Method and apparatus for one second forced expiratory volume measurement based on millimeter wave radar

Abstract

The embodiment of the present application provides a kind of one second forced expiratory volume measurement method and device based on millimeter wave radar, the method comprises: using millimeter wave radar to collect echo data of human body for lung function test;Respiration signal is extracted from the echo data, and signal segment of forced expiratory process is intercepted from the respiration signal;Key point is sought in the signal segment of forced expiratory process, and the relative value of forced vital capacity and the relative value of one second amount are calculated based on the key point;Based on the relative value of forced vital capacity, the relative value of one second amount and body feature data, the one second forced expiratory volume of human body is calculated.In the embodiment of the present application, the characteristics that the cost of millimeter wave radar is low, the volume is small, does not invade privacy, by receiving echo signal reflected from human body, the motion condition of human body surface can be non-contact sensed, low cost, convenient, non-contact measurement of one second forced expiratory volume of human body is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of radar signal processing and biomedical engineering processing, and particularly relates to a forced expiratory volume in one second measurement method and device based on a millimeter wave radar. BACKGROUND

[0002] Pulmonary function test is one of the necessary tests in the diagnosis of respiratory diseases. By detecting the patency of the respiratory tract and the size of the lung capacity, the type of lung and airway lesions can be judged, and the severity of the disease can be evaluated, which has important guiding significance for the diagnosis and treatment of respiratory diseases. Forced expiratory volume in one second (FEV1) and forced vital capacity (FVC) are important indicators in pulmonary function test. FEV1, also known as one-second volume, is mainly used for judging the severity of the disease.

[0003] At present, the gold standard pulmonary function detector used in hospitals is expensive and needs to be operated by professional technicians. It is a contact type and requires the testee to hold the mouth to test, which is very inconvenient to use and is not conducive to long-term monitoring of pulmonary function outside the hospital. Therefore, there is an urgent need for a low-cost, more convenient non-contact forced expiratory volume in one second measurement method. SUMMARY

[0004] In view of the above problems, the embodiments of the present application provide a forced expiratory volume in one second measurement method and device based on a millimeter wave radar, so as to overcome the above problems or at least partially solve the above problems.

[0005] In a first aspect, the embodiments of the present application disclose a forced expiratory volume in one second measurement method based on a millimeter wave radar, which comprises the following steps:

[0006] Collecting echo data of a human body for pulmonary function test by using a millimeter wave radar;

[0007] Extracting a breathing signal from the echo data, and intercepting a signal segment of a forced expiratory process from the breathing signal;

[0008] Finding a key point in the signal segment of the forced expiratory process, and calculating a relative value of forced vital capacity and a relative value of one-second volume based on the key point;

[0009] Calculating the forced expiratory volume in one second of the human body based on the relative value of forced vital capacity, the relative value of one-second volume, and body feature data, wherein the body feature data comprises height, weight, body mass index and gender.

[0010] Optionally, the echo data collected by the millimeter wave radar for the lung function test of the human body comprises:

[0011] The millimeter wave radar is controlled to emit a frequency-modulated continuous wave signal to obtain an echo signal for the lung function test of the human body.

[0012] The echo signal is mixed with the frequency-modulated continuous wave signal to obtain a difference frequency signal.

[0013] The difference frequency signal is sequentially subjected to high-pass filtering, low-noise amplification, and ADC sampling processing to obtain echo data.

[0014] Optionally, the breathing signal is extracted from the echo data, comprising:

[0015] The echo data is subjected to FFT transformation to obtain a distance-dimension complex signal.

[0016] An original phase signal containing human respiratory motion information is extracted from the distance-dimension complex signal.

[0017] The original phase signal is subjected to unwrapping operation to obtain a breathing signal.

[0018] Optionally, the original phase signal containing human respiratory motion information is extracted from the distance-dimension complex signal, comprising:

[0019] Static clutter in the distance-dimension complex signal is removed along the frame time dimension to obtain a distance-dimension complex signal from which static clutter is removed.

[0020] In the distance-dimension complex signal from which static clutter is removed, a point with the strongest power within a time range of the lung function test is searched along the distance dimension.

[0021] A distance gate preceding the distance gate corresponding to the point with the strongest power is selected as a breathing signal selection distance gate.

[0022] A phase angle of the breathing signal selection distance gate in the distance-dimension complex signal corresponding to each period Chirp is extracted to obtain an original phase signal containing human respiratory motion information.

[0023] Optionally, the key point is searched in the signal segment of the forced exhalation process, comprising:

[0024] The signal segment of the forced exhalation process is subjected to Gaussian smoothing processing to obtain a smoothed signal segment of the forced exhalation process.

[0025] For all minimum values within the first N seconds of the smoothed signal segment of the forced exhalation process, a maximum value most adjacent to each minimum value is found, and an amplitude difference value between the minimum value and the maximum value is calculated.

[0026] selecting a minimum point corresponding to the maximum amplitude difference as the forced expiration starting point;

[0027] finding a maximum point in a signal segment of the forced expiration process within M seconds after the forced expiration starting point, wherein the M seconds are determined according to the human expiration time.

[0028] Optionally, the finding of the maximum point in the signal segment of the forced expiration process within the M seconds after the forced expiration starting point comprises:

[0029] finding an initial maximum value in the signal segment of the forced expiration process within the M seconds after the forced expiration starting point;

[0030] performing median filtering in a preset range with the initial maximum value point as the center to eliminate burrs in the signal segment of the forced expiration process;

[0031] determining a maximum point in the signal segment of the forced expiration process within the M seconds after the forced expiration starting point after the median filtering.

[0032] Optionally, the calculating of the relative value of forced vital capacity and the relative value of one-second volume based on the key point comprises:

[0033] subtracting the thoracic displacement corresponding to the forced expiration starting point from the thoracic displacement corresponding to the maximum value point to obtain the relative value of forced vital capacity;

[0034] calculating the thoracic displacement within one second with J points after the forced expiration starting point as the starting point respectively, and determining the thoracic displacement within the maximum one second as the relative value of one-second volume.

[0035] Optionally, the calculating of the one-second forced expiration volume of the human body based on the relative value of forced vital capacity, the relative value of one-second volume, and the body feature data comprises:

[0036] combining the relative value of forced vital capacity, the relative value of one-second volume, and the body feature data, and using a pre-trained radar one-second volume index nonlinear fitting formula to calculate a radar one-second volume index, the radar one-second volume index representing the one-second forced expiration volume of the human body.

[0037] Optionally, the radar one-second volume index nonlinear fitting formula FEV1 is expressed as:

[0038]

[0039] wherein a, b, c, d, e, and f are fitting parameters determined by training, FEV1 is the relative value of one-second volume, FVC is the relative value of forced vital capacity, and V1 is the radar one-second volume index. RELThe forced vital capacity is a relative value, the BMI is a body mass index, the Height is a height, the Weight is a weight, the BMI is a body mass index, and the Sex is a gender.

[0040] In a second aspect, the application discloses a one-second forced expiratory volume measuring device based on a millimeter wave radar, which comprises:

[0041] A data acquisition module is configured to acquire echo data of a human body for a lung function test by using the millimeter wave radar.

[0042] A signal extraction module is configured to extract a breathing signal from the echo data and extract a signal segment of a forced expiratory process from the breathing signal.

[0043] A relative value calculation module is configured to find a key point in the signal segment of the forced expiratory process, and calculate a relative value of forced vital capacity and a relative value of one-second volume based on the key point.

[0044] A one-second volume calculation module is configured to calculate a one-second forced expiratory volume of the human body based on the relative value of forced vital capacity, the relative value of one-second volume and body feature data, wherein the body feature data comprises a height, a weight, a body mass index and a gender.

[0045] The application has the following advantages:

[0046] In the application, the millimeter wave radar has the advantages of low cost, small size and non-invasion of privacy, and can non-contact perceive the motion of the surface of the human body by receiving the echo signal reflected by the human body. A method for measuring the one-second forced expiratory volume based on the millimeter wave radar is provided. The echo data of the human body for the lung function test is acquired by using the millimeter wave radar, the breathing signal is extracted from the echo data, and the signal segment of the forced expiratory process is extracted. Then, the key point in the signal segment of the forced expiratory process is found, and the relative value of forced vital capacity and the relative value of one-second volume are calculated based on the key point. Finally, the one-second forced expiratory volume of the human body is calculated based on the relative value of forced vital capacity, the relative value of one-second volume and the body feature data. Thus, the one-second forced expiratory volume of the human body can be measured at low cost, conveniently and non-contact. BRIEF DESCRIPTION OF DRAWINGS

[0047] In order to more clearly illustrate the technical solutions of the embodiments of the application, the following will briefly introduce the drawings needed to be used in the description of the embodiments of the application. Obviously, the drawings in the following description are only some embodiments of the application, and other drawings can be obtained by those skilled in the art without any creative labor.

[0048] Figure 1A one-second forced expiratory volume measurement method based on a millimeter wave radar is provided in the embodiment of the present application.

[0049] Figure 2 A signal segment example of a forced expiratory process is provided in the embodiment of the present application.

[0050] Figure 3 A data acquisition scene diagram of a millimeter wave radar and a lung function instrument is provided in the embodiment of the present application.

[0051] Figure 4 A one-second forced expiratory volume measurement device structure schematic diagram based on a millimeter wave radar is provided in the embodiment of the present application. DETAILED DESCRIPTION

[0052] In order to make the above objectives, characteristics and advantages of the present application more apparent, clear and easy to understand, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0053] A one-second forced expiratory volume measurement method based on a millimeter wave radar is provided in the embodiment of the present application. Figure 1 As shown in Figure 1 A one-second forced expiratory volume measurement method based on a millimeter wave radar is provided in the embodiment of the present application, which comprises steps S101 to S104.

[0054] Step S101: collecting echo data of a human body for a lung function test by using a millimeter wave radar.

[0055] In the embodiment, when the lung function test is performed, the tested person sits upright on a chair with a backrest, the back is attached to the backrest, and the hands are naturally placed on both sides. Under the guidance of medical staff, the hospital's lung function test is accepted. At the same time, the millimeter wave radar is placed at a distance of about 75 cm from the tested person, and the height is as level as possible with the chest of the tested person, so as to ensure that the beam direction of the radar is directly opposite to the chest of the tested person.

[0056] The exhalation test process related to one-second measurement in the whole lung function test in the hospital includes: the subject normally breathes, then inhales deeply under the instruction of the medical staff, exhales as fast as possible after inhaling, inhales as fast as possible after exhaling, and finally normally breathes. The above process can be summarized as five parts: normal breathing, deep inhalation, forced exhalation, forced inhalation and normal breathing. The echo data collected by the millimeter wave radar for the human body for lung function test refers to the echo data collected according to the above exhalation test process. In addition, the subject is required to keep other parts of the body as stable as possible during the collection process, and the height, weight, gender data and other body characteristic data of the subject are recorded.

[0057] In an optional embodiment, the echo data collected by the millimeter wave radar for the human body for lung function test includes:

[0058] The millimeter wave radar transmits a frequency-modulated continuous wave signal to obtain an echo signal for human lung function test; the echo signal is mixed with the frequency-modulated continuous wave signal to obtain a beat signal; the beat signal is sequentially subjected to high-pass filtering, low-noise amplification and ADC sampling processing to obtain echo data.

[0059] In this embodiment, the millimeter wave radar transmits a frequency-modulated continuous wave signal, which can be a sawtooth signal. This signal has a linear increase in frequency over time within one period, which is called a Chirp. When the frequency-modulated continuous wave signal transmitted by the millimeter wave radar reaches the human chest cavity, it produces a reflection, i.e. an echo signal for human lung function test. After receiving the echo signal, the radar mixes the echo signal with the transmitted frequency-modulated continuous wave signal to obtain a beat signal. The beat signal is a continuously changing signal. Finally, by performing high-pass filtering and low-noise amplification on the beat signal, noise interference in the beat signal can be effectively removed. Then, through ADC (Analog-to-Digital Converter) sampling processing, the continuously changing beat signal is converted into a discrete digital signal, i.e. echo data. The echo data contains multiple Chirp-received echo signals.

[0060] Step S102: Extract a breathing signal from the echo data, and cut out a signal segment of the forced exhalation process from the breathing signal.

[0061] In this embodiment, the breathing signal refers to the breathing signal in the whole test process, i.e. the breathing signal including normal breathing, deep inhalation, forced exhalation, forced inhalation and normal breathing.

[0062] Specifically, the extraction of the breathing signal from the echo data includes steps A1 to A3:

[0063] Step A1: performing FFT transform on the echo data to obtain a range-dimension complex signal.

[0064] In this embodiment, the FFT transform (Fast Fourier Transform) can transform the signal from the time domain to the frequency domain. Specifically, performing FFT transform on the echo data to obtain a range-dimension complex signal includes: performing FFT transform on the echo signal received in each Chirp in the echo data, thereby obtaining a range-dimension complex signal corresponding to each Chirp. The range-dimension complex signal is a signal with frequency as the horizontal axis and the amplitude corresponding to each frequency as the vertical axis, and the frequency is related to the distance from the chest to the radar during the lung function test of the human body, and the range-dimension complex signal represents the relationship between the energy amplitude and the distance. When the human body is performing the lung function test, the distance from the chest to the radar is different, and the corresponding signal amplitude is different. If the distance from the chest to the radar is farther, the corresponding signal amplitude is smaller, and if the distance from the chest to the radar is smaller, the corresponding signal amplitude is larger.

[0065] Step A2: extracting an original phase signal containing human respiratory motion information from the range-dimension complex signal.

[0066] In this embodiment, the original phase signal containing human respiratory motion information means that the phase signal is related to the displacement of the chest during the lung function test of the human body. Specifically, the extraction of the original phase signal containing human respiratory motion information from the range-dimension complex signal includes: removing static clutter in the range-dimension complex signal along the frame time dimension to obtain a range-dimension complex signal with static clutter removed; finding the point with the strongest power in the range-dimension complex signal with static clutter removed along the distance dimension within the time range of the lung function test; selecting the distance gate corresponding to the point with the strongest power as the respiratory signal selection distance gate; extracting the phase angle of the selected distance gate in the range-dimension complex signal corresponding to each period Chirp to obtain the original phase signal containing human respiratory motion information.

[0067] Step A3: performing unwrapping operation on the original phase signal to obtain a respiratory signal.

[0068] In this embodiment, since the original phase signal is a signal from 0 to 2π, when the displacement of the chest is relatively long with respect to the wavelength, the actual phase signal corresponding to the displacement of the chest may exceed the range from 0 to 2π, and there is a jump in the original phase signal. In order to facilitate analysis and calculation, the original phase signal is subjected to unwrapping operation, that is, the phase signal with sudden change is restored to obtain a respiratory signal. The respiratory signal is a signal with time as the horizontal axis and phase as the vertical axis, and the phase value represents the displacement of the chest during the lung function test.

[0069] For example, when the actual chest displacement corresponds to a phase signal of 3π, but since the original phase signal ranges from 0 to 2π, the phase signal cannot rise after 2π and directly jumps to 0 and then rises to π. The unwrapping operation adds the phase value π of the sudden change to 2π to obtain the phase value of 3π.

[0070] In the embodiment, the respiratory signal is a phase signal that changes over time. Since the chest displacement ranges differently during normal breathing, deep inhalation, forced exhalation, forced inhalation, and normal breathing, i.e., the corresponding phase signal values in the respiratory signal are different. For example, the chest displacement between normal exhalation and forced exhalation is different, and the corresponding phase values are also different. Therefore, according to the change of the phase in the respiratory signal, the signal segment of the forced exhalation process is intercepted from the respiratory signal. As shown in Figure 2 Figure 2 The signal segment is the signal segment of the forced exhalation process, and the phase value (chest displacement) changes over time during the forced exhalation process.

[0071] Step S103: finding a key point in the signal segment of the forced exhalation process, and calculating a relative value of forced vital capacity and a relative value of one-second volume based on the key point.

[0072] In the embodiment, the key points include a starting point of forced exhalation and a maximum point, where the maximum point refers to a point with the maximum phase value in the signal segment of the forced exhalation process, as shown in Figure 2

[0073] In an alternative embodiment, the step of finding a key point in the signal segment of the forced exhalation process includes steps B1 to B4:

[0074] Step B1: performing Gaussian smoothing on the signal segment of the forced exhalation process to obtain a smoothed signal segment of the forced exhalation process.

[0075] In the embodiment, Gaussian smoothing is performed on the signal segment of the forced exhalation process to further remove the noise in the signal and make the signal of the forced exhalation process smoother. Thus, the key points obtained in the subsequent steps are more accurate.

[0076] Step B2: for all minimum values in the first N seconds of the smoothed signal segment of the forced exhalation process, finding the nearest maximum value after each minimum value and calculating the amplitude difference between the minimum value and the maximum value.

[0077] For example, the smoothed signal segment of the forced exhalation process is denoted as φ[n], and for all minimum values φ[q i ​​], find the nearest maximum value φ[p i ], the amplitude difference Δh between each minimum value and the maximum value i , is expressed as:

[0078] Δh i = [p i ]-[q i ], i = 1, 2, …, N s

[0079] where N s is the number of minimum points.

[0080] Step B3: Select the minimum point corresponding to the maximum amplitude difference as the forced expiration starting point.

[0081] For example, select the minimum point corresponding to the index i that makes the amplitude difference maximum as the forced expiration starting point q start , that is:

[0082] q start = m , m = argmax i Δh i , i = 1, 2, …, N s

[0083] where argmax i Δh i represents finding the maximum amplitude difference in all amplitude differences Δh i , i = 1, 2, …, N s , and m is the index corresponding to the maximum amplitude difference.

[0084] In addition, after determining the forced expiration starting point q start , if the signal appears a continuous decrease amplitude greater than π in the process of the signal rising (i.e. the forced expiration process), it is considered that there is a body motion interference. Then, the signal segment after the starting point of the decrease is added with the decrease amplitude value, so as to realize the correction of the forced expiration process signal, and further improve the accuracy of the forced expiration signal.

[0085] Step B4: Find a maximum point in the forced expiration process signal segment within M seconds after the forced expiration starting point, where the M seconds are determined according to the human expiration length.

[0086] In this embodiment, the maximum point refers to the point corresponding to the maximum phase value in the forced expiration signal segment. M is determined according to the human expiration length, and M should be greater than the normal expiration length. For a person with a longer expiration time, the corresponding search range is larger, i.e. the corresponding M should be larger. For example, if the expiration length is 6 seconds, M can be set to 8.

[0087] Specifically, finding a maximum value point in the signal segment of the forced exhalation process within M seconds after the starting point of the forced exhalation includes: finding an initial maximum value in the signal segment of the forced exhalation process within M seconds after the starting point of the forced exhalation; performing median filtering within a preset range with the initial maximum value point as the center to eliminate spikes in the signal segment of the forced exhalation process; and determining a maximum value point in the signal segment of the forced exhalation process within M seconds after the starting point of the forced exhalation process after median filtering.

[0088] In this embodiment, by confirming the maximum value twice, interference from glitches in the signal is avoided, thus improving the accuracy of the maximum value.

[0089] In an optional embodiment, the calculation of the relative values ​​of forced vital capacity and force-in-one-second (FV) based on the key points includes steps C1 and C2:

[0090] Step C1: Subtract the chest cavity displacement corresponding to the starting point of forced exhalation from the chest cavity displacement corresponding to the maximum value point to obtain the relative value of the forced vital capacity.

[0091] In this embodiment, the signal during forced exhalation is a phase signal that varies over time. The phase value represents the displacement of the chest cavity during the human function test, with the maximum value point q... max Corresponding chest displacement minus the starting point of forced exhalation q start The corresponding chest cavity displacement, specifically the relative value of forced vital capacity (FVC). REL Represented as:

[0092] FVC REL =φ[q max ]-φ[q start ]

[0093] Step C2: For J points within one second after the start of the forced exhalation, calculate the chest cavity displacement within one second starting from each of the J points, and determine the maximum chest cavity displacement within one second as the relative value of the one-second quantity.

[0094] In this embodiment, the signal segment of the forced exhalation process is a discrete signal, for the forced exhalation starting point q start For J points within the last second, calculate the thoracic cavity displacement within one second, starting from each point. J is determined based on the Chirp sampling rate; for example, if the Chirp sampling rate is 500, then J equals 500.

[0095] For example, the thoracic cavity displacement Δd within one second, starting from each point. k It can be represented as:

[0096] Δd k =φ[qstart + f s - φ [q start + k], k = 0, 1,..., f s - 1

[0097] where f s is the Chirp sampling rate.

[0098] The maximum chest displacement within one second is determined as the relative value of one second volume FEV 1REL , i.e.

[0099] FEV 1REL = Δd a , a = arg max k Δd k , k = 0, 1,..., f s - 1

[0100] where arg max k Δd k represents finding the maximum chest displacement within one second from all chest displacements Δd k , k = 0, 1,..., f s - 1, and a is the index corresponding to the maximum chest displacement within one second.

[0101] In this embodiment, the key points are found in the signal segment of the forced expiration process, and the relative value of forced vital capacity and the relative value of one second volume are calculated based on the chest displacement corresponding to the key points. Then, in the subsequent steps, the one second forced expiration volume of the human body is calculated based on the relative value of forced vital capacity and the relative value of one second volume.

[0102] Step S104: calculating the one second forced expiration volume of the human body based on the relative value of forced vital capacity, the relative value of one second volume, and body feature data; wherein the body feature data includes height, weight, body mass index, and gender.

[0103] In this embodiment, considering that different people have different body types, the actual one second forced expiration volume of the human body cannot be reliably estimated only according to the relative value of one second volume (i.e. one second chest displacement) obtained in the above steps. Generally, people with larger BMI (Body Mass Index) have larger body size and chest volume, and the expiration volume may be larger under the same chest displacement. In addition, the chest volume may be different, i.e. the expiration volume may be different, for people with different height, weight, and gender. Therefore, the one second forced expiration volume of the human body is calculated by comprehensively considering the relative value of one second volume, the relative value of forced vital capacity, and the height, weight, BMI, and gender of the human body in the forced expiration process.

[0104] Specifically, in combination with the relative value of forced vital capacity, the relative value of the one-second volume, and the body feature data, a radar one-second volume index is calculated using a pre-trained radar one-second volume index nonlinear fitting formula, the radar one-second volume index representing the one-second forced expiratory volume of the human body.

[0105] For example, the radar one-second volume index nonlinear fitting formula FEV1 is expressed as:

[0106]

[0107] wherein a, b, c, d, e, and f are fitting parameters determined through training, FEV1 is the relative value of the one-second volume, FVC is the relative value of the forced vital capacity, BMI is the body mass index, Height is the height, Weight is the weight, BMI is the body mass index, and Sex is the gender, with Sex taking a value of 0 or 1 (0 representing male and 1 representing female). REL

[0108] In this embodiment, the radar one-second volume index nonlinear fitting formula comprehensively considers the relative value of the one-second volume in the forced expiratory process, the relative value of the forced vital capacity, and the height, weight, BMI, and gender of the subject, so that the one-second forced expiratory volume of the human body calculated is more accurate. In turn, low-cost, convenient, and non-contact measurement of the one-second forced expiratory volume of the human body is realized.

[0109] In an alternative embodiment, the radar one-second volume index nonlinear fitting formula is trained using the least square estimate method, and the values of the fitting coefficients a, b, c, d, e, and f are obtained after the training is completed. The reliability of the radar one-second volume index nonlinear fitting formula is verified on the verification data.

[0110] In order to verify the reliability of the one-second forced expiratory volume measurement method based on the millimeter wave radar provided in the present embodiment (i.e., to evaluate the clinical value of the radar one-second volume index), the data of the above expiratory test process of the subject are collected using both the lung function instrument and the millimeter wave radar, as shown in FIG. 1. Figure 3 The lung function instrument one-second volume index and the radar one-second volume index measured under the same experimental conditions are obtained, respectively, and consistency analysis is performed on a large amount of experimental data, and in turn, the clinical value of the radar one-second volume index is evaluated.

[0111] ​The forced expiratory volume in one second (FEV1) measured by the radar and the forced expiratory volume in one second (FEV1) measured by the pulmonary function instrument are compared, and the mean absolute error (MAE), the mean square error (MSE), and the interclass correlation coefficient (ICC) are calculated on a large amount of experimental data, that is,

[0112]

[0113]

[0114]

[0115]

[0116]

[0117] wherein n is the total number of forced expiratory segments collected. The MAE and the MSE can reflect the error of the forced expiratory volume in one second measured by the radar and the forced expiratory volume in one second measured by the pulmonary function instrument, and the ICC can reflect the consistency of the measurement results of the radar and the pulmonary function instrument.

[0118] Specifically, all the forced expiratory segments are divided into training data and verification data at a ratio of 3:1, the coefficients of the forced expiratory volume in one second measured by the radar are determined by using the least square fitting on the training data, and the reliability of the forced expiratory volume in one second measured by the radar is verified on the verification data. The leave-P method is used for cross-validation, and the MAE, the MSE, and the ICC on the training data and the verification data under cross-validation are calculated, which are used as the standards for measuring the consistency of the forced expiratory volume in one second measured by the radar and the pulmonary function instrument and the measurement accuracy of the radar.

[0119] As shown in Table 1, the training set and the verification set are divided at a ratio of 3:1 on the data set, 10000 times of cross-validation are performed, and the indexes are obtained.

[0120] Table 1 Indexes of the training set and the verification set

[0121]

[0122] As shown in Table 1, under cross-validation, the ICC of the forced expiratory volume in one second measured by the radar and the forced expiratory volume in one second measured by the pulmonary function instrument on the training set and the verification set is 0.7915 and 0.7597 respectively, which indicates that the measurement results of the two devices have high consistency, verifies the reliability of the proposed forced expiratory volume in one second fitting formula of the radar, and has potential clinical value.

[0123] In the embodiment, the cost of the millimeter wave radar is low, the volume is small, privacy is not invaded, and the motion condition of the surface of the human body can be non-contact sensed by receiving the echo signal reflected from the human body; a method for measuring the forced expiratory volume in one second based on the millimeter wave radar is provided, first, the echo data of the human body for the lung function test is collected by using the millimeter wave radar, the breathing signal is extracted from the echo data, and the signal segment of the forced expiration process is intercepted, then the key points are searched in the signal segment of the forced expiration process, and the relative value of the forced vital capacity and the relative value of the one-second volume are calculated from the key points, finally, based on the relative value of the forced vital capacity, the relative value of the one-second volume, and the body feature data, the forced expiratory volume in one second of the human body is calculated; and the forced expiratory volume in one second of the human body is measured at low cost, conveniently and non-contact.

[0124] The embodiment of the present application provides a forced expiratory volume in one second measurement device based on a millimeter wave radar, as shown in Figure 4 The forced expiratory volume in one second measurement device based on the millimeter wave radar provided by the embodiment of the present application is a structure schematic diagram, and the device comprises: Figure 4 The forced expiratory volume in one second measurement device based on the millimeter wave radar provided by the embodiment of the present application is a structure schematic diagram, and the device comprises:

[0125] The data acquisition module 41 is used for collecting the echo data of the human body for the lung function test by using the millimeter wave radar;

[0126] The signal extraction module 42 is used for extracting the breathing signal from the echo data, and intercepting the signal segment of the forced expiration process from the breathing signal;

[0127] The relative value calculation module 43 is used for searching the key points in the signal segment of the forced expiration process, and calculating the relative value of the forced vital capacity and the relative value of the one-second volume based on the key points;

[0128] The one-second volume calculation module 44 is used for calculating the forced expiratory volume in one second of the human body based on the relative value of the forced vital capacity, the relative value of the one-second volume, and the body feature data; wherein the body feature data comprises height, weight, body mass index and gender.

[0129] In an optional embodiment, the data acquisition module comprises:

[0130] The signal transmission module is used for controlling the millimeter wave radar to transmit the frequency-modulated continuous wave signal, so as to obtain the echo signal of the human lung function test;

[0131] The frequency mixing processing module is used for mixing the echo signal with the frequency-modulated continuous wave signal to obtain the difference frequency signal;

[0132] A signal filtering module is configured to sequentially perform high-pass filtering, low-noise amplification and ADC sampling processing on the difference frequency signal to obtain echo data.

[0133] In an alternative embodiment, the signal extraction module comprises:

[0134] A signal change module is configured to perform FFT transformation on the echo data to obtain a distance-dimension complex signal.

[0135] A phase extraction module is configured to extract an original phase signal containing human respiratory motion information from the distance-dimension complex signal.

[0136] A phase unwrapping module is configured to perform unwrapping operation on the original phase signal to obtain a respiratory signal.

[0137] In an alternative embodiment, the phase extraction module comprises:

[0138] A first phase extraction submodule is configured to remove static clutter in the distance-dimension complex signal along a frame time dimension to obtain a distance-dimension complex signal from which static clutter is removed.

[0139] A second phase extraction submodule is configured to find a point with the strongest power in a lung function test process time range in the distance-dimension complex signal from which static clutter is removed along a distance dimension.

[0140] A third phase extraction submodule is configured to select a distance gate preceding a distance gate corresponding to the point with the strongest power as a respiratory signal selection distance gate.

[0141] A fourth phase extraction submodule is configured to extract a phase angle of the respiratory signal selection distance gate in a distance-dimension complex signal corresponding to each period Chirp to obtain an original phase signal containing human respiratory motion information.

[0142] In an alternative embodiment, the relative value calculation module comprises:

[0143] A Gaussian smoothing module is configured to perform Gaussian smoothing processing on the signal segment of the forced expiration process to obtain a smoothed signal segment of the forced expiration process.

[0144] An amplitude calculation module is configured to find a maximum value closest to each minimum value in the first N seconds of the smoothed signal segment of the forced expiration process, and calculate an amplitude difference value between the each minimum value and the maximum value.

[0145] A minimum value determination module is configured to select a minimum value point corresponding to the maximum amplitude difference value as a forced expiration starting point.

[0146] A maximum value determining module is configured to find a maximum value point in a signal segment of the forced expiration process within M seconds after the forced expiration starting point, wherein the M seconds are determined according to the human expiration time length.

[0147] In an alternative embodiment, the maximum value determining module comprises:

[0148] A first maximum value submodule is configured to find an initial maximum value in the signal segment of the forced expiration process within M seconds after the forced expiration starting point, and perform median filtering in a preset range with the initial maximum value point as the center to eliminate burrs in the signal segment of the forced expiration process.

[0149] A second maximum value submodule is configured to determine a maximum value point in the signal segment of the forced expiration process within M seconds after the forced expiration starting point after the median filtering.

[0150] In an alternative embodiment, the relative value calculating module comprises:

[0151] A first relative value module is configured to subtract the thoracic displacement corresponding to the forced expiration starting point from the thoracic displacement corresponding to the maximum value point to obtain the relative value of the forced vital capacity.

[0152] A second relative value module is configured to calculate the thoracic displacement within one second with J points as the starting points respectively, and determine the thoracic displacement within the maximum one second as the relative value of the one-second volume.

[0153] In an alternative embodiment, the one-second volume calculating module comprises:

[0154] A fitting module is configured to combine the relative value of the forced vital capacity, the relative value of the one-second volume, and the body feature data, and calculate the radar one-second volume index by using a pre-trained nonlinear fitting formula, wherein the radar one-second volume index represents the one-second forced expiration volume of the human body.

[0155] Each of the embodiments in the specification is described in a progressive manner, and each embodiment focuses on the difference from other embodiments. The same or similar parts between the embodiments can be referred to each other.

[0156] Each of the embodiments in the specification is described in a progressive manner, and each embodiment focuses on the difference from other embodiments. The same or similar parts between the embodiments can be referred to each other.

[0157] The embodiments of the present application are described with reference to the flowchart illustrations and / or block diagrams of the methods and apparatuses according to the embodiments of the present application. It is understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processing unit, or other programmable data processing terminal devices to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal devices, create means for implementing the functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more of the flowcharts and / or block diagrams. Figure 1 one or more of the flowcharts and / or block diagrams.

[0158] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing terminal devices to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the function specified in the flowcharts and / or block diagrams. Figure 1 one or more of the flowcharts and / or block diagrams. Figure 1 one or more of the flowcharts and / or block diagrams.

[0159] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal devices, such that a series of operational steps are carried out on the computer or other programmable terminal devices to produce a computer implemented process so that the instructions executed on the computer or other programmable terminal devices provide steps for implementing the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more of the flowcharts and / or block diagrams. Figure 1 one or more of the flowcharts and / or block diagrams.

[0160] Although preferred embodiments of the present application have been described, those skilled in the art will be able to make additional modifications and variations to the embodiments without departing from the scope of the present application. Accordingly, the appended claims are intended to encompass all such modifications and variations as falling within the scope of the embodiments of the present application.

[0161] Finally, it is to be understood that the phraseology or terminology such as "first" and "second" etc. used herein is merely intended to differentiate one entity or operation from another entity or operation, without necessarily requiring or implying any actual such relationship or order between such entities or operations. Moreover, the terms "comprising", "including", or any other closure, are intended to cover the non-exclusive inclusion such that a process, method, article, or apparatus that comprises a list of elements does not include those elements alone but can include other elements not expressly listed or even include elements inherent in such process, method, article, or apparatus. Without more limitations, the element defined by the statement "comprising a" does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0162] The above describes in detail the method and device for measuring one second forced expiratory volume based on millimeter wave radar provided by the present application. The principle and implementation mode of the present application are described by applying specific examples. The above description of the examples is only used to help understand the method of the present application and its core idea. Meanwhile, for those skilled in the art, the specific implementation mode and application range will be changed according to the idea of the present application. In summary, the content of the specification should not be understood as a limitation of the present application.

Claims

1. A method for measuring forced expiratory volume in one second based on millimeter-wave radar, characterized in that, The method includes: Millimeter-wave radar is used to collect echo data of human lung function tests; The respiratory signal is extracted from the echo data, and a signal segment of the forceful exhalation process is extracted from the respiratory signal. Find key points in the signal segment of the forced exhalation process, and calculate the relative values ​​of forced vital capacity and volume in one second based on the key points; Based on the relative value of the forced vital capacity, the relative value of the volume per second, and the body characteristic data, the forced expiratory volume per second of a human body is calculated; wherein, the body characteristic data includes: height, weight, body mass index, and gender; The calculation of the forced expiratory volume per second (FEAV) based on the relative value of the forced vital capacity, the relative value of the volume per second, and body characteristic data includes: Combining the relative values ​​of forced vital capacity, the relative values ​​of the volume per second (VPC), and body characteristic data, the radar VPC index is calculated using a pre-trained nonlinear fitting formula. The radar VPC index represents the forced expiratory volume in one second (FEV1) of the human body. The nonlinear fitting formula for the radar VPC index is expressed as follows: Where a, b, c, d, e, and f are the fitting parameters determined during training, and FEV 1 REL FVC is a relative value for a time in one second. REL Forced lung capacity is a relative value; BMI is body mass index; Height is height; Weight is weight; and Sex is gender.

2. The method according to claim 1, characterized in that, The method of using millimeter-wave radar to collect echo data for lung function testing of the human body includes: Control the millimeter-wave radar to transmit frequency-modulated continuous wave signals in order to obtain echo signals from human lung function tests; The echo signal is mixed with the frequency-modulated continuous wave signal to obtain the difference frequency signal; The difference frequency signal is sequentially subjected to high-pass filtering, low-noise amplification, and ADC sampling to obtain echo data.

3. The method according to claim 1, characterized in that, Extracting the respiratory signal from the echo data includes: Perform an FFT transform on the echo data to obtain a distance-dimensional complex signal; Extract the original phase signal containing human respiratory motion information from the distance-dimensional complex signal; The original phase signal is unwound to obtain the breathing signal.

4. The method according to claim 3, characterized in that, Extracting the original phase signal containing human respiratory motion information from the distance-dimensional complex signal includes: Static clutter is removed from the range dimension complex signal along the frame time dimension to obtain a range dimension complex signal with static clutter removed. In the distance dimension complex signal after removing static clutter, find the point of strongest power within the time range of the lung function test process; Select the distance gate preceding the distance gate corresponding to the point of strongest power as the breathing signal selection distance gate; The phase angle of the distance gate is selected from the distance dimension complex signal corresponding to each cycle Chirp to obtain the original phase signal containing human respiratory motion information.

5. The method according to claim 1, characterized in that, Finding key points in the signal segment during the forced exhalation process includes: Gaussian smoothing was applied to the signal segment of the forced exhalation process to obtain a smoothed signal segment of the forced exhalation process. For all the minimum values ​​in the first N seconds of the signal segment of the smoothed forced exhalation process, find the nearest maximum value after each minimum value, and calculate the amplitude difference between each minimum value and the maximum value; Choose the minimum point corresponding to the largest amplitude difference as the starting point of forced exhalation; Find a maximum value point in the signal segment of the forced exhalation process within M seconds after the start point of the forced exhalation, where M seconds is determined according to the duration of human exhalation.

6. The method according to claim 5, characterized in that, Finding a maximum value point in the signal segment of the forced exhalation process within M seconds after the start of the forced exhalation includes: Find an initial maximum value in the signal segment of the forced exhalation process within M seconds after the start point of the forced exhalation; Centered on the initial maximum value point, median filtering is performed within a preset range to eliminate spikes in the signal segment of the forced exhalation process; Determine a maximum value point within a segment of the forced exhalation process within M seconds after the starting point of the forced exhalation, which has been filtered by median.

7. The method according to claim 1, characterized in that, The calculation of the relative values ​​of forced vital capacity and volume per second based on the key points includes: Subtract the chest displacement corresponding to the starting point of forced exhalation from the chest displacement corresponding to the maximum value point to obtain the relative value of the forced vital capacity. For J points within one second after the start of the forced exhalation, calculate the chest cavity displacement within one second starting from each of the J points, and determine the maximum chest cavity displacement within one second as the relative value of the one-second quantity.

8. A device for measuring forced expiratory volume per second based on millimeter-wave radar, characterized in that, The device includes: The data acquisition module is used to collect echo data of human lung function tests using millimeter-wave radar; The signal extraction module is used to extract the respiratory signal from the echo data and extract the signal segment of the forceful exhalation process from the respiratory signal. The relative value calculation module is used to find key points in the signal segment of the forced exhalation process and calculate the relative value of forced vital capacity and the relative value of one-second volume based on the key points. The one-second volume calculation module is used to calculate the forced expiratory volume in one second (FEV1) of a human body based on the relative value of the forced vital capacity, the relative value of the one-second volume, and body characteristic data. The body characteristic data includes height, weight, body mass index, and gender. Combining the relative value of the forced vital capacity, the relative value of the one-second volume, and the body characteristic data, a pre-trained nonlinear fitting formula for the radar one-second index is used to calculate the radar one-second index. The radar one-second index represents the forced expiratory volume in one second of a human body, and the nonlinear fitting formula for the radar one-second index is expressed as follows: Where a, b, c, d, e, and f are the fitting parameters determined during training, and FEV 1 REL FVC is a relative value for a time in one second. REL Forced lung capacity is a relative value; BMI is body mass index; Height is height; Weight is weight; and Sex is gender.

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