Sleep monitoring method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention discloses a sleep monitoring method and device, electronic equipment and a storage medium. The sleep monitoring method comprises the steps of receiving a reflection signal sent by a millimeter wave radar monitoring user, processing the reflection signal, generating multi-frame point cloud information, and determining sleep information of the user according to the change degree of the point cloud information in a monitoring area. According to the embodiment of the invention, the reflected signal of the position of the target user is acquired through the millimeter-wave radar, so that the user does not need to wear any equipment, the use is more comfortable, the reflected signal acquired by the millimeter-wave radar generates the point cloud information accurately representing the user state, the sleep condition of the user is accurately identified, and the user experience is improved. Therefore, the sleep health condition of the user can be accurately evaluated, and the user experience is further improved.

Description

Technical Field

[0001] The present invention relates to the field of signal monitoring technology, and in particular to a sleep monitoring method, device, electronic equipment and storage medium. Background Art

[0002] As the pace of life in modern society gradually accelerates, sleep problems are becoming more and more important. Therefore, how to monitor the user's sleep condition has become an issue that needs to be considered when paying attention to human health.

[0003] At present, traditional wearable devices or mobile phone terminals use close-range sleep stage recognition methods that require users to actively wear relevant sensor devices or keep the phone within a close range of the body, and use instruments such as gyroscopes and accelerometers to capture the user's body movements during sleep, or use heart rate sensors to obtain the user's heart rate data during sleep, and combine signal processing and data analysis to obtain the user's sleep status.

[0004] However, wearing devices to monitor the user's sleep will affect the user's sleep comfort, and there are also additional burdens such as the need to charge the device and perform regular maintenance. In other words, there are many limitations to wearing corresponding devices for sleep monitoring, which affects the user experience. Summary of the invention

[0005] In order to solve the above problems, embodiments of the present invention provide a sleep monitoring method, device, electronic device and storage medium.

[0006] In a first aspect, an embodiment of the present invention discloses a sleep monitoring method, the method comprising:

[0007] Receive the reflected signal sent by the millimeter wave radar monitoring target user;

[0008] Processing the reflected signal to generate multi-frame point cloud information, wherein the point cloud information is used to determine the monitoring area;

[0009] The sleep information of the target user is determined according to the degree of change of the point cloud information in the monitoring area.

[0010] Optionally, the processing the reflected signal to generate multi-frame point cloud information includes:

[0011] Converting the reflected signal to generate a distance matrix, wherein the distance matrix includes the reflection distance and Doppler velocity of the reflected signal;

[0012] Point cloud information of a plurality of consecutive frames is generated according to the reflection distance and the Doppler velocity.

[0013] Optionally, after generating a plurality of continuous frames of point cloud information according to the reflection distance and the Doppler velocity, the method further includes:

[0014] The point cloud information of multiple consecutive frames is superimposed according to a preset time window to generate a point cloud data frame;

[0015] Clustering all point cloud data frames within a first preset time period to obtain multiple cluster sets;

[0016] A monitoring area for monitoring the sleep of a target user is determined according to an average Doppler velocity of the point cloud data frames in the cluster.

[0017] Optionally, determining the sleep information of the target user according to the degree of change of the point cloud information in the monitoring area includes:

[0018] Obtaining a degree of change in the number of points in the point cloud data frame in the monitoring area within a first preset time period;

[0019] If the degree of change of the number of points in the monitoring area is less than a first change threshold, it is confirmed that the target user is stationary, and the sleeping time of the target user is recorded;

[0020] If the degree of change of the number of points in the monitoring area is greater than a second change threshold, it is confirmed that the target user is not stationary, and the awake time of the target user is recorded;

[0021] The sleep information of the target user is determined according to the sleeping time and waking time of the target user.

[0022] Optionally, after determining the sleep information of the target user according to the degree of change of the point cloud information in the monitoring area, the method further includes:

[0023] Recording the sleep information of the target user within a second preset time period to determine the sleep health condition of the target user;

[0024] The sleep health status is sent to the target user.

[0025] In a second aspect, an embodiment of the present invention further provides a sleep monitoring device, the device comprising:

[0026] A signal receiving module is used to receive the reflected signal sent by the millimeter wave radar monitoring target user;

[0027] A signal processing module, used to process the reflected signal to generate multi-frame point cloud information, wherein the point cloud information is used to determine the monitoring area;

[0028] The information determination module is used to determine the sleep information of the target user according to the degree of change of the point cloud information in the monitoring area.

[0029] Optionally, the signal processing module includes:

[0030] A processing submodule, configured to convert the reflected signal to generate a distance matrix, wherein the distance matrix includes a reflection distance and a Doppler velocity of the reflected signal;

[0031] The first generating submodule is used to generate point cloud information of a plurality of consecutive frames according to the reflection distance and the Doppler velocity.

[0032] Optionally, the signal processing module includes:

[0033] The second generation submodule is used to perform superposition processing on the point cloud information of multiple consecutive frames according to a preset time window to generate a point cloud data frame;

[0034] A clustering submodule, used for clustering all point cloud data frames within a first preset time period to obtain a plurality of cluster sets;

[0035] The area determination submodule is used to determine the monitoring area for monitoring the sleep of the target user according to the average Doppler velocity of the point cloud data frame in the clustering concentration.

[0036] Optionally, the information determination module includes:

[0037] An acquisition submodule, used to acquire a degree of change in the number of points in the point cloud data frame in the monitoring area within a first preset time period;

[0038] A first recording submodule is used to confirm that the target user is stationary and record the target user's sleeping time if the degree of change of the number of points in the monitoring area is less than a first change threshold;

[0039] A second recording submodule is configured to confirm that the target user is not stationary and record the awake time of the target user if the degree of change of the number of points in the monitoring area is greater than a second change threshold;

[0040] The determination submodule is used to determine the sleep information of the target user according to the sleeping time and waking time of the target user.

[0041] Optionally, the device further comprises:

[0042] An information recording module, used to record the sleep information of the target user within a second preset time period, and determine the sleep health condition of the target user;

[0043] A sending prompt module is used to send the sleep health status to the target user.

[0044] In a third aspect, an embodiment of the present invention further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of any of the sleep monitoring methods described above are implemented.

[0045] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the sleep monitoring methods described above.

[0046] The sleep monitoring method provided by the embodiment of the present invention monitors the target user through a millimeter-wave radar, receives the reflected signal sent by the millimeter-wave radar, processes the reflected signal, generates multiple frames of point cloud information, and determines the sleep information of the target user according to the degree of change of the point cloud information in the monitoring area. The embodiment of the present invention uses a millimeter-wave radar device to collect the reflected signal at the location of the target user. The user does not need to wear any equipment, which is more comfortable to use. The millimeter-wave radar has a low resolution, which is beneficial to protecting the privacy of the user. Through the point cloud generation algorithm, the reflected signal collected by the millimeter-wave radar is generated into point cloud information that accurately represents the user's status, thereby accurately identifying the user's sleep condition. The point cloud information can be used to dynamically monitor the user's status, thereby improving the accuracy of sleep time monitoring, accurately evaluating the user's sleep health, and further enhancing the user's experience.

[0047] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0049] Figure 1 This is one of the step flow charts of a sleep monitoring method provided by an embodiment of the present invention;

[0050] Figure 2 yes Figure 1 One of the flowcharts of step 102 of a sleep monitoring method according to an embodiment of the present invention is provided;

[0051] Figure 3 yes Figure 1A second flowchart of step 102 of a sleep monitoring method according to an embodiment of the present invention is provided;

[0052] Figure 4 yes Figure 1 A flowchart of step 103 of a sleep monitoring method according to an embodiment of the present invention is provided;

[0053] Figure 5 This is a second step flow chart of a sleep monitoring method provided by an embodiment of the present invention;

[0054] Figure 6 is a scene schematic diagram of a sleep monitoring method provided in an embodiment of the present application;

[0055] Figure 7 is a structural schematic diagram of a sleep monitoring device provided by an embodiment of the present invention;

[0056] Figure 8 It is a structural schematic diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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.

[0058] Figure 1 A schematic flow chart of a sleep monitoring method provided by some embodiments of the present invention is schematically shown, and the method comprises:

[0059] Step 101: Receive a reflected signal sent by a millimeter-wave radar monitoring target user.

[0060] In an embodiment of the present invention, in order to realize non-contact and accurate monitoring of the target user's sleep condition, this embodiment monitors the target user through a millimeter wave radar, and the signal processor processes and analyzes the reflected signal to obtain the target user's sleep condition.

[0061] It should be noted that millimeter waves refer to electromagnetic waves with a wavelength of 1 to 10 mm, which are located in the wavelength range where microwaves and far-infrared waves overlap, and therefore have the characteristics of two spectra. Figure 6 The schematic diagram of the scenario of the sleep monitoring method provided by an embodiment of the present invention is shown. In this embodiment, a millimeter wave radar is used to continuously transmit millimeter wave signals, which are reflected by the human body and received by the radar's receiving antenna.

[0062] Specifically, the millimeter-wave radar can continuously emit signals after being started. Each signal reaches the receiving end of the millimeter-wave radar after being reflected by the room and the human body. The millimeter-wave radar receiving end processes the signal to obtain a reflected signal, and sends the reflected signal to the signal processor. The signal processor receives the reflected signal sent by the target user monitored by the millimeter-wave radar, and performs signal processing and analysis. For example, in an embodiment of the present invention, the transformation of the reflected signal from the time domain to the frequency domain can be achieved by fast Fourier transform.

[0063] The embodiment of the present invention can pre-set the startup parameters of the millimeter wave radar, and the startup parameters may include parameters such as the monitoring range and the monitoring time window. Among them, the monitoring range can be set according to the size of the room, and the time window can be set according to the needs of the target user. The longer the time window, the more it can reduce the impact of the target user's micro-movement on the monitoring distance. The size of the time window can be set manually or by program, and this embodiment does not make any specific limitation on this.

[0064] For example, this embodiment is described by taking the Texas Instruments (TI) millimeter wave radar IWR 1443 as an example. The millimeter wave radar has 3 transmitting antennas and 4 receiving antennas, and can output 10 frames of point cloud information per second to determine the target user's sleeping and waking time.

[0065] In the embodiment of the present invention, the transmission signal at the location of the target user can be enhanced by the millimeter wave radar, and the signal reflected back by the target user received by the receiving end will also be enhanced, so that the present invention can perform non-contact and long-distance monitoring of the user's sleep condition.

[0066] Step 102: Process the reflected signal to generate multiple frames of point cloud information, wherein the point cloud information is used to determine the monitoring area.

[0067] In an embodiment of the present invention, after receiving the reflected signal sent by the millimeter wave radar, the signal processor obtains a distance matrix by performing one-dimensional and two-dimensional fast Fourier transform processing on the reflected signal, and then processes the obtained distance matrix to output point cloud information in frames.

[0068] It should be noted that, in this embodiment, a point cloud data analysis algorithm model may be pre-trained in a signal processor, the reflected signal may be input into the model for processing, and multiple frames of point cloud information may be output, or a point cloud data analysis algorithm may be called to convert the reflected signal to obtain multiple frames of point cloud information. This embodiment will not be described in detail here.

[0069] Specifically, since the millimeter wave radar can output at least 10 frames of point cloud information per second, in order to collect point cloud information and determine the user's sleep state, each frame of point cloud information includes the X, Y, Z three-dimensional coordinates, three-dimensional speed and signal strength of multiple points. In this embodiment, the three-dimensional coordinate information and speed information are mainly used. It should be noted that the distance matrix generated by the signal processor after converting the reflected signal includes the reflection distance and Doppler speed of the reflected signal, which is used to determine the monitoring area and the user's sleep state.

[0070] Step 103: determining the sleep information of the target user according to the degree of change of the point cloud information in the monitoring area.

[0071] In the embodiment of the present invention, the point cloud data analysis module in the signal processor determines the sleep information of the target user according to the degree of change of the point cloud information in the monitoring area. Specifically, multiple frames of point cloud information are superimposed in advance according to a preset time window to generate a point cloud data frame, which is used to characterize the regional conditions mapped by all reflection signals within a certain time period, so as to determine the monitoring area and the target user in the monitoring area.

[0072] In this embodiment, the sleep information of the target user is determined based on the degree of change of the point cloud data frame further generated by the point cloud information in the monitoring area, which can specifically include obtaining the degree of change of the number of points in the point cloud data frame in the monitoring area within a preset time period, wherein the degree of change of the number of points is the rate of change of the points in the point cloud data frame, including changes from more to less and from less to more.

[0073] Specifically, by determining whether the target user is stationary based on the change from more to less and / or the degree of change from less to more of the point cloud data frames further generated based on the point cloud information in the monitoring area, the target user's sleeping time and waking time can be determined, and the sleep duration can be calculated based on the sleeping time and waking time.

[0074] In the embodiment of the present invention, the accurate sleeping time and waking time of the user, as well as the sleeping duration of the user can be obtained based on the point cloud data frame, so as to provide the user with some contents related to the sleep condition analysis.

[0075] The sleep monitoring method provided by the embodiment of the present invention monitors the target user through a millimeter-wave radar, receives the reflected signal sent by the millimeter-wave radar, processes the reflected signal, generates multiple frames of point cloud information, and determines the sleep information of the target user according to the degree of change of the point cloud information in the monitoring area. The embodiment of the present invention uses a millimeter-wave radar device to collect the reflected signal at the location of the target user. The user does not need to wear any equipment, which is more comfortable to use. The millimeter-wave radar has a low resolution, which is beneficial to protecting the privacy of the user. Through the point cloud generation algorithm, the reflected signal collected by the millimeter-wave radar is generated into point cloud information that accurately represents the user's status, thereby accurately identifying the user's sleep condition. The point cloud information can be used to dynamically monitor the user's status, thereby improving the accuracy of sleep time monitoring, accurately evaluating the user's sleep health, and further enhancing the user's experience.

[0076] Further, see Figure 2 , showing Figure 1 One of the flowcharts of step 102 of the sleep monitoring method provided is substantially the same as the sleep monitoring method provided in the first embodiment of the present invention. Step 102 may include:

[0077] Step 1021: convert the reflected signal to generate a distance matrix, wherein the distance matrix includes the reflection distance and Doppler velocity of the reflected signal.

[0078] In the embodiment of the present invention, after receiving the reflected signal, the signal processor performs a fast Fourier transform on the reflected signal to generate a distance matrix, wherein the distance matrix may be a distance-Doppler velocity matrix, which is used to represent the distance and Doppler velocity of the signal reflected from the target person, that is, the distance matrix includes the reflection distance and Doppler velocity of the reflected signal. In this embodiment, the distance-Doppler matrix is ​​obtained by performing one-dimensional and two-dimensional fast Fourier transform on the reflected signal. It should be noted that the fast Fourier transform (Fast Fourier Transform, FFT) is an efficient and fast calculation method for calculating discrete Fourier transform using a computer. The use of fast Fourier transform can greatly reduce the number of multiplications required for the computer to calculate the discrete Fourier transform, especially the more the number of sample points to be transformed, the more significant the saving of the algorithm calculation amount.

[0079] Step 1022, generating point cloud information of multiple consecutive frames according to the reflection distance and Doppler velocity.

[0080] In the embodiment of the present invention, according to the reflection distance and Doppler velocity, the distance matrix obtained is subjected to CFAR (Constant False Alarm Rate Detector, a detector under constant false alarm probability) detection and DOA estimation to generate point cloud information of multiple continuous frames. Among them, CFAR is a method of radar target detection, which is used to determine whether the target exists; DOA estimation is also called direction of arrival estimation or spatial spectrum estimation, which is one of the two main directions of array signal processing and is used to process array signals.

[0081] The embodiment of the present invention converts the reflected signal to generate a distance matrix, and generates point cloud information of multiple continuous frames according to the reflection distance and Doppler velocity in the distance matrix, thereby processing and analyzing the reflected signal into information that can accurately characterize the target, thereby facilitating further judgment of the target user's sleep condition.

[0082] Further, see Figure 3 , showing Figure 1 The second flowchart of step 102 of the sleep monitoring method provided is substantially the same as the sleep monitoring method provided in the first embodiment of the present invention. Step 102 may further include:

[0083] Step 1023 , the point cloud information of multiple consecutive frames are superimposed according to a preset time window to generate a point cloud data frame.

[0084] Step 1024: cluster all point cloud data frames within the first preset time period to obtain a plurality of cluster sets.

[0085] Step 1025 , determining a monitoring area for monitoring the target user's sleep according to the average Doppler velocity of the point cloud data frame in the cluster.

[0086] It should be noted that, in the above steps 1023 to 1025, in order to improve the accuracy of monitoring the user's sleep and reduce unnecessary calculations, the embodiment of the present invention first determines the monitoring area of ​​the user after determining the point cloud information. In this embodiment, the monitoring area can be the area of ​​the bed. Specifically, the point cloud information of multiple consecutive frames is superimposed according to a preset time window to generate a point cloud data frame, and then all the point cloud data frames within the first preset time period are clustered to obtain multiple cluster sets. According to the average Doppler velocity of the point cloud data frames in the cluster sets, the monitoring area for monitoring the target user's sleep is determined.

[0087] In this embodiment, in the embodiment of the present invention, the preset time window is used to update data in a timely manner, and the preset time window is slid forward to estimate the position and status of the target user based on the point cloud information of the entire window. The setting duration of the time window is not specifically limited. The first preset time period is used to count the point cloud information within a short period of time. The average Doppler velocity of the clustered point cloud data frame is pre-calculated based on the Doppler velocity of the point cloud, which will not be described one by one here.

[0088] For example, first, the directly extracted point cloud information is superimposed according to the time window, for example, the information of all points within 5 seconds is superimposed together as a new point cloud data frame, and then all the point cloud data frames of the whole night are superimposed together, and the DBSCAN algorithm is used to perform cluster analysis on them. The monitoring area, i.e. the bed area, is delineated according to the average Doppler velocity of the point cloud in each cluster set, so as to facilitate the statistics of the point cloud information in the monitoring area and analyze the user's sleep condition.

[0089] Further, see Figure 4 , showing Figure 1 A flowchart of step 103 of the sleep monitoring method is provided. The method is substantially the same as the sleep monitoring method provided in the first embodiment of the present invention. Step 103 may include:

[0090] Step 1031, obtaining the degree of change in the number of points in the point cloud data frame in the monitoring area within a first preset time period.

[0091] In the embodiment of the present invention, in order to determine the sleep state of the target user, the degree of change of the number of points in the point cloud data frame in the monitoring area within the first preset time period is obtained, and the sleeping time and the awake time are determined according to whether the degree of change of the number of points meets the conditions. The first preset time period is set according to the user's sleeping habits or determined according to a large amount of sleep data, and can be set according to user needs, which is not specifically limited here.

[0092] Step 1032: If the degree of change of the number of points in the monitoring area is less than the first change threshold, it is confirmed that the target user is stationary, and the target user's sleeping time is recorded.

[0093] Step 1033: If the degree of change of the points in the monitoring area is greater than the second change threshold, it is confirmed that the target user is not still, and the awake time of the target user is recorded.

[0094] In the embodiment of the present invention, if the degree of change of the number of points in the monitoring area is less than the first change threshold, it is confirmed that the target user is stationary and the target user's sleeping time is recorded; if the degree of change of the number of points in the monitoring area is greater than the second change threshold, it is confirmed that the target user is not stationary and the target user's awake time is recorded. The first change threshold is a change rate threshold of the number of points from more to less, which is used to assess whether the target user remains asleep within a preset time, and the second change threshold is a change rate threshold of the number of points from less to more, which is used to assess whether the target user stops sleeping. The specific setting value can be determined based on a large number of signal samples of the sleep stage.

[0095] Step 1034 , determining the sleep information of the target user according to the target user's sleeping time and waking time.

[0096] The embodiment of the present invention determines the degree of change in the number of points in the point cloud data frame in the monitoring area within the first preset time period, determines the degree of change in the number of points in the point cloud data frame, determines the sleeping time and the waking time of the target user, and thus obtains the sleep information of the target user, and generates point cloud information that accurately represents the user's state from the reflected signal collected by the millimeter-wave radar, thereby accurately identifying the user's sleep condition. The point cloud information can be used to dynamically monitor the user's state, thereby improving the accuracy of sleep time monitoring and accurately evaluating the user's sleep health.

[0097] The second embodiment of the present invention relates to a sleep monitoring method, which is basically the same as the sleep monitoring method provided by the first embodiment of the present invention, except that: Figure 5 , shows a second step flow chart of the sleep monitoring method provided by an embodiment of the present invention, the method comprising:

[0098] Step 101: Receive a reflected signal sent by a millimeter-wave radar monitoring target user.

[0099] Step 102: Process the reflected signal to generate multiple frames of point cloud information, wherein the point cloud information is used to determine the monitoring area.

[0100] Step 103: determining the sleep information of the target user according to the degree of change of the point cloud information in the monitoring area.

[0101] The above steps 101 to 103 are described in the foregoing description and will not be repeated here.

[0102] Step 104 , recording the target user's sleep information within a second preset time period, and determining the target user's sleep health condition.

[0103] In an embodiment of the present invention, the sleep health condition of the target user is determined by recording the sleep information of the target user within a second preset time period. The second preset time period is a longer period for monitoring the user. Specifically, the sleep detection results of multiple nights can be recorded, that is, some sleep condition analysis-related content can be provided to the user based on the bedtime, wakefulness time, and sleep duration of multiple nights. For example, when the sleep time is relatively short, the user is reminded to pay attention to sleep; when the user falls asleep relatively late, the user is reminded to go to bed earlier, and so on.

[0104] Step 105: Send the sleep health status to the target user.

[0105] In an embodiment of the present invention, the sleep status of the target user over a longer period is fed back to the user in a timely manner, so as to provide intimate reminders to the user on sleep quality and health issues. On the basis of accurately identifying the user's sleep status, improving the accuracy of sleep time monitoring, and accurately evaluating the user's sleep health status, the interaction between the monitoring device and the user can be increased, thereby further improving the user experience.

[0106] Reference Figure 7 , shows a schematic structural diagram of a sleep monitoring device provided by an embodiment of the present invention, the device may include:

[0107] The signal receiving module 201 is used to receive the reflected signal sent by the millimeter wave radar monitoring target user;

[0108] A signal processing module 202, used to process the reflected signal to generate multi-frame point cloud information, wherein the point cloud information is used to determine the monitoring area;

[0109] The information determination module 203 is used to determine the sleep information of the target user according to the degree of change of the point cloud information in the monitoring area.

[0110] Optionally, the signal processing module 202 includes:

[0111] A processing submodule, configured to convert the reflected signal to generate a distance matrix, wherein the distance matrix includes a reflection distance and a Doppler velocity of the reflected signal;

[0112] The first generating submodule is used to generate point cloud information of a plurality of consecutive frames according to the reflection distance and the Doppler velocity.

[0113] Optionally, the signal processing module 202 further includes:

[0114] The second generation submodule is used to perform superposition processing on the point cloud information of multiple consecutive frames according to a preset time window to generate a point cloud data frame;

[0115] A clustering submodule, used for clustering all point cloud data frames within a first preset time period to obtain a plurality of cluster sets;

[0116] The area determination submodule is used to determine the monitoring area for monitoring the sleep of the target user according to the average Doppler velocity of the point cloud data frame in the clustering concentration.

[0117] Optionally, the information determination module 203 includes:

[0118] An acquisition submodule, used to acquire a degree of change in the number of points in the point cloud data frame in the monitoring area within a first preset time period;

[0119] A first recording submodule is used to confirm that the target user is stationary and record the target user's sleeping time if the degree of change of the number of points in the monitoring area is less than a first change threshold;

[0120] A second recording submodule is configured to confirm that the target user is not stationary and record the awake time of the target user if the degree of change of the number of points in the monitoring area is greater than a second change threshold;

[0121] The determination submodule is used to determine the sleep information of the target user according to the sleeping time and waking time of the target user.

[0122] Optionally, the device further comprises:

[0123] An information recording module, used to record the sleep information of the target user within a second preset time period, and determine the sleep health condition of the target user;

[0124] A sending prompt module is used to send the sleep health status to the target user.

[0125] The sleep monitoring device provided by the embodiment of the present invention monitors the target user through the millimeter wave radar, receives the reflected signal sent by the millimeter wave radar, processes the reflected signal, generates multiple frames of point cloud information, and determines the sleep information of the target user according to the degree of change of the point cloud information in the monitoring area. The embodiment of the present invention uses the millimeter wave radar device to collect the reflected signal at the location of the target user. The user does not need to wear any equipment, which is more comfortable to use. The millimeter wave radar has a low resolution, which is conducive to protecting the privacy of the user. Through the point cloud generation algorithm, the reflected signal collected by the millimeter wave radar is generated into point cloud information that accurately represents the user's status, thereby accurately identifying the user's sleep condition. The point cloud information can be used to dynamically monitor the user's status, thereby improving the accuracy of sleep time monitoring, accurately evaluating the user's sleep health, and further enhancing the user's experience.

[0126] The embodiment of the present invention further provides an electronic device, such as Figure 8As shown, it includes a processor 301, a communication interface 302, a memory 303 and a communication bus 304, wherein the processor 301, the communication interface 302, and the memory 303 communicate with each other through the communication bus 304.

[0127] Memory 303, used for storing computer programs;

[0128] The processor 301 is used to execute the program stored in the memory 303 to implement the following steps:

[0129] Receive the reflected signal sent by the millimeter wave radar monitoring target user;

[0130] Processing the reflected signal to generate multi-frame point cloud information, wherein the point cloud information is used to determine the monitoring area;

[0131] The sleep information of the target user is determined according to the degree of change of the point cloud information in the monitoring area.

[0132] The communication bus 304 mentioned in the above terminal can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus 304 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0133] The communication interface 302 is used for communication between the terminal and other devices.

[0134] The memory 303 may include a random access memory (RAM) or a non-volatile memory, such as at least one disk memory. Optionally, the memory 303 may also be at least one storage device located away from the aforementioned processor.

[0135] The above-mentioned processor 301 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components.

[0136] In another embodiment of the present invention, a computer-readable storage medium is provided. The computer-readable storage medium stores instructions. When the instructions are executed on a computer, the computer executes the sleep monitoring method described in any one of the above embodiments.

[0137] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented by software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes one or more available media integrated. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state hard disk SolidStateDisk (SSD)), etc.

[0138] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0139] Each embodiment in this specification is described in a related manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0140] The above description is only a preferred embodiment of the present invention and is not intended to limit the protection scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention are included in the protection scope of the present invention.

Claims

1. A sleep monitoring method, characterized in that: The method comprises: Receive the reflected signal sent by the millimeter wave radar monitoring target user; Processing the reflected signal to generate multi-frame point cloud information, wherein the point cloud information is used to determine the monitoring area; The sleep information of the target user is determined according to the degree of change of the point cloud information in the monitoring area.

2. The method according to claim 1, characterized in that The processing of the reflected signal to generate multi-frame point cloud information includes: Converting the reflected signal to generate a distance matrix, wherein the distance matrix includes the reflection distance and Doppler velocity of the reflected signal; Point cloud information of a plurality of consecutive frames is generated according to the reflection distance and the Doppler velocity.

3. The method according to claim 2, characterized in that After generating a plurality of continuous frames of point cloud information according to the reflection distance and the Doppler velocity, the method further includes: The point cloud information of multiple consecutive frames is superimposed according to a preset time window to generate a point cloud data frame; Clustering all point cloud data frames within a first preset time period to obtain a plurality of cluster sets; A monitoring area for monitoring the sleep of a target user is determined according to an average Doppler velocity of the point cloud data frames in the cluster.

4. The method according to claim 1, characterized in that: The determining the sleep information of the target user according to the degree of change of the point cloud information in the monitoring area includes: Obtaining a degree of change in the number of points in the point cloud data frame in the monitoring area within a first preset time period; If the degree of change of the number of points in the monitoring area is less than a first change threshold, it is confirmed that the target user is stationary, and the sleeping time of the target user is recorded; If the degree of change of the number of points in the monitoring area is greater than a second change threshold, it is confirmed that the target user is not stationary, and the awake time of the target user is recorded; The sleep information of the target user is determined according to the sleeping time and waking time of the target user.

5. The method according to claim 1, characterized in that After determining the sleep information of the target user according to the degree of change of the point cloud information in the monitoring area, the method further includes: Recording the sleep information of the target user within a second preset time period to determine the sleep health condition of the target user; The sleep health status is sent to the target user.

6. A sleep monitoring device, characterized in that: The device comprises: A signal receiving module is used to receive the reflected signal sent by the millimeter wave radar monitoring target user; A signal processing module, used to process the reflected signal to generate multi-frame point cloud information, wherein the point cloud information is used to determine the monitoring area; The information determination module is used to determine the sleep information of the target user according to the degree of change of the point cloud information in the monitoring area.

7. The device according to claim 6, characterized in that The signal processing module comprises: A processing submodule, configured to convert the reflected signal to generate a distance matrix, wherein the distance matrix includes a reflection distance and a Doppler velocity of the reflected signal; The first generating submodule is used to generate point cloud information of a plurality of consecutive frames according to the reflection distance and the Doppler velocity.

8. The device according to claim 6, characterized in that The signal processing module comprises: The second generation submodule is used to perform superposition processing on the point cloud information of multiple consecutive frames according to a preset time window to generate a point cloud data frame; A clustering submodule, used for clustering all point cloud data frames within a first preset time period to obtain a plurality of cluster sets; The area determination submodule is used to determine the monitoring area for monitoring the sleep of the target user according to the average Doppler velocity of the point cloud data frame in the clustering concentration.

9. An electronic device, characterized in that: The device comprises a processor and a memory: The memory is used to store computer programs; The processor is configured to execute the sleep monitoring method according to any one of claims 1 to 5 according to the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium is used to store a computer program, and the computer program is used to execute the sleep monitoring method according to any one of claims 1 to 5.

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