Biological sound state monitoring method, wearable device and intelligent monitoring system
By implementing biosound status monitoring methods in smart wearable devices, analyzing biosound signal data and generating detailed monitoring reports, the problem that users cannot fully understand their health status is solved, and more accurate health status monitoring and suggestions are achieved.
Patent Information
- Application Number
- CN202411549095.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-31
- Publication Date
- 2025-02-28
AI Technical Summary
Existing smart wearable devices only provide digital data after biosound detection, and users cannot fully and accurately understand their current health status.
A biosound status monitoring method is proposed. By obtaining the biosound signal monitored by the wearable device, forming biosound signal data, analyzing the data to generate monitoring reports, and transmitting the reports to the wearable device and mobile devices, including biosound data charts and status evaluation briefs.
Improves the monitoring ability of users' current biosound status, so users can fully and accurately understand their current health status, and obtain more in-depth health information through charts, analysis and suggestions.
Smart Images
Figure CN119523520A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of intelligent electronic products, and in particular to a biological sound state monitoring method, a wearable device and an intelligent monitoring system. Background Art
[0002] Bio-sound detection is an important test item in routine physical examinations. Bio-sound detection includes but is not limited to heart sound detection, lung sound detection, etc. Taking heart sound detection as an example, heart sound detection usually uses a bio-sound sensor to obtain the low-frequency vibration sound waves generated by the heart contraction, so as to analyze the heart health status of humans or animals through the waveform of the sound waves.
[0003] Existing bio-sound sensors are also gradually being widely used in smart wearable devices to help users perform daily bio-sound detection more quickly, such as smart wearable watches. However, existing smart wearable devices only provide data displayed in digital form after detection. Users cannot know the specific meaning and status represented by the data, and thus cannot fully and accurately understand their current status. Summary of the invention
[0004] The main purpose of the present invention is to propose a bio-sound status monitoring method, wearable device and intelligent monitoring system, aiming to improve the monitoring ability of the user's current bio-sound status through the bio-sound status monitoring method, so as to fully and accurately understand the user's current health status.
[0005] To achieve the above object, the present invention proposes a biological sound state monitoring method, the steps of the biological sound state monitoring method comprising: Obtain the bio-sound signal monitoring value detected by the wearable device; Aggregating the bio-sound signal monitoring values to form bio-sound signal data; Analyzing the bio-sound signal data and generating a bio-sound status monitoring report; Transmitting the bio-sound status monitoring report to the wearable device and the mobile device; The bio-sound status monitoring report includes a bio-sound data chart and a bio-sound status assessment brief.
[0006] In one embodiment, after acquiring the monitoring value of the biological sound signal monitored by the wearable device, the biological sound state monitoring method further includes: Set default contacts; Determining whether the bio-sound signal monitoring value is less than a preset bio-sound signal value; If yes, storing the bio-sound signal monitoring value, and sending the bio-sound signal monitoring value to the preset contact; If not, an emergency call is made to the preset contact.
[0007] In one embodiment, the step of determining whether the bio-sound signal monitoring value is less than a preset bio-sound signal value comprises: Acquiring state characteristics of biological sound signal data; Constructing a bio-sound state prediction model according to the state characteristics of the bio-sound signal data; Acquiring characteristic parameters of the bio-sound signal data, and inputting the characteristic parameters of the bio-sound signal data into the bio-sound state prediction model, and outputting the preset bio-sound signal value; The bio-sound signal monitoring value is compared with the preset bio-sound signal value to determine whether the bio-sound signal monitoring value is less than the preset bio-sound signal value.
[0008] In one embodiment, the step of determining whether the bio-sound signal monitoring value is less than a preset bio-sound signal value further includes: updating the characteristic parameters of the bio-sound signal data according to the bio-sound signal monitoring value; Performing sample augmentation training on the bio-sound state prediction model according to the characteristic parameters of the bio-sound signal data to obtain augmented sample data; The bio-sound state prediction model is iteratively optimized according to the amplified sample data.
[0009] In one embodiment, the step of aggregating the bio-sound signal monitoring values to form bio-sound signal data comprises: Storing the collected biological sound signal monitoring values; According to the received historical signal monitoring value of the wearable device, searching for abnormal vibration value in the biological sound signal monitoring value; Eliminating the abnormal vibration value in the biological sound signal monitoring value; Using bandpass filtering to filter out external low-frequency noise and high-frequency interference in the biological sound signal monitoring value; Using a wavelet threshold noise reduction method to reduce noise on the filtered biological sound signal monitoring value; The bio-sound signal monitoring value is smoothed to obtain the bio-sound signal data.
[0010] In one embodiment, the step of analyzing the bio-sound signal data and generating a bio-sound status monitoring report includes: Determine the wearable device feature code and compare it with the feature code database to identify the wearable device; Determining the type and collection location of the biological sound according to the biological sound signal data; Determining whether there is a noise signal in the bio-sound signal data within a preset time; If yes, the type of noise is analyzed through the spectrum of the noise signal, and the biological sound status monitoring report is output; If not, the bio-sound status monitoring report is output.
[0011] In one embodiment, the types of biological sounds include but are not limited to at least one of heart sounds, lung sounds, bowel sounds, vascular echoes, tracheal breath sounds, bronchial breath sounds, and joint movement sounds; And / or, the acquisition position includes a cardiac auscultation position, and the cardiac auscultation position includes a mitral valve area, a pulmonary valve area, an aortic valve area, a second auscultation area of the aortic valve, and a tricuspid valve area; And / or, the acquisition positions include lung auscultation positions, and the lung auscultation positions include the left front chest, the left chest, the left back, the right front chest, the right chest and the right back.
[0012] The present invention further provides a wearable device, the wearable device comprising: at least one processor; at least one bio-sound sensor, each of the bio-sound sensors being electrically connected to at least one of the processors, the bio-sound sensor being configured to monitor a bio-sound signal; and a memory communicatively coupled to the at least one processor; The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the steps of the above-mentioned biological sound state monitoring method.
[0013] In one embodiment, the bio-sound sensor includes but is not limited to one of a bone conduction sensor, a microphone, an acceleration sensor, an inertial sensor, a piezoelectric ceramic, a pressure sensor, and a vibration detection sensor.
[0014] The present invention also provides an intelligent monitoring system, the intelligent monitoring system comprising: Such as the wearable devices mentioned above; A mobile device, the mobile device being communicatively connected to the wearable device; and A cloud server is communicatively connected with the mobile device.
[0015] The steps of the bio-sound state monitoring method of the technical solution of the present invention include: obtaining the bio-sound signal monitoring value monitored by the wearable device; aggregating the bio-sound signal monitoring value to form bio-sound signal data; analyzing the bio-sound signal data and generating a bio-sound state monitoring report; transmitting the bio-sound signal data to the wearable device and the mobile terminal device, and displaying them separately; wherein the bio-sound state monitoring report includes bio-sound data charts, bio-sound state analysis and suggestions. Through this bio-sound state monitoring method, a bio-sound state monitoring report in the form of charts, analysis, suggestions, etc. can be obtained, thereby improving the monitoring capability of the user's current bio-sound state, and being able to fully and accurately understand the user's current health status. BRIEF DESCRIPTION OF THE DRAWINGS
[0016] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying creative work.
[0017] Figure 1 A schematic diagram of the steps of a method for monitoring a biological sound state in one embodiment of the present invention; Figure 2 A schematic diagram of the steps of a method for monitoring a biological sound state in another embodiment of the present invention; Figure 3 A schematic diagram of the steps of determining whether a biological sound signal monitoring value is less than a preset biological sound signal value in one embodiment of the present invention; Figure 4 A schematic diagram of the steps of aggregating bio-sound signal monitoring values to form bio-sound signal data in one embodiment of the present invention; Figure 5 A schematic diagram of the steps of analyzing biological sound signal data and generating a biological sound status monitoring report in one embodiment of the present invention; Figure 6 Schematic diagram of the structure of a wearable device in one embodiment of the present invention.
[0018] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION
[0019] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0020] It should be noted that if the embodiments of the present invention involve directional indications (such as up, down, left, right, front, back, etc.), the directional indications are only used to explain the relative position relationship, movement status, etc. between the components in a certain specific posture. If the specific posture changes, the directional indication will also change accordingly.
[0021] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present invention, the descriptions of "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Therefore, the features limited to "first" and "second" may explicitly or implicitly include at least one of the features. In addition, if "and / or" or "and / or" appears in the full text, its meaning includes three parallel solutions. Taking "A and / or B" as an example, it includes solution A, solution B, or solutions that satisfy both A and B. In addition, the technical solutions between the various embodiments can be combined with each other, but it must be based on the ability of ordinary technicians in this field to implement. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by the present invention.
[0022] To achieve the above purpose, please refer to Figures 1 to 5 As shown, the present invention proposes a biological sound state monitoring method, and the steps of the biological sound state monitoring method include: S10, obtaining the biological sound signal monitoring value monitored by the wearable device; S20, collecting the bio-sound signal monitoring values to form bio-sound signal data; S30, analyzing the bio-sound signal data and generating a bio-sound status monitoring report; S40, transmitting the bio-sound status monitoring report to the wearable device and the mobile device; Among them, the bio-sound status monitoring report includes bio-sound data charts and bio-sound status assessment briefs.
[0023] In this embodiment, the bio-sound state monitoring method first obtains the bio-sound signal monitoring value monitored by the wearable device. The wearable device can be a smart watch, a smart bracelet, a smart necklace, a smart ring and other devices. The bio-sound refers to the relevant sounds generated during the heart beating, lung breathing, intestinal digestion, muscle contraction, joint movement and other processes, such as the heart sounds generated by the heart beating, such as the sound of atrial contraction and ventricular contraction, such as the breathing sounds, wheezing sounds, dry rales, etc. during lung breathing, and the bowel sounds during intestinal digestion. The bio-sound sensor is placed on the chest near the heart or lung area, or on the abdomen to obtain the vibration signal. The sound is transmitted to the outside world in the form of mechanical waves and can be detected by the corresponding The bio-sound sensor is received by a related device or sensor, such as a bone conduction sensor, a microphone, an acceleration sensor, an inertial sensor, a piezoelectric ceramic, a pressure sensor, or a vibration detection sensor, etc. The above are bio-sound sensors. The sensor structure in the present application includes at least one bio-sound sensor. The at least one bio-sound sensor can be one of the above sensors, or it can be a combination of the above sensors to obtain signals. There is no limitation on this. The bio-sound sensor receives pressure and sound wave vibrations, and forms an analog signal through the vibration. The analog signal is then converted into a digital signal. After signal amplification and signal filtering, the background noise is removed to obtain the final bio-sounds such as heart sound characteristics and breathing characteristics.
[0024] Furthermore, if Figure 1 As shown, the acquired bio-sound signal monitoring values are aggregated to form bio-sound signal data, that is, the bio-sound signal data includes multiple bio-sound signal monitoring values. The bio-sound signal data is analyzed to generate a bio-sound status monitoring report, and the bio-sound status monitoring report is transmitted to the wearable device and the mobile device, and displayed on the wearable device and the mobile device, respectively.
[0025] It can be understood that the bio-sound status monitoring method is implemented based on the bio-sound monitoring system, which includes a wearable device (i.e., a wearable device), a mobile client and a cloud server: the wearable device is used to collect heart sound data and send the heart sound data to the mobile client via Bluetooth; the mobile client is used to control and manage the wearable device, and send the obtained heart sound data to the cloud server, and display the bio-sound status monitoring report received from the cloud server to the user; the cloud server is used to process the obtained heart sound data through the heart sound data analysis module, give a heart sound classification diagnosis result, form a bio-sound status monitoring report and send it to the mobile client.
[0026] In the embodiment of the present invention, the mobile client runs on the smart phone, the wearable device and the mobile client communicate via Bluetooth, and the mobile client and the cloud server communicate via the smart phone wireless network.
[0027] The wearable device includes a heart sound data acquisition module and a data transmission module. The heart sound data acquisition module is a digital stethoscope, which collects heart sound data by placing the heart sound acquisition end close to the heart sound auscultation point. The data transmission module is used to interact with the mobile client for data.
[0028] The mobile client includes a mobile client user information management module, a mobile client heart sound data management module, an analysis result display module and a mobile client data transmission module. The mobile client user information management module is used to record and manage the personal information input by the user; the mobile client heart sound data management module is used to record and manage the obtained heart sound data; the analysis result display module is used to display the biological sound status monitoring report sent back by the cloud server; the mobile client data transmission module is used to interact with the wearable device and the cloud server. At the same time, the mobile client is responsible for communicating, managing and configuring with the wearable device, so that the user can observe the vital signs of the guardian, and is responsible for uploading the collected vital signs data to the cloud server, so as to facilitate the recording and management of the user's health status. At the same time, the user's vital sign information is stored in the cloud, and the user can view it without location and time restrictions. He can view his own vital sign information at any time, and it will not add extra memory burden to the user's device, and the user's information can be stored for a long time.
[0029] In addition, the APP on the same device can view the data of multiple "biological signal acquisition" sensors to monitor multiple guardians. At the same time, this APP is also suitable for institutions and can detect the vital signs of multiple guardians at the same time.
[0030] The cloud server includes a cloud server user information management module, a cloud server heart sound data management module, a heart sound data analysis module and a cloud server data transmission module; the cloud server user information management module is used to collect and manage the personal information of all users; the cloud server heart sound data management module is used to collect, store and manage the heart sound data of all users; the heart sound data analysis module is used to analyze the user's heart sound data, including artificial intelligence classification diagnosis; the cloud server data transmission module is used to interact with the mobile client for data.
[0031] It can be understood that the generated bio-sound status monitoring report includes a bio-sound data chart and a bio-sound status evaluation brief. The bio-sound data chart converts the acquired bio-sound signal data into a more intuitive line chart, bar chart, pie chart, etc. The chart can clearly understand the distribution status of the bio-sound data and its changes over time. At the same time, the bio-sound status monitoring report also includes a bio-sound status evaluation brief based on the bio-sound data chart, that is, the cloud server can analyze the bio-sound status, such as whether the current heart sound status is fast or slow, and give exercise and maintenance suggestions based on the analysis, such as suggesting increased exercise or improving diet, etc., so as to help users understand the user's current health status more comprehensively and accurately.
[0032] The steps of the bio-sound state monitoring method of this scheme include: obtaining the bio-sound signal monitoring value monitored by the wearable device; aggregating the bio-sound signal monitoring value to form bio-sound signal data; analyzing the bio-sound signal data and generating a bio-sound state monitoring report; transmitting the bio-sound signal data to the wearable device and the mobile device, and displaying them separately; wherein the bio-sound state monitoring report includes bio-sound data charts, bio-sound state analysis and suggestions. Through this bio-sound state monitoring method, a bio-sound state monitoring report in the form of charts, analysis, suggestions, etc. can be obtained, thereby improving the monitoring ability of the user's current bio-sound state, and being able to fully and accurately understand the user's current health status.
[0033] In one embodiment, if Figure 2 As shown, after obtaining the monitoring value of the bio-sound signal monitored by the wearable device, the steps of the bio-sound state monitoring method further include: S01. Set up a default contact; S02, determining whether the biological sound signal monitoring value is less than the preset biological sound signal value; S02a, if yes, storing the bio-sound signal monitoring value, and sending the bio-sound signal monitoring value to a preset contact; S02b. If not, an emergency call is made to a preset contact.
[0034] It can be understood that after the wearable device detects the bio-sound signal monitoring value, the cloud server will determine whether the bio-sound signal monitoring value is less than the preset bio-sound signal value. The preset bio-sound signal value is the safety value of the bio-sound state set by the current user himself in a healthy state, or the cloud server obtains the safety value of the user's bio-sound state in a healthy state through big data analysis. By judging the size relationship between the bio-sound signal monitoring value and the preset bio-sound signal value, the user's current health status is determined. If the bio-sound signal monitoring value is less than the preset bio-sound signal value, the user is in a healthy state. The cloud server stores the bio-sound signal monitoring value and sends the bio-sound signal monitoring value to the preset contact so that the preset contact can understand the user's current health status. Of course, the preset contact can also be the user himself; if the bio-sound signal monitoring value is greater than the preset bio-sound signal value, the user is in an unhealthy state or an emergency state, and the cloud server will urgently call the preset contact to help the user as soon as possible to prevent the user from falling into a dangerous state.
[0035] In one embodiment, if Figure 3 As shown, the step of determining whether the bio-sound signal monitoring value is less than the preset bio-sound signal value includes: S021. Acquiring state characteristics of biological sound signal data; S022. Constructing a biological sound state prediction model according to the state characteristics of the biological sound signal data; S023, obtaining characteristic parameters of the biological sound signal data, and inputting the characteristic parameters of the biological sound signal data into the biological sound state prediction model, and outputting the preset biological sound signal value; S024. Compare the bio-sound signal monitoring value with the preset bio-sound signal value to determine whether the bio-sound signal monitoring value is less than the preset bio-sound signal value.
[0036] In this embodiment, it is first necessary to obtain the state characteristics of the biological sound signal data. The state characteristics refer to the normal state of the biological sound signal data. The state characteristics are universal characteristics of biological sounds and are not affected by the differences in the monitored individuals. For example, taking the heart sound signal data obtained by a wearable device with a vibration sensor as the main monitoring sensor as an example, the state characteristics of the heart sound signal data include user characteristics, regional characteristics, time characteristics and vibration characteristics. User characteristics include but are not limited to age, height, weight, gender, etc. Regional characteristics include but are not limited to longitude and latitude, altitude, temperature, humidity, etc. Time characteristics include but are not limited to seasons and the wearing time of the same wearable device. Vibration characteristics include but are not limited to the phase, amplitude, frequency and other characteristics of the monitored heart sound vibration signal.
[0037] Furthermore, by collecting multiple of the above-mentioned user characteristics, regional characteristics, time characteristics and vibration characteristics, a bio-sound state prediction model is constructed using a large amount of data. The bio-sound state prediction model can simulate the bio-sound state under the above-mentioned different conditions. The user inputs the state characteristics of the bio-sound signal data into the bio-sound state prediction model in the form of feature parameters. The bio-sound state prediction model matches the internal historical state to obtain similar bio-sound signal values, and outputs them as preset bio-sound signal values.
[0038] Finally, compare the bio-sound signal monitoring value and the preset bio-sound signal value, that is, compare the currently monitored bio-sound signal monitoring value with the preset bio-sound signal value output by the bio-sound state prediction model to determine whether the bio-sound signal monitoring value is less than the preset bio-sound signal value, so as to determine whether the current bio-sound signal monitoring value is in a safe and healthy state.
[0039] In one embodiment, if Figure 3 As shown, the step of determining whether the bio-sound signal monitoring value is less than the preset bio-sound signal value also includes: S025. updating characteristic parameters of the biological sound signal data according to the biological sound signal monitoring value; S026. Performing sample amplification training on the biological sound state prediction model according to the characteristic parameters of the biological sound signal data to obtain amplified sample data; S027. Iteratively optimize the biological sound state prediction model based on the amplified sample data.
[0040] In this embodiment, since the number of initial samples of the bio-sound state prediction model is small, the degree of simulation of the preset bio-sound signal value by the model is poor, and it cannot accurately restore the user's current usage status and usage environment through the characteristic parameters of the input bio-sound signal data, and output the preset bio-sound signal value. Therefore, it is also possible to update the characteristic parameters of the bio-sound signal data, perform sample amplification training on the bio-sound state prediction model, and perform sample iterative optimization on the bio-sound state prediction model.
[0041] It can be understood that, based on the state characteristics of the original biological sound signal data, the user inputs the characteristic parameters of the biological sound signal data and agrees that the parameters are applied to the biological sound state prediction model for sample augmentation training, or the user actively updates the characteristic parameters of the biological sound signal data to the biological sound state prediction model, to obtain augmented sample data for sample augmentation training of the biological sound state prediction model. The augmented sample data is mainly based on the characteristic parameters of the biological sound signal data, and other auxiliary parameters that affect the biological sound state can be set, and the auxiliary parameters do not appear in the above-mentioned characteristic parameters of the biological sound signal data.
[0042] After obtaining the amplified sample data, the biological sound state prediction model is iteratively optimized through the newly added amplified sample data, continuously enhancing the degree of fit of the model to the biological sound state and improving the generalization performance of the model, so that the biological sound state can be accurately restored through the characteristic parameters of the biological sound signal data, and the preset biological sound signal value can be accurately output.
[0043] In one embodiment, if Figure 4 As shown, the step of collecting the bio-sound signal monitoring values to form the bio-sound signal data includes: S201, storing the collected biological sound signal monitoring values; S202, searching for abnormal vibration values in the biological sound signal monitoring values according to the received historical signal monitoring values of the wearable device; S203, eliminating abnormal vibration values in the biological sound signal monitoring values; S204, using bandpass filtering to filter out external low-frequency noise and high-frequency interference in the biological sound signal monitoring value; S205, using a wavelet threshold noise reduction method to reduce noise on the filtered biological sound signal monitoring value; S206. Smoothing the biological sound signal monitoring value to obtain biological sound signal data.
[0044] In this embodiment, the collected bio-sound signal monitoring values are stored to facilitate subsequent processing and analysis of the bio-sound signal monitoring values. The abnormal vibration value is searched in the bio-sound signal monitoring values among the historical signal monitoring values received from the wearable device. The abnormal vibration value can be the maximum or minimum value in the bio-sound signal monitoring value, or it can be a monitoring value that is obviously inconsistent with the user's bio-sound state, which determines whether the system considers that the bio-sound sensor is in a stable state.
[0045] Furthermore, the abnormal vibration values in the biological sound signal monitoring values are eliminated, and then the acceleration signal sampling data is discretely transformed by the FFT, i.e., fast Fourier transform method. The frequency part to be filtered out is directly set to zero, and then the FFT algorithm is used to perform discrete Fourier inverse transform on the filtered data to restore the time domain signal. The cutoff frequencies are set for low-frequency and high-frequency interference respectively, and high-pass filtering and low-pass filtering are performed respectively to achieve noise elimination.
[0046] Bio-acoustic signals are relatively weak and non-stationary signals. They are easily affected by the human body, sensors, environment, etc. during signal acquisition. Interference will inevitably be introduced into the signal, which mainly includes power frequency interference, baseline drift and high-frequency random interference. For baseline drift interference, we use db5 wavelet to decompose the original heart rate signal into 8 scales. After decomposition, the 8-scale low-frequency coefficients are set to zero to reconstruct the heart rate signal, and the baseline drift signal is completely eliminated from the heart rate signal; for high-frequency noise, we decompose the original signal into 8 scales, use the wavelet threshold method to denoise, and finally use the wavelet decomposition coefficients after filtering out the noise to reconstruct the heart rate signal, and the high-frequency noise is removed.
[0047] Then, the average value of a continuous biological sound signal monitoring value can be taken as a new data point, or different weights can be assigned to each biological sound signal monitoring value, usually with the most recent data point having a larger weight, to generate a smoothed biological sound signal monitoring value.
[0048] In the bio-acoustic signal monitoring value, the abnormal vibration value is searched for to identify possible abnormal vibrations, which may be caused by external interference, equipment failure or other abnormal conditions. A threshold can be set, and only when the vibration signal exceeds the threshold, it is regarded as an abnormal vibration value. In addition, the sliding window technology can be considered to analyze the data step by step to better capture the instantaneous abnormal changes. A preset threshold for the number of abnormal points is set. If the number of abnormal points found in the preset time period is less than or equal to this threshold, then the working state of the sensor can be considered to be stable. This is because under normal circumstances, the vibration of the sensor should fluctuate within a relatively stable range, and only when encountering abnormal conditions will it produce larger vibrations, that is, abnormal points. If the number of abnormal points is too large, it means that there may be continuous unstable factors affecting the performance of the sensor. If so, the bio-acoustic sensor is in a stable state within the preset time; if not, the bio-acoustic sensor is not in a stable state within the preset time: Based on the results of the previous step, it can be concluded that if the number of abnormal points meets the preset conditions, it means that the working state of the sensor in this time period is stable, otherwise it is considered that its working state is not stable and needs further inspection or adjustment.
[0049] It can be understood that through the above steps, the collected bio-sound signal monitoring values can be used to determine whether the bio-sound sensor is in a stable state within a preset time period, wherein the number of abnormal points is used as an indicator to measure the frequency of abnormal situations, which helps to promptly detect possible problems or fluctuations, that is, it can determine whether the bio-sound sensor is in a stable state.
[0050] In one embodiment, if Figure 5 As shown, the steps of analyzing the bio-sound signal data and generating a bio-sound status monitoring report include: S301, determining a wearable device feature code, and comparing it with a feature code database to determine the wearable device; S302, determining the type and collection location of the biological sound according to the biological sound signal data; S303, determining whether there is a noise signal in the biological sound signal data within a preset time; S303a, if yes, analyze the type of noise through the spectrum of the noise signal and output a biological sound status monitoring report; S303b. If not, output a bio-sound status monitoring report.
[0051] It can be understood that by determining the feature code of the wearable device and comparing it with the feature code database, the identity of the wearable device and the user using the wearable device can be determined, and then the historical bio-sound signal data of the user using the wearable device can be called. At the same time, the cloud server can determine the type of bio-sound and the collection location based on the bio-sound signal data, and determine whether there is a noise signal in the bio-sound signal data within a preset time. If there is a noise signal, the type of noise is analyzed and a bio-sound status monitoring report is output. If there is no noise signal, the bio-sound status monitoring report is directly output.
[0052] In one embodiment, the types of biological sounds include but are not limited to at least one of heart sounds, lung sounds, bowel sounds, vascular echoes, tracheal breath sounds, bronchial breath sounds, and joint movement sounds; Optionally, the acquisition position includes a cardiac auscultation position, and the cardiac auscultation position includes a mitral valve area, a pulmonary valve area, an aortic valve area, a second auscultation area of the aortic valve, and a tricuspid valve area; Optionally, the acquisition positions include lung auscultation positions, and the lung auscultation positions include the left front chest, the left chest, the left back, the right front chest, the right chest and the right back.
[0053] It can be understood that bio-sounds refer to related sounds produced during the process of heart beating, lung breathing, intestinal digestion, muscle contraction, joint movement, etc., such as heart sounds produced by heart beating, such as the sound of atrial contraction and ventricular contraction, such as breath sounds, wheezing sounds, dry rales, etc. during lung breathing, and bowel sounds during intestinal digestion. The bio-sound sensor 3 is placed on the chest near the heart or lung area, or on the abdomen to obtain vibration signals. The sound is transmitted to the outside world in the form of mechanical waves and can be received by related equipment or sensors.
[0054] It is understandable that the bio-sound vibration signals collected at different auscultation positions are also different. The common auscultation positions of the heart include but are not limited to the mitral valve area, pulmonary valve area, aortic valve area, aortic valve second auscultation area and tricuspid valve area. The auscultation positions of the lungs include but are not limited to the left anterior chest, left chest, left back, right anterior chest, right chest and right back. In addition, more accurate bio-sound signals can be obtained by collecting multiple times in the above-mentioned areas and averaging the collected bio-sound signal monitoring values.
[0055] An embodiment of the present invention provides a wearable device, such as Figure 6 As shown, the wearable device includes: at least one processor, at least one bio-sound sensor and a memory connected to the at least one processor in communication; wherein each bio-sound sensor is electrically connected to the at least one processor, the bio-sound sensor is configured to monitor bio-sound signals, and the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the bio-sound state monitoring method in the above-mentioned embodiment one.
[0056] Optionally, the headset includes a processor, a memory, a universal serial bus (USB) interface, a charging management module, a power management module, a battery, an antenna, an antenna, a mobile communication module, a wireless communication module, an audio module, a sensor module, a button, a motor, an indicator, etc. The sensor module may include a photoelectric volumetric pulse wave sensor, an acceleration (ACC) sensor, a temperature sensor, a bone conduction sensor, a gyroscope sensor, etc.
[0057] Optionally, the wearable device may be, for example, earphones, smart glasses, smart helmets, smart headbands, smart accessories (such as smart earrings, smart hairpins, smart hairbands, etc.), smart watches, smart rings, and other terminal devices with health detection functions. The operating system installed on the wearable device includes but is not limited to or other operating systems. In some embodiments, the wearable device may be a fixed device or a portable device. This application does not limit the specific type of the wearable device or the installed operating system.
[0058] The wearable device may include a processing device 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM) 1004. Various programs and data required for the operation of the wearable device are also stored in RAM 1004. The processing device 1001, ROM 1002, and RAM 1004 are connected to each other via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus.
[0059] Typically, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009.
[0060] The communication device can allow the wearable device to communicate with other devices wirelessly or wired to exchange data. Although the figure shows a wearable device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or provided alternatively.
[0061] The processor 110 may include an application processor (AP), a modem processor, a graphics processing unit (GPU), an image signal processor (ISP), a controller, a video codec, a digital signal processor (DSP), a baseband processor, and / or a neural-network processing unit (NPU), etc. Different processing units may be independent devices or integrated into one or more processors.
[0062] The controller can generate operation control signals according to the instruction operation code and timing signal to complete the control of instruction fetching and execution.
[0063] A memory may also be provided in the processor for storing instructions and data. In some embodiments, the memory in the processor is a cache memory. The memory may store instructions or data that the processor has just used or is cyclically used. If the processor needs to use the instruction or data again, it may be directly called from the memory. This avoids repeated access, reduces the waiting time of the processor, and thus improves the efficiency of the system.
[0064] In some embodiments, the processor may include one or more interfaces, such as a USB interface or the like.
[0065] The charging management module is used to receive charging input from a charger, where the charger can be a wireless charger or a wired charger.
[0066] The power management module is used to connect the battery, the charging management module and the processor. The power management module receives input from the battery and / or the charging management module to power the processor, the memory, and the wireless communication module.
[0067] The wireless communication function of the headset can be realized through an antenna, an antenna, a mobile communication module, a wireless communication module, etc.
[0068] Antennas and antennas are used to transmit and receive electromagnetic wave signals. Each antenna in the headset can be used to cover a single or multiple communication frequency bands. Different antennas can also be reused to improve the utilization of the antenna. For example, the antenna can be reused as a diversity antenna for a wireless local area network. In some other embodiments, the antenna can be used in combination with a tuning switch.
[0069] The mobile communication module can provide wireless communication solutions including G / G / G / G, etc. applied to the headset. The mobile communication module can include at least one filter, a switch, a power amplifier, a low noise amplifier (LNA), etc.
[0070] The wireless communication module can provide wireless communication solutions for headphones, including wireless local area networks (WLAN) (such as wireless fidelity (Wi-Fi) networks), Bluetooth (BT), global navigation satellite system (GNSS), frequency modulation (FM), near field communication (NFC), infrared technology (IR), etc.
[0071] In some embodiments, the antenna of the headset is coupled to the mobile communication module, and the antenna is coupled to the wireless communication module, so that the headset can communicate with the network and other devices through wireless communication technology.
[0072] The memory can be used to store computer executable program codes, and the executable program codes include instructions. The memory may include a program storage area and a data storage area. The program storage area may store an operating system, an application required for at least one function (such as a sound playback function, etc.), etc. The data storage area may store data created during the use of the headset (such as audio data, etc.), etc. In addition, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, a universal flash storage (UFS), etc. The processor executes various functional applications and data processing of the headset by running instructions stored in the memory and / or instructions stored in a memory provided in the processor.
[0073] In some embodiments of the present application, a health detection model and / or a recognition model may be stored in the memory. The health detection model may be used to determine the health status of the user, and the recognition model may be used to determine whether the acquired bio-sound signal data is the bio-sound signal data of the user.
[0074] It can be understood that the various models involved in the embodiments of the present application, including but not limited to health detection models, recognition models, etc., can be various machine learning models and / or deep learning models, and the present application does not limit this.
[0075] It can also be understood that in the embodiments of the present application, the data input into the model can be unprocessed data (such as signal processing, endpoint segmentation, feature extraction, etc.) or processed data, such as data after feature extraction, and the present application does not limit this.
[0076] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication device 1009, or installed from the storage device 1003, or installed from the ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment of the present disclosure are executed.
[0077] The wearable device provided by the present invention adopts the bio-sound state monitoring method of the above embodiment, which solves the technical problem that the user of the prior art cannot know the specific meaning and state represented by the data, and thus cannot fully and accurately understand his current state. Compared with the prior art, the beneficial effects of the wearable device provided by the embodiment of the present invention are the same as the beneficial effects of the bio-sound state monitoring method provided by the above embodiment, and the other technical features in the wearable device are the same as the features disclosed in the above embodiment method, which will not be repeated here.
[0078] It should be understood that the various parts of the present disclosure can be implemented with hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.
[0079] In one embodiment, the bio-sound sensor includes but is not limited to one of a bone conduction sensor, a microphone, an acceleration sensor, an inertial sensor, a piezoelectric ceramic, a pressure sensor, and a vibration detection sensor.
[0080] It can be understood that the bio-sound sensor can be one or more of a bone conduction sensor, a microphone, an acceleration sensor, an inertial sensor, a piezoelectric ceramic, a pressure sensor, and a vibration detection sensor, and when multiple of the above sensors are provided, they can be the same sensor, or different sensors can be used together to adapt to different detection areas and detection environments.
[0081] Among them, if the bio-sound sensor is a bone conduction sensor, it can directly contact the bones and detect the propagation of bio-sound in the body by detecting the vibration of the body bones; if the bio-sound sensor is a microphone, it can detect the bio-sound generated inside or on the body surface through the vibration sound waves in the air; if the bio-sound sensor is an accelerometer sensor, when the heart beats or the lungs breathe, the body will produce tiny movements and vibrations, and the accelerometer can obtain the changes in the above movements; if the bio-sound sensor is a pressure sensor, the pressure sensor can be placed on the surface of the body to capture the pressure changes caused by the heart beating or lung activity. All of the above types of sensors can convert tiny vibrations into electrical signals and effectively extract the characteristics of bio-sounds to realize the detection of bio-sounds.
[0082] Furthermore, the bio-sound sensor may also be a photoplethysmography sensor, which can obtain a PPG signal by measuring the attenuated light reflected and absorbed by human blood vessels and tissues through photoplethysmography (PPG), based on an LED light source and a detector. In some embodiments of the present application, the wearable device analyzes the PPG signal obtained by the photoplethysmography sensor to obtain the user's physiological parameters, such as adjacent R-wave intervals (R-R interval, RRI), heart rate, respiratory rate, blood oxygen, etc. Optionally, the user's physiological parameters can be used to determine the user's health status.
[0083] Alternatively, the bio-sound sensor is an acceleration sensor, which can detect the magnitude of the acceleration of the wearable device in all directions (generally three axes). When the wearable device is stationary, the magnitude and direction of gravity can be detected. It can also be used to identify the posture of the wearable device, and is applied to horizontal and vertical screen switching, pedometers and other applications. In some embodiments of the present application, the acceleration signal of the acceleration sensor can be used to determine the user state, such as: stationary state, motion state, etc., because the user's physiological parameters (such as: breathing rate, heart rate, blood oxygen, etc.) may be different in different states. Therefore, in order to improve the accuracy of the user's physiological parameters obtained, the wearable device can also determine the user's state through the acceleration signal of the acceleration sensor, and further assist in determining the user's physiological parameters. In other embodiments of the present application, due to the user's coughing, the user's body will produce corresponding coughing movements, such as: head shaking, facial tremor, mandibular tremor, etc., so the acceleration sensor can also be used to measure the human body vibration signal, which can be used to determine whether the user is coughing, and can also be used as bio-sound signal data to determine the user's health status.
[0084] The present invention also proposes an intelligent monitoring system, which includes a wearable device, a mobile device and a cloud server, wherein the mobile device is communicatively connected to the wearable device, and the cloud server is communicatively connected to the mobile device. The specific structure of the wearable device refers to the aforementioned embodiment. Since the present intelligent monitoring system adopts all the technical solutions of all the aforementioned embodiments, it has at least all the beneficial effects brought by the technical solutions of the aforementioned embodiments, which will not be described one by one here.
[0085] It is understandable that the mobile terminal is an electronic device, and the electronic device may be, for example, a mobile phone, a personal computer (PC), a tablet computer (Pad), a laptop, a desktop computer, a laptop, a computer with a transceiver function, a wearable device, a vehicle-mounted device, an artificial intelligence (AI) device, and other terminal devices. The operating system installed in the electronic device includes but is not limited to or other operating systems. In some embodiments, the electronic device may be a fixed device or a portable device. The present application does not limit the specific type of electronic device or the installed operating system.
[0086] The wearable device can establish a communication connection with the mobile terminal and the cloud server through wired communication technology and / or wireless communication technology. Among them, the wireless communication technology includes but is not limited to one or more of the following: near field communication (NFC), Bluetooth (BT) (for example, traditional Bluetooth or Bluetooth low energy (BLE)), wireless local area network (WLAN) (such as wireless fidelity (Wi-Fi) network), Zigbee, frequency modulation (FM), infrared (IR), etc.
[0087] In one embodiment, the wearable device and the mobile terminal support a proximity discovery function. For example, when the wearable device is close to the electronic device, the wearable device and the mobile terminal can discover each other, and then establish a wireless communication connection such as a Wi-Fi peer to peer (PP) connection, a Bluetooth connection, etc. After the wireless communication connection is established, the wearable device, the mobile terminal, and the cloud server can realize signal interaction through the wireless communication connection.
[0088] In one embodiment, the wearable device establishes a wireless communication connection with the mobile terminal and the cloud server through a local area network. For example, the wearable device, the mobile terminal and the cloud server are all connected to the same router.
[0089] In one embodiment, the wearable device establishes a wireless communication connection with the mobile terminal and the cloud server through a cellular network, the Internet, etc. For example, the mobile terminal and the cloud server access the Internet through a router, and the wearable device accesses the Internet through a cellular network; then, the wearable device establishes a wireless communication connection with the mobile terminal and the cloud server.
[0090] The above description is only an exemplary embodiment of the present invention, and does not limit the patent scope of the present invention. All equivalent structural changes made by using the contents of the present invention specification and drawings under the technical concept of the present invention, or directly / indirectly applied in other related technical fields are included in the patent protection scope of the present invention.
Claims
1. A biological sound state monitoring method, characterized in that: The steps of the bio-sound state monitoring method include: Obtain the bio-sound signal monitoring value detected by the wearable device; Aggregating the bio-sound signal monitoring values to form bio-sound signal data; Analyzing the bio-sound signal data and generating a bio-sound status monitoring report; Transmitting the bio-sound status monitoring report to the wearable device and the mobile device; The bio-sound status monitoring report includes a bio-sound data chart and a bio-sound status assessment brief.
2. The biological sound state monitoring method according to claim 1, characterized in that: After obtaining the biological sound signal monitoring value monitored by the wearable device, the biological sound state monitoring method further includes: Set default contacts; Determining whether the bio-sound signal monitoring value is less than a preset bio-sound signal value; If yes, storing the bio-sound signal monitoring value, and sending the bio-sound signal monitoring value to the preset contact; If not, an emergency call is made to the preset contact.
3. The biological sound state monitoring method according to claim 2, characterized in that: The step of determining whether the bio-sound signal monitoring value is less than a preset bio-sound signal value comprises: Acquiring state characteristics of biological sound signal data; Constructing a bio-sound state prediction model according to the state characteristics of the bio-sound signal data; Acquiring characteristic parameters of the bio-sound signal data, and inputting the characteristic parameters of the bio-sound signal data into the bio-sound state prediction model, and outputting the preset bio-sound signal value; The bio-sound signal monitoring value is compared with the preset bio-sound signal value to determine whether the bio-sound signal monitoring value is less than the preset bio-sound signal value.
4. The biological sound state monitoring method according to claim 3, characterized in that: The step of determining whether the bio-sound signal monitoring value is less than a preset bio-sound signal value further includes: updating the characteristic parameters of the bio-sound signal data according to the bio-sound signal monitoring value; Performing sample augmentation training on the bio-sound state prediction model according to the characteristic parameters of the bio-sound signal data to obtain augmented sample data; The bio-sound state prediction model is iteratively optimized according to the amplified sample data.
5. The biological sound state monitoring method according to claim 1, characterized in that: The step of collecting the bio-sound signal monitoring values to form bio-sound signal data comprises: Storing the collected biological sound signal monitoring values; According to the received historical signal monitoring value of the wearable device, searching for abnormal vibration value in the biological sound signal monitoring value; Eliminating the abnormal vibration value in the biological sound signal monitoring value; Using bandpass filtering to filter out external low-frequency noise and high-frequency interference in the biological sound signal monitoring value; Using a wavelet threshold noise reduction method to reduce noise on the filtered biological sound signal monitoring value; The bio-sound signal monitoring value is smoothed to obtain the bio-sound signal data.
6. The biological sound state monitoring method according to any one of claims 1 to 5, characterized in that: The step of analyzing the bio-sound signal data and generating a bio-sound status monitoring report comprises: Determine the wearable device feature code and compare it with the feature code database to identify the wearable device; Determining the type and collection location of the biological sound according to the biological sound signal data; Determining whether there is a noise signal in the bio-sound signal data within a preset time; If yes, the type of noise is analyzed through the spectrum of the noise signal, and the biological sound status monitoring report is output; If not, the bio-sound status monitoring report is output.
7. The biological sound state monitoring method according to claim 6, characterized in that: The types of biological sounds include but are not limited to at least one of heart sounds, lung sounds, bowel sounds, vascular echoes, tracheal breath sounds, bronchial breath sounds, and joint movement sounds; And / or, the acquisition position includes a cardiac auscultation position, and the cardiac auscultation position includes a mitral valve area, a pulmonary valve area, an aortic valve area, a second auscultation area of the aortic valve, and a tricuspid valve area; And / or, the acquisition positions include lung auscultation positions, and the lung auscultation positions include the left front chest, the left chest, the left back, the right front chest, the right chest and the right back.
8. A wearable device, characterized in that: The wearable device comprises: at least one processor; at least one bio-sound sensor, each of the bio-sound sensors being electrically connected to at least one of the processors, the bio-sound sensor being configured to monitor a bio-sound signal; and a memory communicatively coupled to the at least one processor; The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the steps of the biological sound state monitoring method according to any one of claims 1 to 7.
9. The wearable device according to claim 8, characterized in that: The bio-sound sensor includes but is not limited to one of a bone conduction sensor, a microphone, an acceleration sensor, an inertial sensor, a piezoelectric ceramic, a pressure sensor, and a vibration detection sensor.
10. An intelligent monitoring system, characterized in that: The intelligent monitoring system comprises: The wearable device according to any one of claims 8 or 9; A mobile device, the mobile device being communicatively connected to the wearable device; and A cloud server is communicatively connected with the mobile device.