CN113208581A - Human body posture detection device, method and system - Google Patents
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Abstract
The embodiment of the invention provides a human body posture detection device, a method and a system, wherein the device comprises: a first calculation unit which calculates multi-antenna distance FFT data at a plurality of moments of a static scene according to microwave reflection signals from a space where a human body is located; the second calculation unit is used for determining the position of the human body according to the multi-antenna distance FFT data at multiple moments of a static scene; the third calculation unit is used for calculating the angle frequency points belonging to the human body according to the multi-antenna distance FFT data at multiple moments of a static scene and the position of the human body; and a first determination unit that determines the posture of the human body based on the heights of the angular frequency points belonging to the human body.
Description
Technical Field
The invention relates to the technical field of information.
Background
With the aging becoming more and more serious, the health care demand of the old people is increasing, and the method has important significance in providing effective health monitoring service for the old people. The falling is an important factor threatening the health and life safety of the old. According to the statistics of the world health organization, the serious fall injury needing to be treated occurs at 3730 thousands of times per year; the proportion of elderly people over 65 years old is the greatest among fatal injuries. The detection technology for the human body postures such as falling is beneficial to rapidly finding accidents such as falling, and the rescue is timely improved to prevent the aggravation of injury. The falling detection technology plays an important role in industries such as nursing for the aged and the like, and the nursing quality and efficiency are improved.
The falling detection technology based on the microwave radar has the advantage of strong privacy, can be applied to private places such as bedrooms and toilets, and has good market prospect. The existing fall detection technology based on microwave radar judges whether a fall occurs by analyzing the motion characteristics of a human body and utilizing methods such as machine learning or template matching and the like.
It should be noted that the above background description is only for the sake of clarity and complete description of the technical solutions of the present invention and for the understanding of those skilled in the art. Such solutions are not considered to be known to the person skilled in the art merely because they have been set forth in the background section of the invention.
Disclosure of Invention
The inventors have found that there are many limitations and disadvantages with existing microwave radar based fall detection techniques. First, a fall is a transient action, and the whole process is short, generally only a few seconds. Therefore, the data related to the fall action that can be captured by the radar is small, and the fall detection accuracy is greatly affected. Secondly, falls can be caused by a variety of reasons, such as slipping, tripping, physiological factors, etc., and there are many unpredictable factors during a fall, such as whether there is support cushioning, etc. These factors lead to differences in the movement characteristics of fall actions, which are difficult to detect for all types of fall actions. In addition, the problem that data samples are difficult to obtain exists in the process of fall detection by using a machine learning correlation algorithm, and the problems of weak generalization capability and low detection precision exist.
In order to solve at least one of the above problems, embodiments of the present invention provide a human body posture detection device, method, and system, which are not limited by a fall type, and have high detection accuracy, good robustness, and a wide application range.
According to a first aspect of embodiments of the present invention, there is provided a human body posture detecting apparatus, the apparatus including: a first calculation unit which calculates multi-antenna distance FFT data at a plurality of moments of a static scene according to microwave reflection signals from a space where a human body is located; the second calculation unit is used for determining the position of the human body according to the multi-antenna distance FFT data at multiple moments of a static scene; the third calculation unit is used for calculating the angle frequency points belonging to the human body according to the multi-antenna distance FFT data at multiple moments of a static scene and the position of the human body; and a first determination unit that determines the posture of the human body based on the heights of the angular frequency points belonging to the human body.
According to a second aspect of embodiments of the present invention, there is provided an electronic device comprising the apparatus according to the first aspect of embodiments of the present invention.
According to a third aspect of embodiments of the present invention, there is provided a human body posture detection system including: the microwave radar is provided with a signal transmitting part and a signal receiving part, wherein the signal transmitting part transmits microwave signals to a space where a human body is located, and the signal receiving part receives microwave reflection signals; and the human body posture detection device according to the first aspect of the embodiment of the invention detects the human body posture according to the microwave reflection signal.
According to a fourth aspect of the embodiments of the present invention, there is provided a human body posture detection method, including: calculating multi-antenna distance FFT data at a plurality of moments of a static scene according to microwave reflection signals from a space where a human body is located; determining the position of the human body according to the multi-antenna distance FFT data at multiple moments of a static scene; calculating angle frequency points belonging to the human body according to the multi-antenna distance FFT data at multiple moments of a static scene and the position of the human body; and determining the posture of the human body according to the height of the angle frequency point belonging to the human body.
The invention has the beneficial effects that: and determining the position of the human body according to the FFT data of the multi-antenna distance at a plurality of moments in a static scene, thereby determining the posture of the human body according to the height of the angle frequency point belonging to the human body. In this way, since the detection data in the stationary scene having a longer duration than the fall motion is used, the amount of the usable data is large, and the detection accuracy is high, and since the detection is performed based on the detection data in the stationary scene, the detection is not affected by the specific type of the fall, and the robustness is good and the application range is wide.
Specific embodiments of the present invention are disclosed in detail with reference to the following description and drawings, indicating the manner in which the principles of the invention may be employed. It should be understood that the embodiments of the invention are not so limited in scope. The embodiments of the invention include many variations, modifications and equivalents within the spirit and scope of the appended claims.
Features that are described and/or illustrated with respect to one embodiment may be used in the same way or in a similar way in one or more other embodiments, in combination with or instead of the features of the other embodiments.
It should be emphasized that the term "comprises/comprising" when used herein, is taken to specify the presence of stated features, integers, steps or components but does not preclude the presence or addition of one or more other features, integers, steps or components.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention. It is obvious that the drawings in the following description are only some embodiments of the invention, and that for a person skilled in the art, other drawings can be derived from them without inventive effort. In the drawings:
fig. 1 is a schematic view of a human body posture detecting apparatus according to embodiment 1 of the present invention;
fig. 2 is a schematic diagram of the second determination unit 105 according to embodiment 1 of the present invention;
FIG. 3 is a diagram of the second calculating unit 102 according to embodiment 1 of the present invention;
fig. 4 is another schematic diagram of the second calculation unit 102 according to embodiment 1 of the present invention;
FIG. 5 is a diagram of the third calculating unit 103 according to embodiment 1 of the present invention;
fig. 6 is a schematic view of an electronic device according to embodiment 2 of the present invention;
fig. 7 is a schematic block diagram of a system configuration of an electronic apparatus according to embodiment 2 of the present invention;
fig. 8 is a schematic diagram of a human body posture detecting system according to embodiment 3 of the present invention;
fig. 9 is a schematic diagram of a human body posture detection method according to embodiment 4 of the present invention.
Detailed Description
The foregoing and other features of the invention will become apparent from the following description taken in conjunction with the accompanying drawings. In the description and drawings, particular embodiments of the invention have been disclosed in detail as being indicative of some of the embodiments in which the principles of the invention may be employed, it being understood that the invention is not limited to the embodiments described, but, on the contrary, is intended to cover all modifications, variations, and equivalents falling within the scope of the appended claims.
Example 1
Fig. 1 is a schematic view of a human body posture detection device according to embodiment 1 of the present invention. As shown in fig. 1, the human body posture detecting apparatus 100 includes:
a first calculation unit 101 that calculates multi-antenna distance FFT data at a plurality of times in a stationary scene from a microwave reflection signal from a space in which a human body is present;
a second calculating unit 102, which determines the position of the human body according to the multi-antenna distance FFT data at multiple moments in a static scene;
a third calculating unit 103, which calculates an angle frequency point belonging to the human body according to the multiple-antenna distance FFT data at multiple times in a static scene and the position of the human body; and
and a first determination unit 104 for determining the posture of the human body according to the height of the angular frequency point belonging to the human body.
In this way, since the detection data in the stationary scene having a longer duration than the fall motion is used, the amount of the usable data is large, and the detection accuracy is high, and since the detection is performed based on the detection data in the stationary scene, the detection is not affected by the specific type of the fall, and the robustness is good and the application range is wide.
In the present embodiment, the human body posture detecting apparatus 100 can be used for detecting various human body postures, such as "lying on the ground", "standing", "sitting", and "lying on a bed or a sofa", where "lying on the ground" can be generally regarded as an action of falling of the human body.
For example, when detecting the posture of a human body as a detection target, a microwave radar periodically transmits a microwave signal to a space where the human body is located, and a part of the microwave signal is reflected by the human body and other objects to generate a microwave reflection signal, and a point at which the microwave signal is reflected is referred to as a reflection point.
In this embodiment, the microwave radar has a plurality of antennas that respectively receive microwave reflection signals at different distances. The number of the antennas of the microwave radar can be determined according to actual needs.
In the present embodiment, a "stationary scene" refers to a state in which a human body as a detection object is stationary.
The human body posture detection apparatus 100 may further include:
and a second determination unit 105 which determines the time at which the scene is still based on the microwave reflection signal from the space in which the human body is located.
The second determination unit 105 performs determination one by one for each time, which may employ various determination methods. The structure of the second determination unit 105 and the method of determining a still scene are exemplarily described below.
Fig. 2 is a schematic diagram of the second determining unit 105 according to embodiment 1 of the present invention. As shown in fig. 2, the second determination unit 105 includes:
a fourth calculating unit 201 that calculates a doppler velocity of each reflection point at a time based on a microwave reflection signal from a space where a human body is present at the time; and
a third determination unit 202, which determines that the time is in a static scene when the number of reflection points at which the doppler velocity at the time is greater than the first threshold is less than the second threshold.
Therefore, the Doppler velocity of the reflection point is used for judgment, the processing process is simple, and the precision is high.
In the present embodiment, the fourth calculation unit 202 may use an existing method for calculating the doppler velocity of each reflection point from the microwave reflection signal.
For example, a one-dimensional fourier transform is performed on the microwave reflection signal, and a distance-fourier transform graph, i.e., distance FFT data, of the microwave reflection signal can be obtained. The abscissa of the graph is the distance between the human body and the microwave radar, and the ordinate is the amplitude of the one-dimensional fourier transform, the square of which is the energy of the reflection point. In addition, the microwave reflected signal is subjected to two-dimensional fourier transform, and a doppler-fourier transform graph of the microwave reflected signal can be obtained, in which the abscissa of the graph is the moving speed of the human body and the ordinate is the amplitude of the two-dimensional fourier transform. Then, according to the distance-fourier transform graph and the doppler-fourier transform graph of the microwave reflection signal, a distance-doppler spectrogram of the microwave reflection signal can be obtained, wherein the abscissa is the distance between the human body and the microwave radar, and the ordinate is the doppler velocity of the human body.
In this embodiment, the third determination unit 20 determines that the time is in a static scene when the number of reflection points at which the doppler velocity at the time is greater than the first threshold is less than the second threshold. The specific values of the first threshold and the second threshold can be set according to actual needs.
In the case where the second determining unit 105 determines that a time is a time in a static scene, the multiple antenna distance FFT data of the time is added to the data list, and in the case where the second determining unit 105 determines that a time is not a time in a static scene, the data list is emptied.
That is, when a plurality of time instants in a static scene are continuously detected, multi-antenna distance FFT data of the plurality of time instants are recorded in the data list. And once a certain time instant is determined not to be a static scene, the multi-antenna distance FFT data of a plurality of time instants recorded before are emptied.
The first calculating unit 101 obtains multi-antenna distance FFT data at a plurality of time instants of a static scene, for example, performs one-dimensional fourier transform on a microwave reflection signal to obtain a distance-fourier transform graph of the microwave reflection signal, i.e., distance FFT data, and the distance FFT data of a plurality of antennas are collected to obtain the multi-antenna distance FFT data.
For example, at time t in a stationary scene, the multi-antenna distance FFT data may be represented by the following equation (1):
wherein R istA matrix representing FFT data of multiple antenna distances at time t, m is the number of antennas, n is the number of distance frequency points, row wi(Rt) The distance FFT value of the ith antenna on each distance frequency point is shown, and the jth column colj(Rt) And (3) the distance FFT value of each antenna on the jth distance frequency point is shown.
In the present embodiment, assuming that each time within the time of (0, T) is determined as a still scene, the multi-antenna distance FFT data recorded in the data list can be expressed as:
R＝(R0,R1,…,RT) (2)
where R represents the multi-antenna distance FFT data at each time instant within the time of (0, T).
In this embodiment, the second calculating unit 102 determines the position of the human body according to the FFT data of multiple antenna distances at multiple times of a static scene.
The structure of the second calculation unit 102 and the method of determining the position of the human body are exemplarily described below.
Fig. 3 is a schematic diagram of the second calculating unit 102 according to embodiment 1 of the present invention. As shown in fig. 3, the second calculation unit 102 includes:
a fifth calculating unit 301, configured to calculate a first amplitude standard deviation of each distance frequency point of the antenna according to the distance FFT data of one antenna in the multi-antenna distance FFT data;
a sixth calculating unit 302, configured to calculate, when the maximum value of the first amplitude standard deviation is greater than a third threshold, angle FFT data of distance frequency points at multiple times in a static scene according to distance FFT data of the distance frequency points having the maximum value of the first amplitude standard deviation in the multi-antenna distance FFT data;
a seventh calculating unit 303, configured to calculate a second amplitude standard deviation of each angle frequency point according to the angle FFT data of the distance frequency point at multiple times in the static scene; and
an eighth calculating unit 304, which determines the position of the human body according to the distance corresponding to the distance frequency point having the maximum value of the first amplitude standard deviation and the horizontal angle and the vertical angle corresponding to the angle frequency point having the maximum value of the second amplitude standard deviation.
Therefore, the position of the human body and the distance between the human body and the microwave radar are determined according to the distance FFT data of one antenna, and the horizontal angle and the vertical angle of the position of the human body relative to the microwave radar are determined according to the data corresponding to the distance in the multi-antenna distance FFT data, so that the calculation amount is small, and the processing speed is high.
In this embodiment, the fifth calculating unit 301 calculates, according to distance FFT data of one antenna in the multi-antenna distance FFT data, a first amplitude standard deviation of each distance frequency point of the antenna, where the one antenna may be any one of multiple antennas, and various methods may be used to calculate the amplitude standard deviation of each distance frequency point, for example, the following formula (3) may be used to calculate:
wherein, ci,jIndicating the standard deviation of the distance FFT magnitude at the jth distance bin for the ith antenna,
is a plurality of the number of the optical fibers,
the magnitude of the complex number is represented as,
is the average of the magnitude of the distance FFT.
When the maximum value of all the first amplitude standard deviations of each distance frequency point of the antenna is greater than the third threshold, the sixth calculating unit 302 calculates angle FFT data of the distance frequency point at multiple moments in a static scene according to the distance FFT data of the distance frequency point having the maximum value of the first amplitude standard deviation in the multi-antenna distance FFT data.
For example, when the maximum value of all the first amplitude standard deviations of the distance frequency points of the antenna is greater than the third threshold, the maximum value of the first amplitude standard deviation corresponds to a distance frequency point d, and the distance represented by the distance frequency point d is the distance from the human body to the microwave radar. Multi-antenna distance FFT data R in time of (0, T)tIn the method, the multi-antenna FFT data at each time has a column of distance FFT data col corresponding to the distance frequency point dd(Rt) Col according to the antenna distribution of microwave radard(Rt) The phases of the elements are recombined into a matrix, and an angle FFT operation is performed. In the time of (0, T), the angle FFT data at all the moments on the distance frequency point d can be used
Denotes, wherein, the angle at time tThe degree FFT data can be expressed as:
wherein the content of the first and second substances,
the FFT data of the angle at the time t is shown, p and q respectively show the maximum frequency point number of the horizontal angle and the vertical angle,
and the FFT data of the angle on the kth horizontal angle frequency point and the ith vertical angle frequency point are obtained.
In addition, when the maximum value of all the first amplitude standard deviations of each distance frequency point of the antenna is smaller than or equal to a third threshold value, determining that no human body exists.
The seventh calculating unit 303 calculates the second amplitude standard deviation of each angle frequency point according to the angle FFT data of the distance frequency point at a plurality of moments in the static scene, and may adopt various calculation methods, for example, may calculate according to the following formula (5):
wherein the content of the first and second substances,
represents the standard deviation of the FFT amplitude values of the angle at the k horizontal angle frequency point and the l vertical angle frequency point on the distance frequency point d in the time of (0, T),
the result of the angle FFT of the kth horizontal angle frequency point and the l vertical angle frequency point on the distance frequency point d at the time t,
which is indicative of the magnitude thereof,
the average value of the angle FFT amplitudes of the kth horizontal angle frequency point and the l th vertical angle frequency point on the distance frequency point d is obtained.
The eighth calculating unit 304 determines the position of the human body according to the distance corresponding to the distance frequency point having the maximum value of the first amplitude standard deviation and the horizontal angle and the vertical angle corresponding to the angle frequency point having the maximum value of the second amplitude standard deviation.
For example, the distance frequency point having the maximum value of the first amplitude standard deviation is d, and the horizontal angle and the vertical angle corresponding to the angle frequency point having the maximum value of the second amplitude standard deviation are h and v, respectively, so that the position of the human body can be represented by a three-dimensional coordinate (d, h, v), where d is the distance between the position of the human body and the microwave radar, h is the horizontal angle of the position of the human body relative to the microwave radar, and v is the vertical angle of the position of the human body relative to the microwave radar.
Fig. 4 is another schematic diagram of the second calculating unit 102 according to embodiment 1 of the present invention. As shown in fig. 4, the second calculation unit 102 includes:
a ninth calculating unit 401 that calculates angle FFT data at each time of each distance frequency point based on the multi-antenna distance FFT data;
a tenth calculating unit 402, configured to calculate a third amplitude standard deviation of each angular frequency point of each distance frequency point according to the angular FFT data at each time of each distance frequency point; and
an eleventh calculating unit 403, configured to determine the position of the human body according to the horizontal angle and the vertical angle corresponding to the angle frequency point having the maximum value of the third amplitude standard deviation and the corresponding distance when the maximum value of the third amplitude standard deviation is greater than the fourth threshold.
Therefore, the position of the human body is determined according to the angle FFT data of each distance frequency point at each moment, and the precision is high.
The ninth calculating unit 401 calculates angle FFT data at each time of each distance bin according to the multi-antenna distance FFT data, and the specific calculation method may refer to the above formula (4).
The tenth calculating unit 402 calculates the third amplitude standard deviation of each angular frequency point of each distance frequency point according to the angular FFT data of each time of each distance frequency point, and the calculating method may refer to the above formula (5).
An eleventh calculating unit 403, configured to determine the position of the human body according to the horizontal angle and the vertical angle corresponding to the angle frequency point having the maximum value of the third amplitude standard deviation and the corresponding distance when the maximum value of the third amplitude standard deviation is greater than the fourth threshold.
For example, the horizontal angle and the vertical angle corresponding to the angle frequency point having the maximum value of the third amplitude standard deviation are h and v, respectively, and the corresponding distance is d, then, the position of the human body may be represented by a three-dimensional coordinate (d, h, v), d is the distance between the position of the human body and the microwave radar, h is the horizontal angle of the position of the human body relative to the microwave radar, and v is the vertical angle of the position of the human body relative to the microwave radar.
In addition, when the maximum value of the third amplitude standard deviation is less than or equal to the fourth threshold, it is determined that no human body exists.
In this embodiment, specific values of the third threshold and the fourth threshold may be determined according to actual needs.
After the second calculating unit 102 determines the position of the human body, the third calculating unit 103 calculates the angular frequency point belonging to the human body according to the multi-antenna distance FFT data at multiple times in the static scene and the position of the human body.
The following exemplarily describes the structure and the calculation method of the third calculation unit 103.
Fig. 5 is a schematic diagram of the third calculating unit 103 according to embodiment 1 of the present invention. As shown in fig. 5, the third calculation unit 103 includes:
a twelfth calculating unit 501, configured to calculate a distance frequency point where the human body is located and a fourth amplitude standard deviation of each angle frequency point on the distance frequency point within a predetermined range around the distance frequency point; and
a thirteenth calculating unit 502, which determines the angle frequency point, in which the fourth amplitude standard deviation is greater than the fifth threshold, the distance of the horizontal angle frequency point corresponding to the position of the human body is less than the sixth threshold, and the distance of the vertical angle frequency point corresponding to the position of the human body is less than the seventh threshold, as the angle frequency point belonging to the human body.
In this embodiment, the twelfth calculating unit 501 calculates a distance frequency point where the human body is located and a fourth amplitude standard deviation of each angle frequency point on the distance frequency point in a predetermined range around the distance frequency point, where the distance frequency point where the human body is located is a distance frequency point corresponding to the position where the human body is located determined by the second calculating unit 102, for example, d in the position (d, h, v) where the human body is located, and the distance frequency point d may be regarded as a center position of the human body.
In the present embodiment, the first amplitude standard deviation, the second amplitude standard deviation, the third amplitude standard deviation and the fourth amplitude standard deviation all represent standard deviations of amplitudes, and are distinguished in different description manners.
In this embodiment, the distance frequency points within the predetermined range around the distance frequency point may be regarded as other distance frequency points corresponding to the whole area where the human body is located. The predetermined range may be determined according to the resolution of the microwave radar.
The thirteenth calculating unit 502 determines the angle frequency point, in which the fourth amplitude standard deviation is greater than the fifth threshold, the distance of the horizontal angle frequency point corresponding to the position of the human body is less than the sixth threshold, and the distance of the vertical angle frequency point corresponding to the position of the human body is less than the seventh threshold, as the angle frequency point belonging to the human body. The specific values of the fifth threshold, the sixth threshold and the seventh threshold can be determined according to actual needs.
In this embodiment, after the third calculation unit 103 calculates the angular frequency point belonging to the human body, the first determination unit 104 determines the posture of the human body according to the height of the angular frequency point belonging to the human body.
For example, the height of the angular frequency point belonging to the human body can be obtained by calculating the vertical angular frequency point, for example, the height of the angular frequency point is calculated according to the following formulas (6) and (7):
wherein z represents the height of the angle frequency point, l represents the vertical angle frequency point corresponding to the angle frequency point, and q represents the number of frequency points with the maximum vertical angle FFT amplitude.
In this embodiment, the first determining unit 104 may determine the posture of the human body according to a ratio of the number of angle frequency points with a height smaller than a preset threshold among the angle frequency points belonging to the human body to the total number of angle frequency points belonging to the human body.
For example, when the ratio of the number of angle frequency points with a height smaller than the eighth threshold among the angle frequency points belonging to the human body to the total number of angle frequency points belonging to the human body is greater than the ninth threshold, it is determined that the posture of the human body is "lying on the ground", that is, the human body has a falling action, and when the ratio is smaller than or equal to the ninth threshold, it is determined that the posture of the human body is not "lying on the ground", that is, the human body has no falling action.
In this embodiment, specific values of the eighth threshold and the ninth threshold may be determined according to actual needs.
For another example, the first determining unit 104 may determine the posture of the human body according to a plurality of ratios between the number of the angle frequency points with the heights respectively smaller than the plurality of thresholds among the angle frequency points belonging to the human body and the total number of the angle frequency points belonging to the human body.
For example, a plurality of threshold values with different heights may be set, so that which one of the postures of the human body is "lying on the ground", "lying on a bed or on a sofa", "standing" and "sitting" can be determined according to a plurality of ratios of the number of the plurality of angle frequency points with the heights respectively smaller than the plurality of threshold values among the angle frequency points of the human body to the total number of the angle frequency points belonging to the human body.
According to the embodiment, the position of the human body is determined according to the multi-antenna distance FFT data at multiple moments in a static scene, so that the posture of the human body is determined according to the height of the angle frequency point belonging to the human body. In this way, since the detection data in the stationary scene having a longer duration than the fall motion is used, the amount of the usable data is large, and the detection accuracy is high, and since the detection is performed based on the detection data in the stationary scene, the detection is not affected by the specific type of the fall, and the robustness is good and the application range is wide.
Example 2
An embodiment of the present invention further provides an electronic device, and fig. 6 is a schematic diagram of the electronic device in embodiment 2 of the present invention. As shown in fig. 6, the electronic device 600 includes a human body posture detecting apparatus 601, wherein the structure and function of the human body posture detecting apparatus 601 are the same as those described in embodiment 1, and are not described herein again.
Fig. 7 is a schematic block diagram of a system configuration of an electronic apparatus according to embodiment 2 of the present invention. As shown in fig. 7, the electronic device 700 may include a processor 701 and a memory 702; a memory 702 is coupled to the processor 701. The figure is exemplary; other types of structures may also be used in addition to or in place of the structure to implement telecommunications or other functions.
As shown in fig. 7, the electronic device 700 may further include: an input unit 703, a display 704, and a power source 705.
For example, the functions of the human body posture detection apparatus described in embodiment 1 may be integrated into the processor 701. The processor 701 may be configured to: calculating multi-antenna distance FFT data at a plurality of moments of a static scene according to microwave reflection signals from a space where a human body is located; determining the position of the human body according to the multi-antenna distance FFT data at a plurality of moments in a static scene; calculating angle frequency points belonging to the human body according to the multi-antenna distance FFT data at multiple moments of a static scene and the position of the human body; and determining the posture of the human body according to the height of the angle frequency point belonging to the human body.
For example, the processor 701 may be further configured to: and determining the moment of the static scene according to the microwave reflection signal from the space where the human body is located.
For example, determining the time of the static scene according to the microwave reflection signal from the space where the human body is located includes: calculating the Doppler velocity of each reflection point at a moment according to the microwave reflection signal from the space where the human body is located at the moment; and determining that the moment is in a static scene under the condition that the number of the reflection points of which the Doppler velocity is greater than the first threshold value at the moment is less than a second threshold value.
For example, determining the position of the human body according to the FFT data of multiple antennas at multiple times of the static scene includes: calculating a first amplitude standard deviation of each distance frequency point of the antenna according to the distance FFT data of one antenna in the multi-antenna distance FFT data; when the maximum value of the first amplitude standard deviation is larger than a third threshold value, calculating angle FFT data of the distance frequency point at multiple moments in a static scene according to the distance FFT data of the distance frequency point with the maximum value of the first amplitude standard deviation in the multi-antenna distance FFT data; calculating a second amplitude standard deviation of each angle frequency point according to the angle FFT data of the distance frequency point at a plurality of moments in a static scene; and determining the position of the human body according to the distance corresponding to the distance frequency point with the maximum value of the first amplitude standard deviation and the horizontal angle and the vertical angle corresponding to the angle frequency point with the maximum value of the second amplitude standard deviation.
For example, determining the position of the human body according to the FFT data of multiple antennas at multiple times of the static scene includes: calculating angle FFT data of each distance frequency point at each moment according to the multi-antenna distance FFT data; calculating a third amplitude standard deviation of each angle frequency point of each distance frequency point according to the angle FFT data of each time of each distance frequency point; and when the maximum value of the third amplitude standard deviation is larger than a fourth threshold value, determining the position of the human body according to the horizontal angle and the vertical angle corresponding to the angle frequency point with the maximum value of the third amplitude standard deviation and the corresponding distance.
For example, calculating the angle frequency points belonging to the human body according to the multi-antenna distance FFT data at multiple moments in a static scene and the position of the human body includes: calculating the distance frequency point of the human body and the fourth amplitude standard deviation of each angle frequency point on the distance frequency point in the preset range around the distance frequency point; and determining the angle frequency points of which the fourth amplitude standard deviation is greater than a fifth threshold, the distance of the horizontal angle frequency point corresponding to the position of the human body is less than a sixth threshold, and the distance of the vertical angle frequency point corresponding to the position of the human body is less than a seventh threshold as the angle frequency points belonging to the human body.
For example, determining the posture of the human body according to the heights of the angular frequency points belonging to the human body includes: and determining the posture of the human body according to the ratio of the number of the angle frequency points with the height smaller than a preset threshold value in the angle frequency points belonging to the human body to the total number of the angle frequency points belonging to the human body.
For example, when the ratio of the number of angle frequency points with a height smaller than the eighth threshold among the angle frequency points belonging to the human body to the total number of angle frequency points belonging to the human body is larger than the ninth threshold, it is determined that the human body is lying on the ground.
For example, determining the posture of the human body according to the ratio of the number of the angle frequency points with the height smaller than the preset threshold value among the angle frequency points belonging to the human body to the total number of the angle frequency points belonging to the human body includes: and determining the posture of the human body according to a plurality of ratios of the number of the angle frequency points with the heights respectively smaller than a plurality of threshold values in the angle frequency points belonging to the human body to the total number of the angle frequency points belonging to the human body.
For another example, the human body posture detection device described in embodiment 1 may be disposed separately from the processor 701, and for example, the human body posture detection device may be a chip connected to the processor 701, and the function of the human body posture detection device may be realized by the control of the processor 701.
It is not necessary that the electronic device 700 in this embodiment include all of the components shown in fig. 7.
As shown in fig. 7, the processor 701, which is sometimes referred to as a controller or operational control, may include a microprocessor or other processor device and/or logic device, and the processor 701 receives input and controls the operation of the various components of the electronic device 700.
The memory 702, for example, may be one or more of a buffer, a flash memory, a hard drive, a removable media, a volatile memory, a non-volatile memory, or other suitable device. And the processor 701 may execute the program stored in the memory 702 to realize information storage or processing, or the like. The functions of other parts are similar to the prior art and are not described in detail here. The various components of electronic device 700 may be implemented in dedicated hardware, firmware, software, or combinations thereof, without departing from the scope of the invention.
According to the embodiment, the position of the human body is determined according to the multi-antenna distance FFT data at multiple moments in a static scene, so that the posture of the human body is determined according to the height of the angle frequency point belonging to the human body. In this way, since the detection data in the stationary scene having a longer duration than the fall motion is used, the amount of the usable data is large, and the detection accuracy is high, and since the detection is performed based on the detection data in the stationary scene, the detection is not affected by the specific type of the fall, and the robustness is good and the application range is wide.
Example 3
The embodiment of the invention also provides a human body posture detection system, which comprises a microwave radar and a human body posture detection device, wherein the structure and the function of the human body posture detection device are the same as those recorded in the embodiment 1, and the specific content is not repeated.
Fig. 8 is a schematic diagram of a human body posture detection system according to embodiment 3 of the present invention, and as shown in fig. 8, a human body posture detection system 800 includes:
a microwave radar 810 including a signal transmitting unit 811 and a signal receiving unit 812, the signal transmitting unit 811 transmitting a microwave signal to a space where a human body is located, and the signal receiving unit 812 receiving a microwave reflected signal; and
and a human body posture detection device 820 for detecting the posture of the human body based on the microwave reflection signal.
For example, microwave radar 810 is a multi-antenna microwave radar. The specific structure and function of the signal transmitting section 811 and the signal receiving section 812 of the microwave radar 810 can refer to the related art.
In this embodiment, the structure and function of the human body posture detection device 820 are the same as those described in embodiment 1, and detailed description thereof will not be repeated.
According to the embodiment, the position of the human body is determined according to the multi-antenna distance FFT data at multiple moments in a static scene, so that the posture of the human body is determined according to the height of the angle frequency point belonging to the human body. In this way, since the detection data in the stationary scene having a longer duration than the fall motion is used, the amount of the usable data is large, and the detection accuracy is high, and since the detection is performed based on the detection data in the stationary scene, the detection is not affected by the specific type of the fall, and the robustness is good and the application range is wide.
Example 4
The embodiment of the invention also provides a human body posture detection method, which corresponds to the human body posture detection device in the embodiment 1. Fig. 9 is a schematic diagram of a human body posture detection method according to embodiment 4 of the present invention. As shown in fig. 9, the method includes:
step 901: calculating multi-antenna distance FFT data at a plurality of moments of a static scene according to microwave reflection signals from a space where a human body is located;
step 902: determining the position of the human body according to the multi-antenna distance FFT data at a plurality of moments in a static scene;
step 903: calculating angle frequency points belonging to the human body according to the multi-antenna distance FFT data at multiple moments of a static scene and the position of the human body; and
step 904: and determining the posture of the human body according to the height of the angle frequency point belonging to the human body.
In this embodiment, the specific implementation method in each step is the same as that described in embodiment 1, and is not described herein again.
According to the embodiment, the position of the human body is determined according to the multi-antenna distance FFT data at multiple moments in a static scene, so that the posture of the human body is determined according to the height of the angle frequency point belonging to the human body. In this way, since the detection data in the stationary scene having a longer duration than the fall motion is used, the amount of the usable data is large, and the detection accuracy is high, and since the detection is performed based on the detection data in the stationary scene, the detection is not affected by the specific type of the fall, and the robustness is good and the application range is wide.
Embodiments of the present invention also provide a computer-readable program, where when the program is executed in a human body posture detection apparatus or an electronic device, the program causes a computer to execute the human body posture detection method described in embodiment 4 in the human body posture detection apparatus or the electronic device.
An embodiment of the present invention further provides a storage medium storing a computer-readable program, where the computer-readable program enables a computer to execute the human body posture detection method described in embodiment 4 in a human body posture detection apparatus or an electronic device.
The method for detecting human body gestures performed in the human body gesture detection apparatus or the electronic device described in connection with the embodiments of the present invention may be directly embodied as hardware, a software module executed by a processor, or a combination of the two. For example, one or more of the functional block diagrams and/or one or more combinations of the functional block diagrams illustrated in fig. 1 may correspond to individual software modules of a computer program flow or may correspond to individual hardware modules. These software modules may correspond to the steps shown in fig. 9, respectively. These hardware modules may be implemented, for example, by solidifying these software modules using a Field Programmable Gate Array (FPGA).
A software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. A storage medium may be coupled to the processor such that the processor can read information from, and write information to, the storage medium; or the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC. The software module may be stored in the memory of the mobile terminal or in a memory card that is insertable into the mobile terminal. For example, if the apparatus (e.g., mobile terminal) employs a relatively large capacity MEGA-SIM card or a large capacity flash memory device, the software module may be stored in the MEGA-SIM card or the large capacity flash memory device.
One or more of the functional block diagrams and/or one or more combinations of the functional block diagrams described with respect to fig. 1 may be implemented as a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any suitable combination thereof designed to perform the functions described herein. One or more of the functional block diagrams and/or one or more combinations of the functional block diagrams described with respect to fig. 1 may also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP communication, or any other such configuration.
While the invention has been described with reference to specific embodiments, it will be apparent to those skilled in the art that these descriptions are illustrative and not intended to limit the scope of the invention. Various modifications and alterations of this invention will become apparent to those skilled in the art based upon the spirit and principles of this invention, and such modifications and alterations are also within the scope of this invention.
The embodiment of the invention also discloses the following attached notes:
1. a human pose detection method, the method comprising:
calculating multi-antenna distance FFT data at a plurality of moments of a static scene according to microwave reflection signals from a space where a human body is located;
determining the position of the human body according to the multi-antenna distance FFT data at multiple moments of a static scene;
calculating angle frequency points belonging to the human body according to the multi-antenna distance FFT data at multiple moments of a static scene and the position of the human body; and
and determining the posture of the human body according to the height of the angle frequency point belonging to the human body.
2. The method according to supplementary note 1, wherein the method further comprises:
and determining the moment of the static scene according to the microwave reflection signal from the space where the human body is located.
3. The method according to supplementary note 2, wherein the determining the time of the static scene according to the microwave reflection signal from the space where the human body is located comprises:
calculating the Doppler velocity of each reflection point at a moment according to a microwave reflection signal from the space where the human body is located at the moment; and
and determining that the moment is in a static scene under the condition that the number of the reflection points of which the Doppler velocity is greater than the first threshold value at the moment is less than a second threshold value.
4. The method according to supplementary note 1, wherein the determining the position of the human body according to the FFT data of the multiple antenna distances at multiple times in the static scene includes:
calculating a first amplitude standard deviation of each distance frequency point of the antenna according to the distance FFT data of one antenna in the multi-antenna distance FFT data;
when the maximum value of the first amplitude standard deviation is larger than a third threshold value, calculating angle FFT data of the distance frequency points at multiple moments in a static scene according to distance FFT data of the distance frequency points with the maximum value of the first amplitude standard deviation in the multi-antenna distance FFT data;
calculating a second amplitude standard deviation of each angle frequency point according to the angle FFT data of the distance frequency points at a plurality of moments in a static scene; and
and determining the position of the human body according to the distance corresponding to the distance frequency point with the maximum value of the first amplitude standard deviation and the horizontal angle and the vertical angle corresponding to the angle frequency point with the maximum value of the second amplitude standard deviation.
5. The method according to supplementary note 1, wherein the determining the position of the human body according to the FFT data of the multiple antenna distances at multiple times in the static scene includes:
calculating angle FFT data of each distance frequency point at each moment according to the multi-antenna distance FFT data;
calculating a third amplitude standard deviation of each angle frequency point of each distance frequency point according to the angle FFT data of each time of each distance frequency point; and
and when the maximum value of the third amplitude standard deviation is larger than a fourth threshold value, determining the position of the human body according to the horizontal angle and the vertical angle corresponding to the angle frequency point with the maximum value of the third amplitude standard deviation and the corresponding distance.
6. The method according to supplementary note 1, wherein the calculating of the angle frequency points belonging to the human body according to the multi-antenna distance FFT data at a plurality of moments in a static scene and the position of the human body comprises:
calculating the distance frequency point where the human body is located and the fourth amplitude standard deviation of each angle frequency point on the distance frequency point in the preset range around the distance frequency point;
and determining the angle frequency points of which the fourth amplitude standard deviation is greater than a fifth threshold, the distance of the horizontal angle frequency point corresponding to the position of the human body is less than a sixth threshold, and the distance of the vertical angle frequency point corresponding to the position of the human body is less than a seventh threshold as the angle frequency points belonging to the human body.
7. The method according to supplementary note 1, wherein the determining the posture of the human body according to the heights of the angular frequency points belonging to the human body comprises:
and determining the posture of the human body according to the ratio of the number of the angle frequency points with the height smaller than a preset threshold value in the angle frequency points belonging to the human body to the total number of the angle frequency points belonging to the human body.
8. The method according to supplementary note 7, wherein,
and when the ratio of the number of the angle frequency points with the height smaller than the eighth threshold value in the angle frequency points belonging to the human body to the total number of the angle frequency points belonging to the human body is larger than a ninth threshold value, determining that the posture of the human body lies on the ground.
9. The method according to supplementary note 7, wherein the determining the posture of the human body according to the ratio of the number of the angle frequency points with the height smaller than a preset threshold value among the angle frequency points belonging to the human body to the total number of the angle frequency points belonging to the human body comprises:
and determining the posture of the human body according to a plurality of ratios of the number of the angle frequency points with the heights respectively smaller than a plurality of threshold values in the angle frequency points belonging to the human body to the total number of the angle frequency points belonging to the human body.
Claims (10)
1. A human posture detection apparatus, the apparatus comprising:
a first calculation unit which calculates multi-antenna distance FFT data at a plurality of moments of a static scene according to microwave reflection signals from a space where a human body is located;
the second calculation unit is used for determining the position of the human body according to the multi-antenna distance FFT data at multiple moments of a static scene;
the third calculation unit is used for calculating the angle frequency points belonging to the human body according to the multi-antenna distance FFT data at multiple moments of a static scene and the position of the human body; and
and a first determination unit which determines the posture of the human body according to the height of the angle frequency point belonging to the human body.
2. The apparatus of claim 1, wherein the apparatus further comprises:
and a second determination unit which determines the time of the static scene according to the microwave reflection signal from the space where the human body is located.
3. The apparatus of claim 2, wherein the second determining unit comprises:
a fourth calculation unit that calculates a doppler velocity of each reflection point at a time based on a microwave reflection signal from a space in which a human body is present at the time; and
and a third determination unit that determines that the time point is in a static scene when the number of reflection points at which the doppler velocity at the time point is greater than the first threshold value is less than the second threshold value.
4. The apparatus of claim 1, wherein the second computing unit comprises:
a fifth calculating unit, configured to calculate a first amplitude standard deviation of each distance frequency point of the antennas according to distance FFT data of one antenna in the multi-antenna distance FFT data;
a sixth calculating unit, configured to calculate, when the maximum value of the first amplitude standard deviation is greater than a third threshold, angle FFT data of distance frequency points at multiple times in a static scene according to distance FFT data of the distance frequency points having the maximum value of the first amplitude standard deviation in the multi-antenna distance FFT data;
a seventh calculating unit, configured to calculate a second amplitude standard deviation of each angle frequency point according to the angle FFT data of the distance frequency points at multiple times in a static scene; and
and the eighth calculating unit is used for determining the position of the human body according to the distance corresponding to the distance frequency point with the maximum value of the first amplitude standard deviation and the horizontal angle and the vertical angle corresponding to the angle frequency point with the maximum value of the second amplitude standard deviation.
5. The apparatus of claim 1, wherein the second computing unit comprises:
a ninth calculating unit that calculates angle FFT data at each time of each distance frequency point based on the multi-antenna distance FFT data;
a tenth calculating unit, configured to calculate a third amplitude standard deviation of each angle frequency point of each distance frequency point according to the angle FFT data at each time of each distance frequency point; and
and the eleventh calculating unit is used for determining the position of the human body according to the horizontal angle and the vertical angle corresponding to the angle frequency point with the maximum value of the third amplitude standard deviation and the corresponding distance when the maximum value of the third amplitude standard deviation is larger than a fourth threshold value.
6. The apparatus of claim 1, wherein the third computing unit comprises:
a twelfth calculating unit, configured to calculate a fourth amplitude standard deviation of the distance frequency point where the human body is located and each angle frequency point on the distance frequency point within a predetermined range around the distance frequency point; and
and the thirteenth calculating unit is used for determining the angle frequency point of which the fourth amplitude standard deviation is larger than a fifth threshold, the distance of the horizontal angle frequency point corresponding to the position of the human body is smaller than a sixth threshold, and the distance of the vertical angle frequency point corresponding to the position of the human body is smaller than a seventh threshold as the angle frequency point belonging to the human body.
7. The apparatus of claim 1, wherein,
the first determining unit determines the posture of the human body according to the ratio of the number of the angle frequency points which belong to the human body and have the height smaller than a preset threshold value to the total number of the angle frequency points which belong to the human body.
8. The apparatus of claim 7, wherein,
the first determination unit determines that the posture of the human body is lying on the ground when the ratio of the number of the angle frequency points with the height smaller than the eighth threshold among the angle frequency points belonging to the human body to the total number of the angle frequency points belonging to the human body is larger than a ninth threshold.
9. The apparatus of claim 7, wherein,
the first determining unit determines the posture of the human body according to a plurality of ratios of the number of the angle frequency points with the heights respectively smaller than a plurality of threshold values in the angle frequency points belonging to the human body to the total number of the angle frequency points belonging to the human body.
10. An electronic device comprising the apparatus of claim 1.
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