考图3，再回到步骤S05的判断，若该步骤的判断结果为否，则进入步骤S311的处理。
步骤311：智能手表100执行ECG佩戴部位识别以得到第四佩戴部位信息。
在一些实施例中，可以直接通过再执行至少一次ECG佩戴部位识别次数得到至少一个ECG佩戴部位检测置信度(作为第四佩戴部位置信度的实例)，根据至少一个ECG佩戴部位检测置信度确定ECG佩戴部位检测信息(作为第四佩戴位置信息的实施例)。
例如，再执行一次ECG佩戴部位识别得到一个ECG佩戴部位检测置信度(作为第四佩戴部位置信度的实例)，根据ECG佩戴部位检测置信度确定ECG佩戴部位检测信 息。
此外，在其他一些实施例中，将ECG佩戴部位检测置信度通过第六迭代公式处理得到ECG平均佩戴部位置信度(作为第四平均佩戴部位置信度的实例)，根据ECG平均佩戴部位置信度得到ECG佩戴部位检测信息(第四佩戴部位信息)。
例如重新得到ECG平均佩戴部位检测置信度计算公式(作为第六迭代公式的实例)：
CI6_average＝a6*CI6_average+b6*CIN_CI_ecgi     (公式6)
其中，CI6_average表示重新得到ECG平均佩戴部位检测置信度，CIN_CI_ecgi表示增加的ECG波形检测次数对应的ECG佩戴部位检测置信度，a6和b6为自然数，a6和b6之和为1，且a6小于b6。
步骤312：智能手表100判断第四佩戴部位信息是否为确定状态，若是，则转至步骤313；若否，则转至步骤314。
步骤313：智能手表100根据确定状态对应的显示方式在显示屏上显示ECG波形。
步骤313与步骤309的实施例基于相同的构思，在此不再赘述。
步骤314：智能手表100再执行至少一次ECG佩戴部位识别以得到第五佩戴部位信息，并且，智能手表100根据第五佩戴部位信息表示的确定状态对应的显示方式在显示屏上显示ECG波形。
在一些实施例中，可以直接通过再执行至少一次ECG佩戴部位识别次数得到至少一个ECG佩戴部位检测置信度(作为第五佩戴部位置信度的实例)，根据至少一个ECG佩戴部位检测置信度确定第五佩戴位置信息。
例如，再执行一次ECG佩戴部位识别得到一个ECG佩戴部位检测置信度(作为第五佩戴部位置信度的实例)，根据ECG佩戴部位检测置信度确定第五佩戴位置信息。
此外，在其他一些实施例中，将ECG佩戴部位检测置信度通过第七迭代公式处理得到ECG平均佩戴部位置信度(作为第五平均佩戴部位置信度的实例)，根据ECG平均佩戴部位置信度得到ECG佩戴部位检测信息(第五佩戴部位信息)。
例如，重新得到ECG平均佩戴部位检测置信度的计算公式：
CI7_average＝a7*CI7_average+b7*CIN_CI_ecgi    (公式7)
其中，CI7_average表示重新得到ECG平均佩戴部位检测置信度，CIN_CI_ecgi表示增加的ECG波形检测次数对应的ECG佩戴部位检测置信度，a7和b7为自然数，a7和b7之和为1，且a7小于b7。
根据ECG佩戴部位检测置信度确定第五佩戴位置信息的过程与根据公式1、公式2或公式3得到的佩戴部位信息的过程的构思类似，在此不再赘述。
本申请的实施例还提供了一种可读介质，可读介质上存储有指令，该指令在机器上执行时使机器执行上述的ECG波形显示方法。
可选地，在本实施例中，上述存储介质可以位于计算机网络的多个网络服务器中的至少一个网络服务器。可选地，在本实施例中，上述存储介质可以包括但不限于：U盘、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、移动硬盘、磁碟或者光盘等各种可以存储程序代码的介质。
本申请的实施例还提供了一种电子设备，电子设备包括：
存储器，用于存储由电子设备的一个或多个处理器执行的指令，以及
处理器，是电子设备的处理器之一，用于执行上述的防火墙规则配置方法方法。该电子设备具有实现上述ECG波形显示方法的功能。功能可以通过硬件实现，也可以通过硬件执行相应的软件实现。硬件或软件包括一个或多于一个与上述功能相对应的模块。
根据本申请的实施例，图10示出了一种SoC(System on Chip，片上系统)1000的框图。在图10中，相似的部件具有同样的附图标记。另外，虚线框是更先进的SoC的可选特征。在图10中，SoC 1000包括：互连单元1050，其被耦合至应用处理器1010；系统代理单元1070；总线控制器单元1080；集成存储器控制器单元1040；一组或一个或多个协处理器1020，其可包括集成图形逻辑、图像处理器、音频处理器和视频处理器；静态随机存取存储器(SRAM)单元1030；直接存储器存取(DMA)单元1060。
在一个实施例中，协处理器1020包括专用处理器，诸如例如网络或通信处理器、压缩引擎、GPGPU、高吞吐量MIC处理器、或嵌入式处理器等等。
本申请公开的实施例可以被实现在硬件、软件、固件或这些实现方法的组合中。本申请的实施例可实现为在可编程系统上执行的计算机程序或程序代码，该可编程系统包括至少一个处理器、存储系统(包括易失性和非易失性存储器和/或存储元件)、至少一个输入设备以及至少一个输出设备。
可将程序代码应用于输入指令，以执行本申请描述ECG波形显示方法的各功能并生成输出信息。可以按已知方式将输出信息应用于一个或多个输出设备。
为了本申请的目的，处理系统包括具有诸如例如数字信号处理器(DSP)、微控制器、专用集成电路(ASIC)或微处理器之类的处理器的任何系统。
程序代码可以用高级程序化语言或面向对象的编程语言来实现，以便与处理系统通信。在需要时，也可用汇编语言或机器语言来实现程序代码。事实上，本申请中描述的机制不限于任何特定编程语言的范围。在任一情形下，该语言可以是编译语言或解释语言。
虽然通过参照本申请的某些优选实施例，已经对本申请进行了图示和描述，但本领域的普通技术人员应该明白，可以在形式上和细节上对其作各种改变，而不偏离本申请的精神和范围。

Claims (21)

  1. 一种ECG波形显示的方法，其特征在于，包括：
    电子设备开启ECG波形检测应用程序，采集ECG波形；
    所述电子设备读取电子设备与用户手腕之间的佩戴部位数据；所述佩戴部位数据是通过IMU佩戴部位识别得到的；
    所述电子设备根据所述佩戴状态数据确定第一佩戴部位信息，所述第一佩戴部位信息包括确定状态和不确定状态；所述确定状态是第一确定状态或第二确定状态；
    所述电子设备通过ECG佩戴部位识别得到所述电子设备与用户手腕之间的第二佩戴部位信息；
    在所述第一佩戴部位信息和所述第二佩戴部位信息相同且为确定状态的情况下，所述电子设备根据所述确定状态对应的显示方式在显示屏上显示ECG波形。
  2. 根据权利要求1所述的方法，其特征在于，在所述第一佩戴部位信息和所述第二佩戴部位信息相同且为确定状态的情况下，根据所述确定状态对应的方式在显示屏上显示ECG波形，包括：
    在第一佩戴部位信息及第二佩戴部位信息与预设佩戴部位信息相同的情况下，所述电子设备以正常显示方式在显示屏上显示ECG波形。
  3. 根据权利要求1所述的方法，其特征在于，在所述第一佩戴部位信息和所述第二佩戴部位信息相同且为确定状态的情况下，根据所述确定状态对应的方式在显示屏上显示ECG波形，包括：
    在第一佩戴部位信息及第二佩戴部位信息与预设佩戴部位信息不相同的情况下，所述电子设备对所述ECG波形进行调整以使得所述ECG波形以正常显示方式在显示屏上显示。
  4. 根据权利要求1所述的方法，其特征在于，还包括：在所述第一佩戴部位信息和所述第二佩戴部位信息为确定状态但不相同的情况下，再执行至少一次ECG佩戴部位识别以得到第三佩戴部位信息，并且，所述电子设备根据所述第三佩戴部位信息表示的确定状态对应的显示方式在显示屏上显示ECG波形。
  5. 根据权利要求1所述的方法，其特征在于，还包括：在所述第一佩戴部位信息为不确定状态的情况下，执行ECG佩戴部位识别以得到第四佩戴部位信息，所述电子设备根据所述第四佩戴位置信息表示的确定状态对应的显示方式在显示屏上显示ECG波形。
  6. 根据权利要求5所述的方法，其特征在于，还包括：在所述第一佩戴部位信息和所述第四佩戴部位信息相同且为不确定状态的情况下，再执行至少一次ECG佩戴部位识别以得到第五佩戴部位信息，所述电子设备根据所述第五佩戴位置信息表示的确定状态对应的显示方式在显示屏上显示ECG波形。
  7. 根据权利要求1所述的方法，其特征在于，所述电子设备根据所述佩戴状态数据确定第一佩戴部位信息，包括
    根据所述佩戴状态数据得到第一佩戴部位置信度，并至少根据所述第一佩戴部位置信度确定第一佩戴部位信息。
  8. 根据权利要求7所述的方法，其特征在于，所述根据所述佩戴状态数据得到第 一佩戴部位置信度，并至少根据所述第一佩戴部位置信度确定第一佩戴部位信息，包括：
    根据所述佩戴状态数据得到多个第一佩戴部位置信度；
    将多个第一佩戴部位置信度根据第一迭代公式处理得到第一平均佩戴部位置信度；
    根据所述第一平均佩戴部位置信度确定第一佩戴部位信息。
  9. 根据权利要求7所述的方法，其特征在于，所述佩戴部位数据包括IMU检测到的加速度值和姿态角，所述根据所述佩戴状态数据得到第一佩戴部位置信度，包括：
    根据IMU检测到的加速度值和姿态角得到第一佩戴部位置信度。
  10. 根据权利要求9所述的方法，其特征在于，所述根据IMU检测到的加速度值和姿态角得到第一佩戴部位置信度，包括：
    将当前获取的加速度计在X、Y、Z轴上的加速度标准差和均值，陀螺仪在X、Y、Z轴上的姿态角的标准差和均值输入已训练好的IMU配戴部位识别模型，已训练好的IMU配戴部位识别模型的输出结果为第一佩戴部位置信度。
  11. 根据权利要求1所述的方法，其特征在于，所述通过ECG佩戴部位识别得到第二佩戴部位信息，包括：
    通过ECG佩戴部位识别得到第二佩戴部位置信度，并至少根据所述第二佩戴部位置信度确定第二佩戴位置信息。
  12. 根据权利要求11所述的方法，其特征在于，所述通过ECG佩戴部位识别得到第二佩戴部位置信度，并至少根据所述第二佩戴部位置信度确定第二佩戴位置信息，包括：
    根据所述佩戴状态数据得到多个第一佩戴部位置信度；
    将多个第一佩戴部位置信度根据第一迭代公式处理得到第一平均佩戴部位置信度；
    根据所述第一平均佩戴部位置信度确定第一佩戴部位信息；
    根据ECG佩戴部位识别得到多个第二佩戴部位置信度；
    根据第一平均佩戴部位置信度、多个第二佩戴部位置信度和第二迭代公式得到第二平均佩戴部位置信度；
    根据第二平均佩戴部位置信度得到第二佩戴部位信息。
  13. 根据权利要求11或12任一项所述的方法，其特征在于，所述通过ECG佩戴部位识别得到第二佩戴部位置信度，包括：
    根据ECG波形的波形特征信息确定所述第二佩戴部位置信度。
  14. 根据权利要求13所述的方法，其特征在于，包括：将ECG的波形特征信息输入已训练好的ECG佩戴部位识别模型，得到已训练好的ECG佩戴部位识别模型的输出结果是第二佩戴部位置信度。
  15. 根据权利要求8或12任一项所述的方法，其特征在于，所述第一迭代公式为：
    CI1_average＝a1*CI1_average+b1*CI_imui，其中，CI1_average表示第一平均佩戴部位置信度，CI_imui表示第一佩戴部位置信度，a1和b1为自然数，a1和b1之和为1，且a大于b。
  16. 根据权利要求12所述的方法，其特征在于，所述第二迭代公式为：
    CI2_average＝a2*CI1_average+b2*CI_ecgi，其中，CI2_average表示第二平均佩戴 部位置信度，CI_ecgi表示第二佩戴部位置信度，a2和b2为自然数，a2和b2之和为1，且a2小于b2。
  17. 根据权利要求13所述的方法，其特征在于，所述ECG波形的波形特征信息包括：
    QRS波面积，QR宽度与RS宽度比值，QR高度，RS高度，P波幅值，P波面积(含有正负)，T波宽度和T波面积。
  18. 根据权利要求4所述的方法，其特征在于，所述再执行至少一次ECG佩戴部位识别以得到第三佩戴部位信息，包括：
    将第二佩戴部位置信度和第三佩戴部位置信度进行迭代处理，得到第三平均佩戴部位置信度；其中，第二佩戴部位置信度是根据此前ECG佩戴部位识别得到的，第二佩戴部位置信度与第二佩戴部位信息对应；
    根据所述第三平均佩戴部位置信度确定第三佩戴部位信息。
  19. 根据权利要求1所述的方法，其特征在于，所述确定状态为电子设备与用户手腕之间的佩戴状态为右手佩戴状态或者左手佩戴状态。
  20. 一种可读介质，其特征在于，所述可读介质上存储有指令，该指令在电子设备上执行时使机器执行权利要求1至19中任一项所述的ECG波形显示方法。
  21. 一种电子设备，包括：
    存储器，用于存储由电子设备的一个或多个处理器执行的指令，以及
    处理器，是电子设备的处理器之一，用于执行权利要求1至19中任一项所述的ECG波形显示方法。
PCT/CN2021/114341 2020-08-25 2021-08-24 Ecg波形显示方法及其介质和电子设备 WO2022042558A1 (zh)

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