Microwave radar sleep monitoring method and device based on user charging time

Abstract

The invention relates to a microwave radar sleep monitoring method and device based on a user charging moment, and the method comprises the following steps: S0, transmitting and receiving a radar signal through a microwave radar when the connection between a terminal and a charger is detected, and calculating or speculating the moment when a user enters sleep; s1, at the moment when the user falls asleep, radar signals are transmitted and received through a microwave radar, and the position of a human body is searched; s2, controlling the microwave radar to rotate and / or translate, and searching a vital sign detection area; and S3, receiving a radar signal returned by the vital sign detection area, and extracting vital signs from the radar signal.

Description

Technical Field

[0001] The present invention relates to the field of microwave radar sleep detection, and in particular to a microwave radar sleep monitoring method and device based on user charging time. Background Art

[0002] Microwave radar can collect echo data of the detected person, and then extract the micro-movement changes of the human body from the echo data, thereby calculating the vital signs of the human body, such as breathing, heartbeat, etc.

[0003] The microwave radar used for vital sign detection is fixedly installed at a certain position in the room, such as the head of the bed, the wall, etc. On the one hand, the sleeping time of the human body is unknown, and the microwave radar cannot know when to start detecting the vital signs corresponding to the human body's sleep. On the other hand, since the vital signs of the human body are tiny changes in the human body's movements, such as the heartbeat corresponding to the tiny shaking of the human chest, the position of the human body in the radar scanning area is unknown, and the movement generated by the vital signs is very weak. Not all areas within the radar scanning range can extract micro-motion signals. Before performing vital sign detection, the direction and orientation of the microwave radar need to be manually adjusted to place the human body in an area with better signals within the radar scanning range. Only then can the subsequent vital sign detection algorithm capture the vital sign data from the echo data. In the prior art, it is impossible to realize that the microwave radar automatically finds the part of the human body that can feedback vital signs.

[0004] In view of the above problems existing in the prior art, the purpose of the present invention is to design a microwave radar sleep monitoring method and device based on the user's charging time. Summary of the invention

[0005] In view of the problems existing in the above-mentioned prior art, the present invention provides a microwave radar sleep monitoring method and device based on the user's charging time, which can effectively solve at least one problem existing in the above-mentioned prior art.

[0006] The technical solution of the present invention is:

[0007] A microwave radar sleep monitoring method based on user charging time includes the following steps:

[0008] S0, when it is detected that the terminal is connected to the charger, the microwave radar transmits and receives radar signals to calculate or infer the time when the user falls asleep;

[0009] S1, when the user falls asleep, transmitting and receiving radar signals through a microwave radar to find the position of the human body;

[0010] S2, controlling the microwave radar to rotate and / or translate to find a vital sign detection area;

[0011] S3, receiving the radar signal returned by the vital sign detection area, and extracting the vital sign from the radar signal.

[0012] Further, the calculating or estimating the user's sleep time includes:

[0013] Using a machine learning algorithm to train the user's historical data of charging time of the terminal, historical data of the user falling asleep, and historical data of the user's body movement value, to obtain a user's sleep habit model;

[0014] Obtaining the current charging time of the terminal by the user, and calculating the user's body movement value according to the radar signal;

[0015] The time when the user falls asleep is calculated according to the current charging time of the terminal by the user and the user's body movement value through the user's sleep habit model.

[0016] Furthermore, the body movement value is calculated according to the following steps:

[0017] After performing 2DFFT on the radar signal, the maximum value is found in the distance index range of 1-40, and the maximum value is stored in the body motion array of 10 frames of historical data. The body motion value is obtained by summing the body motion array.

[0018] Further, step S2 includes:

[0019] S21, determining whether the human body is in a micro-motion state, and if so, rotating and / or translating the microwave radar to an area facing the micro-motion state;

[0020] S22, calculating vital signs at multiple locations within the region of the micro-motion state;

[0021] S23, if the vital signs at multiple positions are similar, the area in the micro-motion state is determined to be a vital sign detection area; if the vital signs at multiple positions are different, the scanning range of the microwave radar is rotated and / or translated and the process returns to step S21.

[0022] Furthermore, before step S21, execute:

[0023] S20, record and update the radar signal in real time, and enter step S21 when the number of point clouds of the radar signal is less than the preset number threshold, and use the human body position when the number of point clouds of the radar signal is less than the preset number threshold as the micro-motion position.

[0024] Further, step S22 includes:

[0025] The region in the micro-motion state is divided into a plurality of sub-regions at equal intervals, and the vital signs of the plurality of sub-regions are calculated.

[0026] Further, dividing the region in the micro-motion state into a plurality of sub-regions at equal intervals, and calculating the vital signs of the plurality of sub-regions comprises:

[0027] The radar signal in the area of ​​the micro-motion state is equally divided and the phases are calculated respectively;

[0028] Multiple phases are calculated through a vital sign algorithm to obtain multiple vital signs.

[0029] Further, if the vital signs of multiple positions are different, the scanning range of the microwave radar is rotated and / or translated according to the vital signs of multiple sub-areas and the process returns to step S21.

[0030] Further, rotating and / or translating the microwave radar according to the vital signs of the plurality of sub-areas comprises:

[0031] Calculate the mean of vital signs of multiple sub-areas;

[0032] The microwave radar is rotated and / or translated toward the sub-region where the vital sign is close to the vital sign mean value.

[0033] A microwave radar sleep monitoring device based on the user's charging time is further provided, including a base, a microwave radar, and a charging device, wherein the charging device is one or more of a wired charging device or a wireless charging device, the charging device is arranged on the base, the microwave radar is rotatable, and the sleep monitoring device executes the microwave radar sleep monitoring method based on the user's charging time when working.

[0034] Therefore, the present invention provides the following effects and / or advantages:

[0035] The present application can calculate the time when the user falls asleep based on the time when the terminal establishes a connection with the charger, and start to enable the microwave radar to capture human body signals and calculate the user's vital signs from the time when the user falls asleep.

[0036] The present application can control the rotation and / or translation of the microwave radar to direct the center of its scanning area toward the vital signs detection area by finding the vital signs detection area, and utilize the characteristics of the center of the scanning area having the best signal-to-noise ratio and the best response of human vital signs, thereby improving the detection accuracy of the microwave radar in detecting human vital signs.

[0037] The present application can control the microwave radar to rotate and / or translate to find the vital signs detection area, so that the microwave radar used to detect vital signs can be placed in multiple locations indoors, and there is no need to manually adjust the scanning area of ​​the microwave radar before use. The microwave radar can automatically find the vital signs detection area and perform vital signs detection.

[0038] The present application calculates vital signs at multiple positions within the area of ​​the micro-motion state, and through the vital signs at multiple positions, it is possible to determine whether the scanning center of the microwave radar is facing the part of the human body that reacts to vital signs. This can be used to accurately adjust the scanning range of the microwave radar, thereby improving the accuracy of vital signs detection.

[0039] The present application divides the area of ​​the micro-motion state into multiple sub-areas at equal intervals, which can be applicable to the characteristics of human vital signs in the microwave radar detection process, thereby improving the detection accuracy.

[0040] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description and the drawings.

[0041] It is to be understood that both the foregoing general description and the following detailed description of the present invention are exemplary and explanatory and are intended to provide further explanation of the invention as claimed. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 A schematic diagram of a flow chart provided for an embodiment of the present invention.

[0043] Figure 2 Schematic diagram of the logic for calculating vital signs for microwave radar.

[0044] Figure 3 Schematic diagram of finding the human body position for microwave radar.

[0045] Figure 4 Schematic diagram of finding the micromotion area for microwave radar, where the shaded area represents the micromotion area.

[0046] Figure 5 This is a schematic diagram showing that the center of the scanning area of ​​the microwave radar is located at the center of the micro-motion area after rotation.

[0047] Figure 6 It is a schematic diagram of dividing the micro-motion state area into 2*2 square areas when measuring heart rate.

[0048] Figure 7 This is a schematic diagram of dividing the micro-motion state area into four square areas arranged from top to bottom when measuring the respiratory frequency.

[0049] Figure 8 A schematic diagram of adjusting the scanning area of ​​a microwave radar according to breathing frequency.

[0050] Fig. 9 Schematic diagram of the steps for calculating vital signs.

[0051] Fig.10 A schematic diagram of the device structure. DETAILED DESCRIPTION

[0052] In order to facilitate understanding by those skilled in the art, the structure of the present invention is further described in detail with reference to the embodiments in conjunction with the accompanying drawings:

[0053] refer to Figure 1-2 , a microwave radar sleep monitoring method based on user charging time, characterized in that it includes the following steps:

[0054] S0, when it is detected that the terminal is connected to the charger, the microwave radar transmits and receives radar signals to calculate or infer the time when the user falls asleep;

[0055] In this step, when the user puts down the phone to charge, it can be detected that the terminal has established a connection with the charger. At the same time, in order to improve the accuracy of the detection, in this step, the charging power of the user's phone and the handshake signal during charging can be matched to determine that the phone is the phone corresponding to the permanent user in the room, and the current time can also be obtained. If the current time is close to the time when the user usually falls asleep, the microwave radar transmits and receives radar signals to calculate or infer the time when the user falls asleep.

[0056] By calculating or inferring the time when the user falls asleep, the microwave radar can be accurately controlled to perform subsequent algorithms such as searching for the human body and calculating vital signs at that time, thereby preventing the microwave radar from starting to monitor the user's sleep when the user is not asleep, such as lying in bed using electronic devices, etc., thereby preventing erroneous data from being obtained.

[0057] S1, when the user falls asleep, transmitting and receiving radar signals through a microwave radar to find the position of the human body;

[0058] In this embodiment, a radar signal is transmitted by a microwave radar and a radar signal returned by a human body in the room is received. The microwave radar can be placed in the room, for example, on a bedside table, a wall, a wardrobe, etc., without limitation. The microwave radar can scan multiple positions in the room. At this time, the position of the radar or the position of the human body is unknown. The method of searching for a human body by a microwave radar is an existing technology. For example, when the human body is in a sitting or lying state, the human body does not walk or make large body movements, and the preliminary position of the human body is obtained according to the characteristics of the echo data on the microwave radar in this state.

[0059] In this step, the microwave radar can rotate or translate to search for a human body in the room.

[0060] This step is as follows Figure 3 shown.

[0061] S2, controlling the microwave radar to rotate and / or translate to find a vital sign detection area;

[0062] In step S1, the microwave radar finds the position of the human body, and it is necessary to further find the vital sign detection area. This step can be based on the situation that the human body is in a resting state such as sitting or lying down, the human body does not move in a large range, the human body's breathing will produce a small ups and downs, the human body's heartbeat will produce a small shake, etc., and according to the performance of this situation in the radar echo data, the vital sign detection area can be found.

[0063] Because the signal-to-noise ratio of each area within the scanning range of the microwave radar is different, and the position of the human body is unknown before step S1, if the microwave radar does not look for the vital signs detection area but directly extracts vital signs through the microwave radar data returned by the human body's breathing or heartbeat, its data will be affected by external interference and different radar signal-to-noise ratios, and the calculated vital signs data will have problems such as insufficient accuracy. Therefore, this step searches for the vital signs detection area.

[0064] S3, receiving the radar signal returned by the vital sign detection area, and extracting the vital sign from the radar signal.

[0065] In step S2, the human vital sign detection area is found. At this time, only the radar signal of the vital sign detection area is extracted to calculate the vital sign, which can greatly improve the accuracy of the vital sign calculation result. The method of vital sign detection can refer to the existing application with publication number CN118452869A and the name of the method, device, equipment and medium for monitoring vital signs based on millimeter wave radar.

[0066] Alternatively, first construct the ADC data collected by each frame of microwave radar within a period of time as a matrix to be processed, and use the covariance matrix decomposition method to remove the clutter that is significantly different from the useful signal; then use the wavelet denoising method to remove the non-stationary noise, so as to reconstruct the original ADC data. Then, by referring to Fig. 9 The provided calculation process realizes vital signs analysis.

[0067] Further, in step S1, searching for the human body position includes:

[0068] Identify the human body and obtain its position through point cloud data.

[0069] In this step, the microwave radar is used to collect ADC data, perform one-dimensional FFT calculation, two-dimensional FFT calculation, select the target position, and then map the horizontal angle and pitch angle between the human body and the microwave radar and the target to the direct coordinate system, so that the human body can be identified, and the microwave radar is rotated or translated through the horizontal angle and pitch angle between the human body and the microwave radar, so that the human body is located in the middle of the microwave radar scanning area.

[0070] When the human body is in a resting state, the point cloud data corresponding to the reflected radar signal is relatively small. By utilizing the amount of point cloud data in this state, it can be determined that there is a human body at that position when the point cloud data is less than a preset point cloud data amount threshold.

[0071] Further, step S2 includes:

[0072] S21, determining whether the human body is in a micro-motion state, and if so, rotating and / or translating the microwave radar to an area facing the micro-motion state;

[0073] In this step, the radar signal can be calculated by the micro-motion algorithm to determine whether the human body is in a micro-motion state. The parts of the human body that are in a micro-motion state are generally the chest and abdomen, etc. This area is used to identify the best area for vital sign detection. The micro-motion algorithm can be used to extract the parts of the micro-motion state, such as Figure 4 As shown, in step S1, the microwave radar finds the position of the human body. At this time, the microwave radar can be rotated or translated to face the human body. In this step, by extracting the micro-motion area, the microwave radar can be rotated or translated to face the center of the scanning area toward the chest, abdomen and other parts of the human body, as shown in FIG. Figure 5 shown.

[0074] Since the accuracy of the micro-motion algorithm is average, in this step, when the microwave radar rotates or translates toward the micro-motion area, the chest or abdomen of the human body may not be in the optimal scanning area of ​​the microwave radar.

[0075] S22, calculating vital signs at multiple locations within the region of the micro-motion state;

[0076] In this step, the heartbeat is used as an example to illustrate that the human chest cavity produces a slight tremor under the action of the heartbeat, thereby producing an area in a micro-motion state.

[0077] Theoretically, the frequencies corresponding to the tiny vibrations generated by the human heartbeat at various locations on the chest should be the same. Correspondingly, the heartbeat data calculated from the radar signal reflected back by the tiny vibrations generated by the heartbeat should be the same at multiple locations within the micro-motion state area. Vital signs are calculated at multiple locations within the micro-motion state area obtained in step S21, so as to be used in subsequent steps to determine whether the best signal-to-noise ratio scanning area of ​​the microwave radar is directly corresponding to the human chest.

[0078] S23, if the vital signs at multiple positions are similar, the area in the micro-motion state is determined to be a vital sign detection area; if the vital signs at multiple positions are different, the scanning range of the microwave radar is rotated and / or translated and the process returns to step S21.

[0079] If the vital signs calculated at multiple locations are the same or similar, it means that the best detection area of ​​the microwave radar is right for the micro-movement of vital signs such as the chest or abdomen of the human body. The best detection area of ​​the microwave radar can be considered to be the center of the radar detection area.

[0080] Due to different sleeping postures of the human body, the radar signal of the micro-motion area captured by the microwave radar may be too weak, interfered, or have calculation errors, or the micro-motion signal may be too weak to be captured when it is transmitted from the center of the chest or abdomen to the edge of the human body, resulting in different vital signs calculated at multiple locations. Therefore, this step needs to be performed.

[0081] Preferably, for the heart rate in the vital signs, since the heart is located near the center of the chest cavity, the region of the micro-motion state can be divided into N*N squares, for example, into a 2*2 field-shaped structure, such as Figure 6 As shown, heartbeat detection is performed in each square area in the area. If the heart is located in the exact center of N*N squares, the micro-movements generated by the heartbeat in each square area will be captured by the microwave radar and the heart rate will be calculated to be very close.

[0082] At the same time, when measuring the heart rate, since the chest cavity where the heart is located is located above the human body, in order to facilitate capturing the heart rate, in this step, the area of ​​the micro-motion state close to the human head can first be divided into N*N squares and then the vital signs can be calculated.

[0083] Preferably, for the respiratory rate in the vital signs, since the abdomen of the human body will float up and down during breathing, at this time, the area of ​​the micro-motion state can be divided into N rectangles arranged up and down, for example, 4 rectangles are divided, such as Figure 7 As shown, in this area, the breathing frequency is detected in each rectangular area. If the center of the abdomen is located at the center of N rectangles, the micro-movements generated by the ups and downs of the abdomen in each rectangular area are captured by the microwave radar and the breathing frequency is calculated to be very close.

[0084] At the same time, when measuring the respiratory rate, since the abdomen is located in the middle of the human body, in order to facilitate capturing the respiratory rate, in this step, the area of ​​the micro-motion state close to the human legs can be first divided into N rectangles and then the vital signs can be calculated.

[0085] The legs or head of the human body can be identified using existing technologies.

[0086] Therefore, through this step, it is found whether the center of the scanning range of the microwave radar is located at the center of the human body part from which the vital signs data can be extracted. At this time, the radar data obtained by the microwave radar can correctly reflect the vital signs of the human body. If the vital signs of multiple positions are different, the microwave radar can be rotated or moved to make the scanning area of ​​the microwave radar translate or rotate, thereby changing the center point of the scanning area of ​​the microwave radar.

[0087] Furthermore, before step S21, execute:

[0088] S20, record and update the radar signal in real time, and enter step S21 when the number of point clouds of the radar signal is less than the preset number threshold, and use the human body position when the number of point clouds of the radar signal is less than the preset number threshold as the micro-motion position.

[0089] In this embodiment, if the human body is stationary, the number of point clouds of the radar signal will become very small. By presetting a quantity threshold, it can be determined that the human body is in a stationary state when the number is reduced to below the preset quantity threshold.

[0090] Further, step S22 includes:

[0091] The region in the micro-motion state is divided into a plurality of sub-regions at equal intervals, and the vital signs of the plurality of sub-regions are calculated.

[0092] Further, dividing the region in the micro-motion state into a plurality of sub-regions at equal intervals, and calculating the vital signs of the plurality of sub-regions comprises:

[0093] The radar signal in the area of ​​the micro-motion state is equally divided and the phases are calculated respectively;

[0094] Multiple phases are calculated through a vital sign algorithm to obtain multiple vital signs.

[0095] In this step, you can refer to Figure 7 Or 8, thereby dividing the area of ​​the micro-motion state into equal intervals.

[0096] Specifically, the phase data of the micro-motion area can be extracted first, and the phase data can be phase unwrapped to generate unwrapped data; then the unwrapped data can be preprocessed, and the preprocessed unwrapped data can be subjected to FFT operation to generate heart rate data and track the heart rate data. For details, reference can be made to the existing application entitled "Method, device, equipment and medium for monitoring vital signs based on millimeter wave radar" with publication number CN118452869A.

[0097] Further, if the vital signs of multiple positions are different, the scanning range of the microwave radar is rotated and / or translated according to the vital signs of multiple sub-areas and the process returns to step S21.

[0098] Further, rotating and / or translating the microwave radar according to the vital signs of the plurality of sub-areas comprises:

[0099] Calculate the mean of vital signs of multiple sub-areas;

[0100] The microwave radar is rotated and / or translated toward the sub-region where the vital sign is close to the vital sign mean value.

[0101] In this step, if Figure 8 As shown, assuming that the respiratory rates from multiple positions on the abdomen calculated in the above steps are 15, 20, 21, and 20 (times / minute), respectively, the calculated average is 19, and the sub-areas with respiratory rates of 20, 21, and 20 are areas where vital signs are close to the mean of the vital signs. At this time, the scanning range of the microwave radar needs to be adjusted downward.

[0102] Furthermore, the following steps are performed to determine whether the vital signs at multiple locations are similar:

[0103] The standard deviation of the vital signs at the multiple locations is calculated. If the standard deviation is less than a preset standard deviation threshold, the vital signs at the multiple locations are similar.

[0104] Further, the calculating or estimating the user's sleep time includes:

[0105] Using a machine learning algorithm to train the user's historical data of charging time of the terminal, historical data of the user falling asleep, and historical data of the user's body movement value, to obtain a user's sleep habit model;

[0106] Obtaining the current charging time of the terminal by the user, and calculating the user's body movement value according to the radar signal;

[0107] The time when the user falls asleep is calculated according to the current charging time of the terminal by the user and the user's body movement value through the user's sleep habit model.

[0108] In this embodiment, the machine learning algorithm can be trained based on the input and output data to find the association between the input and output data. It is understandable that by training the user's historical data of the terminal's charging time, the user's historical data of falling asleep, and the user's historical data of body movement values, an accurate model for calculating or inferring the user's sleeping habits can be obtained, which can accurately calculate the user's sleeping time based on various current situations.

[0109] The user's body motion value can be considered as the value calculated by the signal reflected by the microwave radar when the user turns over in bed, moves his limbs, etc.

[0110] The time when the user charges the terminal may be the time when the user starts charging.

[0111] During sleep, the microwave radar can detect that the user's body movement value is low, and / or the user's heart rate is at a resting heart rate, and / or the user's breathing and heart rate are relatively stable, thereby determining that the user has fallen asleep.

[0112] Through the above-mentioned user sleep habit model, the time when the user falls asleep can be accurately calculated according to the charging time of the terminal and the user's body movement value, so as to control the microwave radar to start searching for the human body and calculating vital signs at that time.

[0113] In addition, in the process of training with machine learning algorithms, the number of times the user has charged since the start of charging can be added, and training can be performed together with the historical data of the user's charging time of the terminal, the historical data of the user falling asleep, and the historical data of the user's body movement values. The number of historical charging times indicates the number of times the user did not fall asleep and picked up the phone to charge it again after using it for a period of time. This can reflect the difficulty of the user putting down the phone and falling asleep. The more difficult it is for the user to fall asleep, the more times he or she will charge.

[0114] Furthermore, the body movement value is calculated according to the following steps:

[0115] After performing 2DFFT on the radar signal, the maximum value is found in the distance index range of 1-40, and the maximum value is stored in the body motion array of 10 frames of historical data. The body motion value is obtained by summing the body motion array.

[0116] In this embodiment, a body movement value greater than 200 can be determined as poor sleep quality of the user.

[0117] Further provide a microwave radar sleep monitoring device based on the user charging time, reference Fig.10 , including a base 1, a microwave radar 2, and a charging device 3. The charging device 3 is one or more of a wired charging device or a wireless charging device. The charging device 3 is arranged on the base 1. The microwave radar 2 can be rotatably arranged. When the sleep monitoring device is working, it executes the microwave radar sleep monitoring method based on the user's charging time.

[0118] It should be noted that in the claims, any reference signs placed between brackets shall not be construed as limiting the claims. The word "comprising" does not exclude the presence of components or steps not listed in the claim. The word "a" or "an" preceding a component does not exclude the presence of a plurality of such components. The invention may be implemented by means of hardware comprising several different components and by means of a suitably programmed computer. In a unit claim enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third etc. does not indicate any order. These words may be interpreted as names.

[0119] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0120] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0121] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms should not be understood as necessarily referring to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are contradictory.

Claims

1. A microwave radar sleep monitoring method based on user charging time, characterized in that: The following steps are involved: S0, when it is detected that the terminal is connected to the charger, the microwave radar transmits and receives radar signals to calculate or infer the time when the user falls asleep; S1, when the user falls asleep, transmitting and receiving radar signals through a microwave radar to find the position of the human body; S2, controlling the microwave radar to rotate and / or translate to find a vital sign detection area; S3, receiving the radar signal returned by the vital sign detection area, and extracting the vital sign from the radar signal.

2. The microwave radar sleep monitoring method based on user charging time according to claim 1, characterized in that: The calculating or estimating the user's sleep time includes: Using a machine learning algorithm to train the user's historical data of charging time of the terminal, historical data of the user falling asleep, and historical data of the user's body movement value, to obtain a user's sleep habit model; Obtaining the current charging time of the terminal by the user, and calculating the user's body movement value according to the radar signal; The time when the user falls asleep is calculated according to the current charging time of the terminal by the user and the user's body movement value through the user's sleep habit model.

3. The microwave radar sleep monitoring method based on user charging time according to claim 2, characterized in that: The body movement value is calculated according to the following steps: After performing 2DFFT on the radar signal, the maximum value is found in the distance index range of 1-40, and the maximum value is stored in the body motion array of 10 frames of historical data. The body motion value is obtained by summing the body motion array.

4. The microwave radar sleep monitoring method based on user charging time according to claim 1, characterized in that: Step S2 includes: S21, determining whether the human body is in a micro-motion state, and if so, rotating and / or translating the microwave radar to an area facing the micro-motion state; S22, calculating vital signs at multiple locations within the region of the micro-motion state; S23, if the vital signs at multiple positions are similar, the area in the micro-motion state is determined to be a vital sign detection area; if the vital signs at multiple positions are different, the scanning range of the microwave radar is rotated and / or translated and the process returns to step S21.

5. The microwave radar sleep monitoring method based on user charging time according to claim 4, characterized in that: Before step S21, execute: S20, record and update the radar signal in real time, and enter step S21 when the number of point clouds of the radar signal is less than the preset number threshold, and use the human body position when the number of point clouds of the radar signal is less than the preset number threshold as the micro-motion position.

6. The microwave radar sleep monitoring method based on user charging time according to claim 4, characterized in that: Step S22 includes: The region in the micro-motion state is divided into a plurality of sub-regions at equal intervals, and the vital signs of the plurality of sub-regions are calculated.

7. The microwave radar sleep monitoring method based on user charging time according to claim 4, characterized in that: Dividing the micro-motion state region into a plurality of sub-regions at equal intervals, and calculating the vital signs of the plurality of sub-regions comprises: The radar signal in the area of ​​the micro-motion state is equally divided and the phases are calculated respectively; Multiple phases are calculated through a vital sign algorithm to obtain multiple vital signs.

8. The microwave radar sleep monitoring method based on user charging time according to claim 6, characterized in that: If the vital signs at multiple locations are different, the scanning range of the microwave radar is rotated and / or translated according to the vital signs of the multiple sub-areas and the process returns to step S21.

9. The microwave radar sleep monitoring method based on user charging time according to claim 8, characterized in that: Rotating and / or translating the microwave radar according to the vital signs of the plurality of sub-areas comprises: Calculate the mean of vital signs of multiple sub-areas; The microwave radar is rotated and / or translated toward the sub-region where the vital sign is close to the vital sign mean value.

10. A microwave radar sleep monitoring device based on the user's charging time, characterized in that: It includes a base, a microwave radar, and a charging device, wherein the charging device is one or more of a wired charging device or a wireless charging device, the charging device is arranged on the base, the microwave radar is rotatable, and the sleep monitoring device executes a microwave radar sleep monitoring method based on the user charging time as described in any one of claims 1-9 when working.

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