CN114176564A - Method for extracting respiratory state based on radar signal - Google Patents
Method for extracting respiratory state based on radar signal Download PDFInfo
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Abstract
The invention discloses a method for extracting a respiratory state based on a radar signal, which comprises the following steps: 1) the radar detection module transmits modulated continuous waves, performs one-dimensional fast Fourier transform on the received modulated continuous waves in a plurality of periods, and calculates the frequency shift of the transmitted waves; 2) when the frequency shift of the transmitted wave has 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 aiming at the extracted waveform signals; 4) and when the human body is in a normal breathing state, calculating a breathing value according to the waveform characteristics of the breathing signal, and then judging whether the apnea phenomenon occurs in the sleeping process. The method collects the respiratory signal of the tested person, and the measurement is carried out without direct contact with the human body, so that the operation is simple and convenient, and the human body moves freely.
Description
Technical Field
The invention relates to the technical field of respiration detection, in particular to a method for extracting a respiration state based on a radar signal.
Background
The respiratory state in the sleeping process is related to human health, the phenomena of airway obstruction, mouth and nose airflow obstruction, apnea or snoring in the long-term breathing and the like in the sleeping process are not timely treated, serious harm is caused to the body, and the patient dies, so that the monitoring of the respiratory state in the sleeping process is very important.
The common methods for breathing state in sleep at present mainly include polysomnography, wrist type activity recorder, sleep mattress and the like. The polysomnography requires a plurality of physiological signals such as electroencephalograms, electrocardiograms, blood oxygen saturation, oculograms and the like to be measured simultaneously by professional instruments in a professional hospital, electrodes are easy to fall off in the test process, the process is complex, the personal freedom of a tested person is limited, data analysis is required by professional doctors, the cost is high, and the application range is limited. The wrist type activity recorder needs to be worn on limbs, and although the body movement condition in the sleeping process can be measured, the breathing state cannot be distinguished. The sleep mattress measures the breathing signal in the sleep process through the pressure sensor, but because the testee needs to sleep on the mattress, the sleep condition of the testee can be influenced, and the sleep breathing result is influenced.
Disclosure of Invention
The invention aims to provide a method for extracting a respiratory state based on a radar signal, which 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 understanding of the tested person on the sleeping condition and the health state of the tested person.
In order to achieve the above object, the present invention provides a method for extracting a respiratory state based on a radar signal, the method comprising the steps of: 1) the radar detection module transmits modulated continuous waves, performs one-dimensional fast Fourier transform on the received modulated continuous waves in a plurality of periods, and calculates the frequency shift of the transmitted waves; 2) when the frequency shift of the transmitted wave has 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 aiming at the extracted waveform signals; 4) and when the human body is in a normal breathing state, calculating a breathing value according to the waveform characteristics of the breathing signal, and then judging whether the apnea phenomenon occurs in the sleeping process.
Preferably, in step 2), noise influence caused by an external environment in the chest-abdomen respiration state of the non-contact measurement measured person is eliminated through a background removing method by the waveform subjected to the FFT.
Preferably, the background removal method is as follows: the signal waveform of the current frame signal and the signal waveform of the previous frame are reconstructed in different proportions to be used as a background frame, and the influence of the external environment on the signals is eliminated by subtracting the background frame from the current frame.
Preferably, when the test object is in a state of quiet and regular breathing, the real motion signal of the chest is extracted by a position correction method under the influence of randomly occurring noise.
Preferably, the method of position correction is: the position of the maximum signal amplitude of the current frame is stored, and the waveform position is extracted and corrected by referring to the position information stored for a certain time in the past.
Preferably, in step 3), the extracted waveform signal is comprehensively judged by adopting a signal zero crossing rate, a signal ratio, signal energy, a signal amplitude and waveform characteristics to distinguish whether the test target is in a normal breathing state, a body movement state or an unmanned state of a human body.
Preferably, the breathing waveform characteristic and the signal amplitude are used for simultaneously combining the sleeping state, the body movement state and the waveform condition of the signal to judge whether the apnea phenomenon occurs in the sleeping process.
Preferably, in step 4), the classification of the apnea type is performed according to the waveform characteristics, and the apnea type includes: a low ventilation state, a central apnea state, an obstructive apnea state, and a mixed apnea state.
Preferably, in the step 5), when the apnea phenomenon is judged to occur in the sleeping process, early warning is performed through an early warning device.
Preferably, the method further comprises: and sending the real-time breathing state information to a 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 the human body, judge the respiratory state of the tested person, improve the monitoring of the apnea phenomenon 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, which are included to provide a further understanding 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 and not to limit the invention. In the drawings:
FIG. 1 is a respiratory signal extracted according to the method of the present invention;
FIG. 2 is an apnea signal extracted according to the method of the present invention;
fig. 3 shows the apnea event, apnea duration and apnea type signals obtained by energy spectroscopy during a sleep session.
Detailed Description
The following detailed description of embodiments of the invention refers to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the present invention, are given by way of illustration and explanation only, not limitation.
In the present invention, unless otherwise specified, directional words included in terms such as "upper, lower, left, right, front, rear, inner, and outer" and the like merely represent the directions of the terms in a normal use state or are colloquially known by those skilled in the art, and should not be construed as limiting the terms.
The invention provides a method for extracting a respiratory state based on a radar signal, which comprises the following steps: 1) the radar detection module transmits modulated continuous waves, performs one-dimensional fast Fourier transform on the received modulated continuous waves in a plurality of periods, and calculates the frequency shift of the transmitted waves; 2) when the frequency shift of the transmitted wave has 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 aiming at the extracted waveform signals; 4) and when the human body is in a normal breathing state, calculating a breathing value according to the waveform characteristics of the breathing signal, and then judging whether the apnea phenomenon occurs in the sleeping process.
Through the implementation of 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 apnea phenomenon in the sleeping process, and facilitate the knowledge of the tested person on the sleeping condition and the health state of the tested person in a non-contact mode. The method has the advantages that the extracted waveform signals are firstly distinguished to determine the state of a test target, such as the normal breathing state, the body movement state or the unmanned state of a human body, whether the human body exists in the measurement condition is firstly distinguished, unnecessary operation can be avoided, the code operation speed can be improved, and the problems that the breathing state is wrongly analyzed in the unmanned condition and the human state is considered to be the unmanned condition in the unmanned condition are solved.
In this embodiment, in order to further provide a way to extract an accurate signal, in step 2), the waveform after FFT conversion is used to eliminate the noise influence caused by the external environment in the chest-abdomen respiration state of the subject by non-contact measurement by a background removal method.
Further, the background removing method comprises the following steps: the signal waveform of the current frame signal and the signal waveform of the previous frame are reconstructed in different proportions to be used as a background frame, and the influence of the external environment on the signals is eliminated by subtracting the background frame from the current frame. Specifically, the background removal method is to combine the current frame waveform and the previous frame waveform into background frame data according to a certain proportion, and then subtract the background frame data waveform from the current frame waveform to obtain a background-removed waveform, thereby avoiding the influence caused by noise.
In the embodiment, when the test object is in a state of calm and regular breathing, the real motion signal of the chest is extracted by a position correction method under the influence of randomly occurring noise. The thoracic echo signal of the measurement target is subjected to a series of processing to obtain a signal subjected to one-dimensional FFT processing, and the waveform is extracted at a corresponding position after certain time accumulation. In the process of extraction, in order to avoid interference of occasional signal fluctuation, 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 waveform position is extracted and corrected by referring to the position information stored for a certain time in the past. The position of the maximum signal amplitude of the current frame is stored, and the waveform position is extracted and corrected by referring to the position information stored for a certain time in the past. Considering that the signal amplitude position change in the echo signal does not have a large difference under the condition of a relatively stable and regular respiration waveform. Random occasional noise effects are such that they can be avoided by position correction. The waveform extracted by position correction is adopted, so that the waveform is prevented from generating burrs, the extraction of a respiratory state is further influenced, and the problem of state distinguishing errors caused by inaccurate waveform extraction is solved.
In the embodiment, in step 3), the extracted waveform signal is comprehensively judged by using a signal zero crossing rate, a signal ratio, signal energy, a signal amplitude and waveform characteristics to distinguish whether the test target is in a normal breathing state, a body movement state or an unmanned state of a human body. The judgment process is as follows: firstly, judging whether a measurement environment has a measurement target by using the method, and if the measurement environment is unmanned, carrying out calculation analysis such as apnea and the like; when a target exists, whether the target is in a normal breathing state or a human body movement state needs to be judged according to the characteristics and other characteristics of the signal, whether apnea occurs or not needs to be checked in the normal state, and unnecessary operation can be avoided through the design.
Long-term experiments show that the waveform measured in the absence of people is similar to random noise and 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 with a certain length. The zero-crossing rate is greater than a certain threshold value, which indicates that the section of signal is not collected in a stable state of the human body, and when the zero-crossing rate is lower than a certain threshold value, the section of signal can be determined to be a more uniform respiratory signal. 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 if the zero-crossing rate is used alone, misjudgment may occur.
When the human body is in a non-quiet state, the signal energy and the corresponding amplitude of the extracted signal waveform are obviously higher than those of the signal energy and the corresponding amplitude in an unmanned state and a quiet state of the human body.
Waveform data obtained under the condition that people exist and no people exist in a measurement scene are analyzed, and the waveform amplitude value in a corresponding occupied area presents an obvious bulge which is obviously higher than the amplitude value of an 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 more accurately judge the current environment state, signal interception is carried out on the current frame waveform for multiple times, and the ratio of the average value of the signal at the position of the maximum value to the average value of the intercepted signal is taken as an evaluation index reflecting the environment state.
When the human body is in a calm state or a sleep state, the signal ratio may be lower than 25 in a period of time due to the non-ideal measuring position or the weak breathing intensity. The acquired signal energy is also low, the signal ratio, the signal energy and the like cannot determine the breathing state at the moment, and the characteristic of the breathing waveform is needed to distinguish 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 and present a sine wave which is changed uniformly and regularly, and whether the human body is the quiet and stable breathing waveform is judged according to the distribution condition of wave crests and wave troughs, the zero crossing rate condition between the wave crests and between the wave troughs and the number of the waveform features in the processed waveform section.
In the embodiment, the breathing waveform characteristic and the signal amplitude are used for simultaneously combining the sleeping state, the body movement state and the waveform condition of the signal to judge whether the apnea phenomenon occurs in the sleeping process.
Further, in step 4), classifying the apnea type according to the waveform characteristics, wherein the apnea type comprises: a low ventilation state, a central apnea state, an obstructive apnea state, and a mixed apnea state.
In the embodiment, in step 5), when the apnea phenomenon is judged to occur in the sleeping process, the early warning is performed through an early warning device. The early warning device is an audio alarm, and the audio alarm is arranged at a position 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 a monitoring terminal through a network or Bluetooth and displaying the real-time breathing state information.
The invention has the beneficial effects that: the invention uses the radar monitoring module to detect the respiratory signal of the tested person, does not limit the personal freedom of the tested person, does not influence the sleep quality of the tested person, has simple operation and does not limit the test place. The invention extracts real respiration signal waveform of the tested person based on a background removal method and a position correction method, determines the current measurement state by combining a plurality of methods such as 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. When no one is in the condition, skipping unnecessary distinguishing of other states; when the measured data is in the human condition, the breathing value and the body movement condition are determined by using methods such as signal waveform characteristics, signal energy and the like, whether the tested person has apnea or not is judged by using the signal waveform characteristics and the signal energy and using other parameters in an auxiliary mode, the apnea time is timed, meanwhile, a calculation result is displayed on a monitoring terminal in real time, if the calculation result is displayed on an APP interface, the breathing change condition and the body movement state of the tested person in the whole testing process and the frequency and time of apnea are clearly displayed, and when the calculation result exceeds a threshold value, an emergency contact of the tested person in the APP can be dialed to send an alarm, so that the real condition of the tested person can be conveniently rechecked 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 by detecting data for a long time.
The method of the invention is a respiration monitoring system based on radar signals, a radar detection module is adopted to obtain a respiratory motion signal of the chest and abdomen of a tested person, the obtained respiratory signal is transmitted to a processor to be subjected to one-dimensional fast Fourier transform, the obtained signal is subjected to background removal and position correction, a respiratory state signal is extracted, fig. 1 is the respiratory signal of the tested person in a normal state, fig. 2 is the respiratory signal of the tested person under the condition of apnea, the respiratory value and the physical movement condition are determined by the method of signal ratio, signal waveform characteristic extraction, signal energy and the like of the extracted respiratory signal, simultaneously, the signal energy amplitude and the signal waveform characteristic are used for judging whether the tested person has the apnea phenomenon, the type and the apnea time of the tested person are given when the apnea occurs, and meanwhile, the calculation result is sent to a mobile phone end or a PC end in a network or Bluetooth mode, the result is displayed on an APP or PC end interface in real time, the breathing frequency change condition, the body movement state and the frequency and time of apnea of the testee in the whole test process are clearly displayed, and the emergency contact of the testee in the APP can be dialed to send an alarm when the breathing frequency change condition exceeds a threshold value.
In the specific embodiment of the invention, the radar detection module adopts the emission modulation continuous wave as an original vital signal detection instrument to obtain the respiratory signal of a detected person; the processing of the respiration signal, the calculation of the respiration value and the like are performed on the signal processing module which is integrated with the radar detection module, the waveform of the respiration state can be directly extracted by the signal processing module, a large amount of data are not required to be transmitted to a PC (personal computer) end, and the memory can be saved. The signal processing module can carry out the transmission of computational result through wired or wireless, bluetooth's mode and cell-phone APP or PC end, conveniently with the breathing state result direct display who draws out at the interface, the inquiry of being convenient for is watched.
In the process of extracting the respiratory state, extracting an original respiratory signal according to a background removal method and a position correction method, carrying out median filtering and smooth filtering on the signal, removing interferences such as burrs and the like in the extracted respiratory signal, and distinguishing the measurement state through various conditions such as a signal ratio, signal energy, a zero crossing rate, respiratory waveform characteristics and the like: unmanned state, body movement state, normal state. The calculation of breath pause and breath value can be directly skipped under the unmanned state, thereby saving the calculation time and reducing the calculation amount; under the condition of human body and body movement, the calculation of apnea, respiration value and the like is not carried out, and the calculation of apnea and respiration value is carried out only when the human body is in a calm state, and the specific method comprises the following steps:
the method comprises the steps of filtering signals with frequency higher than 1HZ by adopting low-pass filtering on extracted signal waveforms, searching peak values and judging validity of searching the period according to breathing intervals of breathing signals, calculating breathing values by combining a frequency domain method, adopting breathing signal energy of specific time in the process of breathing searching, updating an apnea energy threshold in real time, starting to judge apnea if the breathing signal energy is lower than an apnea energy amplitude threshold in a stable breathing process, and classifying apnea types according to different characteristics of the apnea signals, wherein the extracted signal waveforms can be mainly divided into four types, namely blocking apnea, central apnea, mixed apnea and low-pass ventilation. FIG. 3 illustrates an apnea event, apnea duration, and apnea type obtained by energy method during a sleep session in an embodiment, where 0 represents a normal state; 1 represents low ventilation; 2 for obstructive apnea; 3 represents central apnea; and 4 for mixed apnea. When severe apnea conditions occur, emergency measures can be taken by dialing emergency contacts. Whether the body movement phenomenon occurs in the sleeping process can be determined according to the change condition of the energy, so that the sleep stable state of the tested person all 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) installing and electrifying a radar detection module, and acquiring a respiratory signal of a measured person within a period of time;
3) the acquired signal is subjected to background removal, a background frame which is synthesized by a current frame and a previous frame according to a certain proportion is subtracted from the current frame, so that the removal of environmental noise is ensured, and a respiratory waveform corresponding to the position of a measured person is extracted by using a position correction method;
4) judging whether 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 when the human body is in a normal state;
5) when the human body is in a normal breathing state, an apnea state also exists.
The method for identifying apnea in the respiratory state comprises the following steps: acquiring waveform energy within 5s, searching an energy threshold in real time, accumulating the number lower than the energy threshold in real time, counting the number higher than the threshold at the same time, and judging whether the physical movement condition occurs, wherein when the physical movement occurs, the apnea condition is not judged within the time period, and parameters for apnea are initialized. When the apnea state is judged, the stable sleep breathing state of the human body in a period of time before the apnea occurs needs to be considered, whether the human body is in the sleep state needs to be judged, and whether the monitored human body is in the uniform breathing state before the apnea state is entered needs to be judged.
In the embodiment of the invention, the interference caused by unstable background is removed by preferentially using a background removing method, and meanwhile, a more accurate and smooth respiratory signal is extracted by combining a position correction method.
In order to reduce the amount of 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 has the condition of human existence, and judging whether a human body target to be measured 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 condition 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 extent by adopting the zero-crossing rate change condition of the waveform extracted within 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 the zero-crossing rate is used alone as an index.
The signal ratio method used in the present invention:
when the human body is in a non-quiet state, the waveform energy and the corresponding amplitude are obviously higher than those of the waveform energy and the corresponding amplitude in an unmanned state. In order to more accurately judge the current environment state, signal interception is carried out on the current frame waveform for multiple times, and the ratio of the average value of the signal at the position of the maximum value to the average value of the intercepted signal is taken as an evaluation index reflecting the environment state.
Under the condition that people exist and no people exist in a measurement scene, the waveform obtained under the real-time condition is observed, and the waveform amplitude value in a corresponding people area presents obvious bulges which are obviously higher than the condition of the unmanned section measured at the same period, so that the ratio of different signal sections of the waveform of the same frame 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 waveform in the same frame 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 condition of no person and is dimensionless. When a person exists and the target is in obvious motion, the signal ratio value is larger than 100 and is dimensionless. A certain amount of signal ratio is stored for use in determining the current environmental state.
Because the whole frame of signal can present amplitude variation conditions of different degrees under the condition that a target exists, certain errors can also occur when the ratio of different parts of the same frame of signal is independently used, but the body movement state can be obviously distinguished by using fixed-length data to calculate energy in the extracted waveform. The waveform length for energy calculation is not too long, and in order to use the condition of energy for judging whether apnea occurs in a respiratory waveform, the waveform energy within 5s is recommended, because the phenomenon of apnea can be considered to occur when the mouth and nose stop breathing for more than 10s, and therefore signal energy of too long time periods cannot be used.
Respiratory waveform characteristics used in the present invention: in a state of calm or sleep, the signal ratio may be below 25 for a period of time, possibly due to an unsatisfactory measurement position or a weak breathing intensity. The energy of the acquired signal is also low, and the human state or the unmanned state needs to be distinguished according to the characteristics of the respiratory waveform. When a human body breathes under the quiet condition, the breathing waveform features are obvious, sine waves which are uniformly and regularly changed are presented, and whether the human body breathes in a quiet and stable manner is judged according to the distribution condition of wave crests and wave troughs, the wave zero crossing rate condition between the wave crests and between the wave troughs and the number of the wave features in the processed waveform section.
The invention judges the measuring state by using signal ratio, signal amplitude, signal energy, signal waveform characteristics, zero crossing rate and the like according to the complexity of the breathing process state. And under the condition of distinguishing the state to which the respiratory system belongs as a normal respiratory state, filtering out the high-frequency signal by using a low-pass filter, thereby reducing the influence of the high-frequency signal on the respiratory signal. In the process of searching the respiratory value in the normal respiratory state, the situation that the respiratory frequency difference of different detected people and age groups is overlarge is considered, the strategy level searching of multiple respiratory cycle searching is adopted, the missing detection of waveforms in special situations is avoided, the signal effectiveness is still monitored under the condition that the respiratory signal is available, the respiratory cycle is determined, and the respiratory frequency is determined under the assistance of a waveform frequency domain.
The invention aims at the phenomenon that the apnea occurring in the breathing process refers to the time that the duration of the stop of the oronasal airflow is more than 10s in the sleeping process, so that the data volume of a signal segment of an energy spectrum is less than 10 s. The invention adopts the acquired energy within 5s, and the used energy amplitude threshold value is updated and searched in real time.
The specific method for distinguishing the type of apnea is as follows:
when the human body is in a calm and uniform breathing state, the waveform amplitude of the state is calculated to obtain the steady state amplitude, and when the real-time sliding signal energy amplitude is smaller than the steady state signal energy amplitude by 0.5, the condition of entering apnea is judged. Apnea conditions can be classified as low-ventilation, obstructive, central, mixed apnea conditions for different apnea waveform characteristics.
When the apnea classification is carried out, two indexes of respiratory waveform characteristics and signal energy amplitude are mainly used. When the condition that the respiratory pause state is met, the signal energy amplitude is lower than 0.5 of the energy threshold value and no respiratory waveform exists, the central respiratory pause state is established; when the signal energy amplitude is lower than 0.5 of the energy threshold value in the apnea process and a respiration waveform is presented, the state is in an obstructive apnea state; when the signal energy amplitude is lower than 0.5 of the energy threshold value in the apnea process, and in the apnea process, a part of the signal has respiratory waveform characteristics, and a part of the signal is not in a waveform at all, the signal is considered to be in a mixed apnea state; when the apnea process is entered, the signal energy amplitude is lower than 0.7 of the energy threshold value, and the above conditions are not met, the state is considered to be a low-ventilation state.
The energy spectrum threshold value is updated in real time aiming at the fact that different crowds cannot use the constant energy spectrum threshold value due to different energy spectrums, and the energy spectrum is updated in a stable breathing state without obvious body movement. When the body movement state occurs, the breathing pause detection is stopped within 20s, and the situation of false alarm of breathing pause is prevented.
The method for extracting the respiratory state based on the radar signal can be used for measuring the respiratory state of a measured person within the 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 change trend of the respiratory value, the occurrence frequency, the occurrence time and the type of apnea, and has a vital effect on the subsequent diagnosis of a doctor due to long-term data accumulation.
The method provided by the invention is obtained through long-term actual measurement, multiple conditions such as a reference signal waveform ratio, a signal waveform amplitude, signal waveform energy, a signal waveform zero crossing rate, signal waveform characteristics and the like are required for judging the state of a measurement signal in the actual measurement process, the single use can cause the misjudgment condition of the measurement condition, and the multiple judgment conditions are the method provided by integrating the problems encountered in the actual measurement scene, so that the misjudgment state is avoided.
The preferred embodiments of the present invention have been described in detail with reference to the accompanying drawings, however, 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 technical idea of the present invention, and these simple modifications are within the protective scope of the present invention.
It should be noted that the various technical features described in the above embodiments can be combined in any suitable manner without contradiction, and the invention is not described in any way for the possible combinations in order to avoid unnecessary repetition.
In addition, any combination of the various embodiments of the present invention is also possible, and the same should be considered as the disclosure of the present invention as long as it does not depart from the spirit of the present invention.
Claims (10)
1. A method of extracting a respiratory state based on a radar signal, the method comprising the steps of:
1) the radar detection module transmits modulated continuous waves, performs one-dimensional fast Fourier transform on the received modulated continuous waves in a plurality of periods, and calculates the frequency shift of the transmitted waves;
2) when the frequency shift of the transmitted wave has 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 aiming at the extracted waveform signals;
4) and when the human body is in a normal breathing state, calculating a breathing value according to the waveform characteristics of the breathing signal, and then judging whether the apnea phenomenon occurs in the sleeping process.
2. The method for extracting a respiratory state based on radar signals as claimed in claim 1, wherein in step 2), the waveform after FFT transform eliminates noise influence caused by external environment in the chest-abdomen respiratory state of the subject by non-contact measurement through a background removal method.
3. The method for extracting a respiratory state based on a radar signal according to claim 2, wherein the background removing method comprises: the signal waveform of the current frame signal and the signal waveform of the previous frame are reconstructed in different proportions to be used as a background frame, and the influence of the external environment on the signals is eliminated by subtracting the background frame from the current frame.
4. The method for extracting respiratory states based on radar signals according to claim 2, wherein when the test object is in a quiet and regular breathing state, the true motion signals of the chest are extracted by a position correction method due to the influence of random noise.
5. The method for extracting a respiratory state based on a radar signal according to claim 4, wherein the position correction method comprises: the position of the maximum signal amplitude of the current frame is stored, and the waveform position is extracted and corrected by referring to the position information stored for a certain time in the past.
6. The method for extracting a respiratory state based on radar signals as claimed in claim 1, wherein in step 3), the extracted waveform signals are comprehensively judged by using a signal zero crossing rate, a signal ratio, signal energy, a signal amplitude and waveform characteristics to distinguish whether the test target is in a normal respiratory state, a physical movement state or an unmanned state of a human body.
7. The method for extracting the respiratory state based on the radar signal as claimed in claim 1, wherein the breathing waveform characteristic and the signal amplitude are used to determine whether the apnea phenomenon occurs during the sleep process by simultaneously combining the sleep state, the body movement state and the waveform condition of the signal.
8. The method for extracting a respiratory state based on a radar signal according to claim 1, wherein in step 4), the classification of the apnea type is performed according to the waveform characteristics, and the apnea type comprises: a low ventilation state, a central apnea state, an obstructive apnea state, and a mixed apnea state.
9. The method for extracting the respiratory state based on the radar signal as claimed in claim 1, wherein in the step 5), when the apnea phenomenon is determined to occur during the sleep process, an early warning is performed through an early warning device.
10. The method of extracting a respiratory state based on a radar signal of claim 1, further comprising: and sending the real-time breathing state information to a monitoring terminal through a network or Bluetooth and displaying the real-time breathing state information.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114732391A (en) * | 2022-06-13 | 2022-07-12 | 亿慧云智能科技（深圳）股份有限公司 | Microwave radar-based heart rate monitoring method, device and system in sleep state |
| CN116098602A (en) * | 2023-01-16 | 2023-05-12 | 中国科学院软件研究所 | Non-contact sleep respiration monitoring method and device based on IR-UWB radar |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103006223A (en) * | 2012-12-13 | 2013-04-03 | 中国人民解放军第四军医大学 | Household non-contact sleeping monitoring device and method |
| CN105962890A (en) * | 2015-12-06 | 2016-09-28 | 宣建民 | Sleep monitor |
| KR101836761B1 (en) * | 2017-01-04 | 2018-03-08 | 조선대학교산학협력단 | Apparatus for non-contact respiration detection using radar and method thereof |
| CN108065916A (en) * | 2017-12-14 | 2018-05-25 | 中国人民解放军国防科技大学 | Non-contact sleep quality monitoring method based on biological radar |
| CN108392186A (en) * | 2018-04-19 | 2018-08-14 | 广西欣歌拉科技有限公司 | A kind of Non-contact type sleep apnea disease detection method and system |
| CN111568417A (en) * | 2020-06-01 | 2020-08-25 | 浙江大学 | Non-contact type respiration real-time monitoring method |
-
2021
- 2021-12-14 CN CN202111526404.0A patent/CN114176564B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103006223A (en) * | 2012-12-13 | 2013-04-03 | 中国人民解放军第四军医大学 | Household non-contact sleeping monitoring device and method |
| CN105962890A (en) * | 2015-12-06 | 2016-09-28 | 宣建民 | Sleep monitor |
| KR101836761B1 (en) * | 2017-01-04 | 2018-03-08 | 조선대학교산학협력단 | Apparatus for non-contact respiration detection using radar and method thereof |
| CN108065916A (en) * | 2017-12-14 | 2018-05-25 | 中国人民解放军国防科技大学 | Non-contact sleep quality monitoring method based on biological radar |
| CN108392186A (en) * | 2018-04-19 | 2018-08-14 | 广西欣歌拉科技有限公司 | A kind of Non-contact type sleep apnea disease detection method and system |
| CN111568417A (en) * | 2020-06-01 | 2020-08-25 | 浙江大学 | Non-contact type respiration real-time monitoring method |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114732391A (en) * | 2022-06-13 | 2022-07-12 | 亿慧云智能科技（深圳）股份有限公司 | Microwave radar-based heart rate monitoring method, device and system in sleep state |
| CN114732391B (en) * | 2022-06-13 | 2022-08-23 | 亿慧云智能科技（深圳）股份有限公司 | Microwave radar-based heart rate monitoring method, device and system in sleep state |
| US11793415B1 (en) | 2022-06-13 | 2023-10-24 | Yihuiyun Intelligent Technology (Shenzhen) Co., Ltd. | Method, apparatus and system for monitoring heart rate in sleep state based on microwave radar |
| CN116098602A (en) * | 2023-01-16 | 2023-05-12 | 中国科学院软件研究所 | Non-contact sleep respiration monitoring method and device based on IR-UWB radar |
| CN116098602B (en) * | 2023-01-16 | 2024-03-12 | 中国科学院软件研究所 | Non-contact sleep respiration monitoring method and device based on IR-UWB radar |
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