CN114176564B - Method for extracting respiratory state based on radar signal - Google Patents
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Abstract
The invention discloses a method for extracting respiratory state based on radar signals, which comprises the following steps: 1) The radar detection module transmits a modulated continuous wave, performs one-dimensional fast Fourier transform on the received modulated continuous wave in a plurality of periods, and calculates the frequency shift of the transmitted wave; 2) When the frequency shift of the emission wave is offset, the influence of environmental noise is removed, and a real motion signal of the chest is extracted; 3) Judging whether the test target is in a normal breathing state, a body movement state or an unmanned state of the human body according to the extracted waveform signals; 4) When the human body is judged to be in a normal breathing state, a breathing value is calculated according to the waveform characteristics of the breathing signals, and whether the phenomenon of apnea occurs in the sleeping process is judged. The method is characterized in that the respiration signals of the tested person are collected, the measurement is carried out without direct contact with the human body, the operation is simple and convenient, and the human body can move freely.
Description
Technical Field
The invention relates to the technical field of breath detection, in particular to a method for extracting a breath state based on radar signals.
Background
The respiratory state in the sleeping process is related to the health of a human body, and the respiratory state in the sleeping process can cause airway obstruction, unsmooth mouth-nose airflow, long-term breathing and occurrence of the phenomena of the respiratory pause or snoring and the like are not timely cured, and serious harm and death can be caused to the human body, so that the respiratory state in the sleeping process is monitored very important.
The current common methods for breathing state in the sleeping process mainly comprise a polysomnography, a wrist activity recorder, a sleeping mattress and the like. The polysomnography method needs to measure a plurality of physiological signals such as an electroencephalogram, an electrocardiogram, blood oxygen saturation, an oculogram and the like at the same time in a professional instrument of a professional hospital, electrodes are easy to fall off in the testing process, the process is complex, the personal freedom of a tested person is limited, a professional doctor is required to conduct data analysis, the cost is high, and the application range is limited. The wrist activity recorder needs to be worn on the limb, and although the body movement during sleep can be measured, the breathing state cannot be distinguished. The sleeping mattress measures the breathing signals in the sleeping process through the pressure sensor, but the sleeping condition of the tested person can be influenced because the tested person needs to sleep on the mattress, and the sleeping breathing result is influenced.
Disclosure of Invention
The invention aims to provide a method for extracting respiratory state based on radar signals, which can conveniently monitor and extract respiratory state of a human body, judge respiratory state of a tested person, improve monitoring of apnea phenomenon in sleeping process and facilitate the tested person to know sleeping condition and health state of the tested person.
To achieve the above object, the present invention provides a method for extracting a respiration state based on a radar signal, the method comprising the steps of: 1) The radar detection module transmits a modulated continuous wave, performs one-dimensional fast Fourier transform on the received modulated continuous wave in a plurality of periods, and calculates the frequency shift of the transmitted wave; 2) When the frequency shift of the emission wave is offset, the influence of environmental noise is removed, and a real motion signal of the chest is extracted;
3) Judging whether the test target is in a normal breathing state, a body movement state or an unmanned state of the human body according to the extracted waveform signals; 4) When the human body is judged to be in a normal breathing state, a breathing value is calculated according to the waveform characteristics of the breathing signals, and whether the phenomenon of apnea occurs in the sleeping process is judged.
Preferably, in step 2), the waveform subjected to the FFT is removed by a background removal method to eliminate the noise influence caused by the external environment in the chest and abdomen respiration state of the non-contact measurement subject.
Preferably, the method for removing the background is as follows: the current frame signal and the previous frame signal are adopted to reconstruct the signal waveform in different proportions to serve as a background frame, and the background frame is subtracted from the current frame to eliminate the influence of the external environment on the signal.
Preferably, when the test target is in calm and regular breathing, the random noise influence is used for extracting the real motion signal of the chest through a position correction method.
Preferably, the method for correcting the position is as follows: the position of the maximum signal amplitude of the current frame is stored, and the position information stored for a certain time is referred to, so that the correction of the extracted waveform position is performed.
Preferably, in step 3), the signal zero-crossing rate, the signal ratio, the signal energy, the signal amplitude and the waveform characteristics of the extracted waveform signal are comprehensively determined to distinguish whether the test target is in a human normal breathing state, a body movement state or an unmanned state.
Preferably, the respiration waveform characteristic and the signal amplitude are combined with the waveform conditions of the sleep state, the body movement state and the signal at the same time to judge whether the phenomenon of apnea occurs in the sleep process.
Preferably, in step 4), classification of the type of apnea is performed according to waveform characteristics, the type of apnea including: hypopnea status, central apneas status, obstructive apneas status, and mixed apneas status.
Preferably, in step 5), when it is determined that an apnea phenomenon occurs during sleep, an early warning is performed by an early warning device.
Preferably, the method further comprises: and sending the real-time breathing state information to the monitoring terminal through a network or Bluetooth and displaying the real-time breathing state information.
According to the technical scheme, the method for extracting the respiratory state based on the radar signal can conveniently monitor and extract the respiratory state of a human body, judge the respiratory state of a tested person, improve the monitoring of the phenomenon of apnea in the sleeping process, and facilitate the tested person to know the sleeping condition and the health state of the tested person in a non-contact mode.
Additional features and advantages of the invention will be set forth in the detailed description which follows.
Drawings
The accompanying drawings are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate the invention and together with the description serve to explain, without limitation, the invention. In the drawings:
FIG. 1 is a respiratory signal extracted according to the method of the present invention;
figure 2 is an apnea signal extracted according to the method of the present invention;
figure 3 is an apnea event, apnea time and apnea type signal obtained using energy spectroscopy during a certain sleep.
Detailed Description
The following describes specific embodiments of the present invention in detail with reference to the drawings. It should be understood that the detailed description and specific examples, while indicating and illustrating the invention, are not intended to limit the invention.
In the present invention, unless otherwise indicated, terms such as "upper, lower, left, right, front, rear, and inner and outer" and the like are used merely to denote the orientation of the term in a conventional use state or are commonly understood by those skilled in the art, and should not be construed as limiting the term.
The invention provides a method for extracting respiratory state based on radar signals, which comprises the following steps: 1) The radar detection module transmits a modulated continuous wave, performs one-dimensional fast Fourier transform on the received modulated continuous wave in a plurality of periods, and calculates the frequency shift of the transmitted wave; 2) When the frequency shift of the emission wave is offset, the influence of environmental noise is removed, and a real motion signal of the chest is extracted; 3) Judging whether the test target is in a normal breathing state, a body movement state or an unmanned state of the human body according to the extracted waveform signals; 4) When the human body is judged to be in a normal breathing state, a breathing value is calculated according to the waveform characteristics of the breathing signals, and whether the phenomenon of apnea occurs in the sleeping process is judged.
Through implementation of the technical scheme, the method for extracting the respiratory state based on the radar signals can conveniently monitor and extract the respiratory state of a human body, judge the respiratory state of a tested person, improve monitoring of an apnea phenomenon in a sleeping process, facilitate the tested person to know the sleeping condition and the health state of the tested person in a non-contact mode, and is simple in testing operation, accurate in non-contact measurement and timely in analysis result. The method and the device aim at the extracted waveform signals to distinguish the state of the test target, such as the normal breathing state, the body movement state or the unmanned state of the human body, and distinguish whether the measurement condition exists the human body or not, so that unnecessary operation can be avoided, the code operation speed can be improved, and the problems of misanalysis of the breathing state under the unmanned condition and the condition of considering the unmanned state under the unmanned condition are solved.
In this embodiment, in order to further provide a means for extracting an accurate signal, in step 2), the waveform subjected to the FFT is subjected to a background removal method to eliminate the influence of noise caused by the external environment in the chest and abdomen respiration state of the non-contact measurement subject.
Further, the background removing method comprises the following steps: the current frame signal and the previous frame signal are adopted to reconstruct the signal waveform in different proportions to serve as a background frame, and the background frame is subtracted from the current frame to eliminate the influence of the external environment on the signal. Specifically, the background removing method combines the current frame waveform and the waveform of the previous frame into background frame data according to a certain proportion, and then subtracts the background frame data waveform from the current frame waveform to obtain a waveform with the background removed, so that the influence caused by noise is avoided.
In this embodiment, when the test target is in calm and regular breathing, the random noise influence is corrected by the position, and the real motion signal of the chest is extracted. For the chest echo signal of the measurement target, a series of processing is carried out to obtain a signal processed by one-dimensional FFT, and the signal is accumulated for a certain time to extract waveforms at corresponding positions. In the extraction process, in order to avoid interference of occasional signal fluctuations, correction processing is performed on the extraction target position.
Further, the position correction method comprises the following steps: the position of the maximum signal amplitude of the current frame is stored, and the position information stored for a certain time is referred to, so that the correction of the extracted waveform position is performed. The position of the maximum signal amplitude of the current frame is stored, and the position information stored for a certain time is referred to, so that the correction of the extracted waveform position is performed. It is contemplated that the amplitude and position variations of the signals in the echo signals will not differ significantly when a relatively smooth, regular breathing waveform occurs. Random occasional noise effects are effects that can be avoided by position correction. The waveform extracted through position correction is adopted, so that burrs are avoided from occurring on the waveform, the extraction of the breathing state is affected, and the problem of state distinguishing errors caused by inaccurate waveform extraction is solved.
In the embodiment, in step 3), the signal zero-crossing rate, the signal ratio, the signal energy, the signal amplitude and the waveform characteristics of the extracted waveform signal are comprehensively judged to distinguish whether the test target is in a human normal breathing state, a body movement state or an unmanned state. The judging flow is as follows: firstly, judging whether a measurement environment has a measurement target or not by using the method, and if the measurement environment has no human, not performing calculation analysis such as apnea and the like; if the target exists, whether the target is in a normal breathing state or a human body movement state is judged according to the characteristics and other characteristics of the signal, and whether the apnea occurs or not is checked in the normal state.
Long-term experiments show that the waveform measured under the condition of no existence of people is similar to random noise, no obvious waveform characteristics exist, and whether the waveform is effective or not can be determined to a certain degree by adopting the zero crossing rate change condition of the waveform with a certain length. The zero crossing rate is greater than a certain threshold value, which indicates that the signal is not collected in a steady state of the human body, and the signal can be considered to be a relatively uniform respiratory signal if the zero crossing rate is lower than a certain threshold value. When a human body exists and the human body is not in a relatively quiet state, the zero crossing rate value of the waveform is large, and erroneous judgment may occur if one index of the zero crossing rate is used alone.
When the human body is in a non-quiet state, the extracted signal waveform, the signal energy and the corresponding amplitude are obviously higher than those in an unmanned state and a calm state.
The waveform data obtained under the condition that the measurement scene is occupied and unoccupied is analyzed, and the waveform amplitude of the corresponding occupied area is found to be obviously raised and is obviously higher than the amplitude of the unmanned section measured at the same time, so that the ratio of different signal sections of the same-frame waveform can be adopted to represent whether a human body target exists in the current measurement section.
In order to judge the current environment state more accurately, signal interception is carried out on the current frame waveform for a plurality of times, and the ratio of the signal average value at the maximum value position to the intercepted signal average value is taken as an evaluation index for reflecting the environment state.
When the human body is in a calm state or a sleeping state, the measurement position is not ideal or the breathing intensity is weakened, and the signal ratio may also be lower than 25 in a period of time. The acquired signal energy is also low, and the signal ratio, the signal energy and the like cannot determine the respiration state at the moment, and the characteristics of the respiration waveform are needed to be used for distinguishing the manned state from the unmanned state at the moment.
When a human body breathes under the quiet condition, the breathing waveform features are obvious, a sine wave with uniform and regular changes is displayed, and whether the breathing waveform is the quiet and stable breathing waveform of the human body is judged according to the distribution situation of wave crests and wave troughs, the zero crossing rate situation between wave crests and between wave troughs and the wave trough and the number of waveform features in a processing waveform segment.
In this embodiment, two indexes of respiratory waveform characteristics and signal amplitude are used to combine the waveform conditions of sleep state, body movement state and signal at the same time, so as to determine whether an apnea phenomenon occurs in the sleep process.
Further, in step 4), classification of the type of apnea is performed according to the waveform characteristics, and the type of apnea includes: hypopnea status, central apneas status, obstructive apneas status, and mixed apneas status.
In the embodiment, in step 5), when it is determined that an apnea phenomenon occurs during sleep, an early warning is performed by an early warning device. When serious respiratory state conditions occur, early warning is timely sent out, a guardian is reminded of the respiratory conditions of the detected objects through early warning signals, and an early warning device such as an audio alarm is arranged at a position which is convenient for the guardian to hear.
In this embodiment, in order to further improve the early warning effect, the method further includes: and sending the real-time breathing state information to the monitoring terminal through a network or Bluetooth and displaying the real-time breathing state information.
The beneficial effects of the invention are as follows: the invention detects the respiratory signal of the tested person by using the radar monitoring module, does not limit the personal freedom of the tested person, does not influence the sleeping quality of the tested person, and has simple operation and no limitation of test places. The invention extracts the actual respiratory signal waveform of the tested person based on the background removing method and the position correcting method, and determines the current measurement state by using the combination of a plurality of methods such as a signal ratio, signal energy, zero-crossing rate, signal waveform characteristics and the like, and judges whether the tested person is in a manned state or an unmanned state. Skipping unnecessary discrimination of other states when no one is present; when the measurement is that someone exists, the respiration value and the physical movement condition are determined by using methods such as signal waveform characteristics, signal energy and the like, meanwhile, whether the person to be measured has an apnea or not is judged by using the signal waveform characteristics, the signal energy and the other parameter assisting methods, the apnea time is counted, meanwhile, a calculation result is displayed on a monitoring terminal in real time, such as an APP interface, the respiration change condition, the physical movement state and the frequency and time of the apnea in the whole test process of the person to be measured are clearly displayed, and when the threshold value is exceeded, an alarm can be dialed by emergency contacts of the person to be measured in the APP, so that the real condition of the person to be measured can be checked conveniently and further medical diagnosis and treatment can be carried out. The invention is simple and easy to use, does not need professional operation, can be used by the old and the children, has accurate detection, and has very important function for diagnosis and treatment of doctors for long-term detection data.
The method is based on a radar signal respiratory monitoring system, a radar detection module is adopted to acquire respiratory motion signals of a chest and abdomen of a tested person, the acquired respiratory signals are transmitted to a processor to carry out one-dimensional fast Fourier transform, background removal and position correction are carried out on the acquired respiratory signals, respiratory state signals are extracted, the respiratory signals in a normal state of the tested person are shown in fig. 1, the respiratory signals in an apnea condition of the tested person are shown in fig. 2, respiratory values and body movement conditions are determined by carrying out methods such as signal ratio, signal waveform characteristic extraction and signal energy on the extracted respiratory signals, meanwhile, whether the respiratory pause phenomenon occurs to the tested person is judged by using signal energy amplitude and signal waveform characteristic, the respiratory pause type and the respiratory pause time which the tested person belongs to are given, meanwhile, the calculation result is sent to an APP end or a PC end of a mobile phone in a network or Bluetooth mode, the result is displayed on an APP or PC end interface in real time, and the respiratory frequency change condition, the body movement state and the frequency and the time of the respiratory pause condition in the whole testing process of the tested person are clearly shown, and an emergency alarm can be dialled to the tested person in case that the threshold value is exceeded.
In a specific embodiment of the invention, the radar detection module adopts a transmitted modulated continuous wave as an original vital signal detection instrument to obtain a respiratory signal of a tested person; the processing of the respiration signals, the calculation of the respiration values and the like are all signal processing modules which are combined with the radar detection module, the signal processing modules can directly extract waveforms of respiration states, a large amount of data are not required to be transmitted to the PC end, and the memory can be saved. The signal processing module can transmit the calculation result with the mobile phone APP or the PC end in a wired, wireless or Bluetooth mode, so that the extracted breathing state result can be conveniently and directly displayed on an interface, and inquiry and watching are facilitated.
In the respiratory state extraction process, an original respiratory signal is extracted according to a background removal method and a position correction mode, interference such as burrs in the extracted respiratory signal is removed by carrying out median filtering and smooth filtering on the signal, and a measurement state is distinguished by various conditions such as a signal ratio, signal energy, zero crossing rate, respiratory waveform characteristics and the like: unmanned state, body movement state, normal state. Calculation of the respiratory value can be directly skipped under the unmanned state, so that the calculation time is saved, and the calculation amount is reduced; under the condition that people and body movements exist, the calculation of the apnea and the respiration value is not performed, and only when the human body is in a calm state, the calculation of the apnea and the respiration value is performed, and the specific method is as follows:
filtering the extracted signal waveform by adopting low-pass filtering to remove signals with the frequency higher than 1HZ, searching peak values according to the respiratory signal respiratory interval and judging the searching effectiveness of the period, calculating respiratory values by combining a frequency domain method, adopting respiratory signal energy of specific time and updating an apnea energy threshold in real time in the respiratory searching process, judging the apnea if the respiratory signal energy is lower than the apnea energy amplitude threshold in the stable respiratory process, and classifying the apnea types according to different characteristics of the apnea signals, wherein the method mainly comprises four types of obstructive apnea, central apnea, mixed apnea and hypopnea. FIG. 3 shows an apnea event, an apnea time and an apnea type obtained by an energy method in a certain sleeping process in an implementation, wherein 0 represents a normal state; 1 represents hypopnea; 2 represents obstructive apnoea; 3 represents central apneas; 4 denotes mixed apneas. When an apnea serious condition occurs, emergency measures can be taken by dialing emergency contacts. According to the energy change condition, whether the body movement phenomenon occurs in the sleeping process can be determined, so that the sleeping stable state of the tested person in the whole night can be analyzed.
The method for extracting the respiratory state based on the radar signal comprises the following specific steps:
1) Setting hardware parameters of a radar detection module, and determining detection distance, sampling frequency and the like;
2) The radar detection module is installed and electrified, and respiratory signals of a tested person in a period of time are collected;
3) The collected signals are subjected to background removal, the background frame synthesized by the current frame and the previous frame according to a certain proportion is subtracted from the current frame, so that the removal of environmental noise is ensured, and the breathing waveform corresponding to the position of the detected person is extracted by using a position correction method;
4) The measurement state is an unmanned state, a body movement state or a normal state by combining a signal ratio, a signal amplitude, signal energy, a zero crossing rate and a signal waveform mode;
further classification of apneas is performed in a state where the human body is normal;
5) When the human body is in a normal breathing state, an apnea state exists.
The method for identifying the breathing pause in the breathing state comprises the following steps: the energy of the waveform is obtained within 5s, the energy threshold is searched in real time, the number lower than the energy threshold is accumulated in real time, the number higher than the threshold is counted at the same time, the energy is used for judging whether the body movement occurs, when the body movement occurs, the apnea condition is not judged within the time period, and the parameter for the apnea is initialized. When judging the apnea state, the human body needs to be considered to be in a stable sleep breathing state for a period of time before the apnea occurs, and whether the human body is in a sleep state or not and whether the human body monitored before the apnea state is entered into a uniform breathing state or not needs to be judged.
In the embodiment of the invention, the background removing method is preferentially used for removing the interference caused by the unstable background, and meanwhile, the position correcting method is combined for extracting more accurate and smooth respiratory signals.
In order to reduce unnecessary computation, it is first determined whether or not the extracted waveform is a waveform in the presence of a person. Judging whether the waveform exists or not, and judging whether a measured human body target exists in the monitoring time by combining various parameters such as the energy of the extracted waveform, the ratio of a useful signal to an environmental signal, the characteristics of the extracted waveform, the duration of a stable waveform, the zero crossing rate of the extracted waveform and the like.
The zero crossing rate method used in the invention comprises the following steps:
long-term experiments show that the waveform change condition such as noise measured in the absence of people has no obvious waveform characteristics, and whether the waveform is effective or not can be determined to a certain degree by adopting the zero crossing rate change condition of the waveform extracted in a period of time. When a human body exists and the human body is not in a relatively quiet state, the zero crossing rate value of the waveform is large, and erroneous judgment may occur if one index of the zero crossing rate is used alone.
The signal ratio method used in the invention comprises the following steps:
when the human body is in the waveform extracted in the non-quiet state, the waveform energy and the corresponding amplitude are obviously higher than those in the unmanned state. In order to judge the current environment state more accurately, signal interception is carried out on the current frame waveform for a plurality of times, and the ratio of the signal average value at the maximum value position to the intercepted signal average value is taken as an evaluation index for reflecting the environment state.
When people and no people exist in the measurement scene, the waveform obtained in real time is observed, and the waveform amplitude of the corresponding people area is found to show obvious bulges which are obviously higher than that of the unmanned section of synchronous measurement, so that the ratio of different signal sections of the same-frame waveform is adopted to represent whether a human body target exists in the current measurement section.
When no test target exists in the test scene, the amplitude change condition of the same-frame waveform is not particularly large, the obtained signal ratio is low, and long-term test shows that the signal ratio is lower than 25 under the unmanned condition and has no dimension. When someone exists, the signal ratio value is more than 100 and the object is in obvious motion, and the object is dimensionless. A certain amount of signal ratio is stored for use in determining the current environmental state.
Under the condition that targets exist, the whole frame of signals can show amplitude change conditions of different degrees, and certain errors can occur when the ratio of different parts of the same frame of signals is singly used, but the energy calculation is performed by using fixed-length data in the extracted waveform, so that the body movement state can be obviously distinguished. The waveform length used for energy calculation should not be too long, in order to use the energy condition for judging whether the breathing waveform has the apnea condition, the waveform energy in 5s is recommended, because the phenomenon of the apnea can be considered to occur when the breathing is stopped for more than 10s, and therefore, the signal energy in too long period of time cannot be used.
Breathing waveform characteristics used in the present invention: in a calm or sleep state, the signal ratio may also be below 25 for a period of time, possibly due to non-ideal measurement positions or weakened respiration intensity. The signal energy acquired at this time is also low, and it is necessary to distinguish between the manned state and the unmanned state according to the characteristics of the respiratory waveform. When a human body breathes under the quiet condition, the breathing waveform features are obvious, a sine wave with uniform and regular changes is presented, and whether the human body is quiet and stable breathing waveform is judged according to the distribution situation of wave crests and wave troughs, the zero crossing rate situation of the waveform between wave crests and wave troughs and the number of waveform features in a processing waveform segment.
The invention uses signal ratio, signal amplitude, signal energy, signal waveform characteristics, zero crossing rate and the like to judge the measurement state according to the complexity of the state of the breathing process. Under the condition that the state is distinguished to be the normal breathing state, a low-pass filter is adopted to filter out the high-frequency signal, so that the influence of the high-frequency signal on the breathing signal is reduced. In the process of searching the respiratory value under the normal respiratory state, taking the situation that the respiratory frequency difference of different detected people and age groups is too large into consideration, adopting strategy level searching of searching for multiple respiratory periods, avoiding missing detection of waveforms under special conditions, still monitoring signal validity under the condition that the respiratory signal is determined to be available, determining the respiratory period and determining the respiratory frequency under the assistance of waveform frequency domain.
The invention aims at the time that the duration of stopping the flow of the oral and nasal air is longer than 10s in the sleeping process aiming at the apnea occurring in the breathing process, so the data volume of a signal segment of an energy spectrum is smaller than 10 s. The invention adopts the obtained energy in 5s time, and the used energy amplitude threshold value is updated and searched in real time.
The specific distinguishing method for distinguishing the types of the apneas is as follows:
when the human body is in a calm and uniform breathing state, the waveform amplitude in the state is calculated to obtain a steady state amplitude, and when the signal energy amplitude sliding in real time is smaller than 0.5 of the steady state signal energy amplitude, the condition of entering into the apnea is judged. For different apneic waveform characteristics, the apneic conditions may be categorized into a hypoventilation state, an obstructive apneic state, a central apneic state, a mixed apneic state.
Two indexes of respiratory waveform characteristics and signal energy amplitude are mainly used in the classification of the apneas. When the condition of the apnea is met, the signal energy amplitude is lower than 0.5 of the energy threshold value, and no respiratory waveform is provided at all, the central apnea is caused; when the energy amplitude of the signal is lower than 0.5 of the energy threshold value in the process of the apnea and the respiratory waveform is presented, the signal is in an obstructive apnea state; when the energy amplitude of the signal is lower than 0.5 of the energy threshold value in the process of the apnea, and part of the signal is characterized by breathing waveform, and the other part of the signal is completely non-waveform in the process of the apnea, the signal is considered to be a mixed type apnea state; when an apnea procedure is entered, the signal energy amplitude is below 0.7 of the energy threshold and several conditions are not met, the hypopnea condition is considered.
According to the invention, aiming at different energy spectrums of different people, a constant energy spectrum threshold cannot be used, the energy spectrum threshold is updated in real time, and the energy spectrum is updated in a state that the breathing state is stable and no obvious body movement exists. When the body movement state occurs, the detection of the apnea is stopped within 20s, and the condition of false alarm of the apnea is prevented.
The method for extracting the respiratory state based on the radar signal can be used for measuring the respiratory state of a tested person within a range of 2m, does not need to limit the freedom of the person, and is simple to operate and accurate in signal extraction.
The method for extracting the respiratory state based on the radar signal can observe the respiratory state in the whole test process, can check the variation trend of respiratory values, the occurrence frequency, the time and the type of the apnea, and has a vital effect on the diagnosis of a subsequent doctor through long-term data accumulation.
The method is obtained through long-term actual measurement, and in the actual measurement process, the state of a measurement signal is judged by referring to various conditions such as a signal waveform ratio, a signal waveform amplitude, a signal waveform energy, a signal waveform zero crossing rate, a signal waveform characteristic and the like, and the single use can cause the misjudgment of the measurement condition.
The preferred embodiments of the present invention have been described in detail above with reference to the accompanying drawings, but the present invention is not limited to the specific details of the above embodiments, and various simple modifications can be made to the technical solution of the present invention within the scope of the technical concept of the present invention, and all the simple modifications belong to the protection scope of the present invention.
In addition, the specific features described in the above embodiments may be combined in any suitable manner, and in order to avoid unnecessary repetition, various possible combinations are not described further.
Moreover, any combination of the various embodiments of the invention can be made without departing from the spirit of the invention, which should also be considered as disclosed herein.
Claims (4)
1. A method of extracting a respiration state based on radar signals, the method comprising the steps of:
1) The radar detection module transmits a modulated continuous wave, performs one-dimensional fast Fourier transform on the received modulated continuous wave in a plurality of periods, and calculates the frequency shift of the transmitted wave;
2) When the frequency shift of the emission wave is offset, the influence of environmental noise is removed, and a real motion signal of the chest is extracted;
3) Judging whether the test target is in a normal breathing state, a body movement state or an unmanned state of the human body according to the extracted waveform signals;
4) When the human body is judged to be in a normal breathing state, calculating a breathing value according to the waveform characteristics of the breathing signals, and judging whether an apnea phenomenon occurs in the sleeping process or not;
in the step 2), the waveform subjected to FFT conversion eliminates the noise influence caused by the external environment in the chest and abdomen respiration state of the non-contact measurement testee by a background removal method;
the background removing method comprises the following steps: reconstructing signal waveforms by using current frame signals and previous frame signals in different proportions as background frames, and eliminating influence of external environment on signals by subtracting the background frames from the current frames;
when the test target is in calm and regular respiration, randomly occurring noise influences are subjected to a position correction method, and a real chest movement signal is extracted;
the position correction method comprises the following steps: storing the position of the maximum signal amplitude of the current frame, and correcting the extracted waveform position by referring to the position information stored for a certain time;
in the step 3), comprehensively judging the extracted waveform signals by adopting the signal zero crossing rate, the signal ratio, the signal energy, the signal amplitude and the waveform characteristics to distinguish whether the test target is in a normal human respiratory state, a body movement state or an unmanned state;
and judging whether an apnea phenomenon occurs in the sleeping process by combining two indexes of breathing waveform characteristics and signal amplitude with the waveform conditions of the sleeping state, the body movement state and the signal.
2. The method of extracting respiratory state based on radar signals according to claim 1, wherein in step 4), classification of an apnea type is performed according to waveform characteristics, the apnea type including: hypopnea status, central apneas status, obstructive apneas status, and mixed apneas status.
3. The method for extracting respiratory state based on radar signal according to claim 1, wherein in step 5), when it is judged that an apnea phenomenon occurs during sleep, an early warning is performed by an early warning device.
4. The method of extracting respiratory state based on radar signals of claim 1, further comprising: and sending the real-time breathing state information to the monitoring terminal through a network or Bluetooth and displaying the real-time breathing state information.
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