A security control method and device based on terahertz wave detection of physiological parameters

Abstract

The present application provides a security inspection control method and device based on terahertz wave detection of physiological parameters. The method collects terahertz wave echo signals, measures the phase difference of the echo signals, and obtains an offset variation curve of the echo signals. The offset variation curve of the echo signals is decomposed to obtain echo offset components of different frequency bands and divide them into different component clusters. The frequency domain spectrum of the echo offset component with the largest correlation in each component cluster is used to extract the frequency measurement value of each type of security inspection physiological parameter, thereby obtaining the abnormality of the physiological parameter. The abnormality value of the physiological parameter is compared with a preset abnormality threshold to determine whether to conduct a security inspection on the inside of the target security inspection subject. This method can achieve more accurate physiological parameter detection using terahertz waves, and can quickly screen out target security inspection subjects with abnormal physiological parameters for body scanning inspection, thereby making it easier to detect whether contraband is hidden in the human body based on terahertz security inspection technology.

Description

Technical Field

[0001] The present application relates to the technical field of security inspection and control, and more specifically, to a security inspection and control method and device based on terahertz wave detection of physiological parameters. Background Art

[0002] In recent years, with the continuous improvement of public transportation infrastructure, the flow of people in public places such as airports, high-speed rail stations, and docks has also increased. Security inspection equipment must be installed in these places where people gather. However, traditional security inspection methods have many disadvantages, such as limited detection capabilities for non-metallic contraband, inability to detect special hidden items, and the need for a large number of security personnel to participate, resulting in low efficiency.

[0003] To address these issues, many public places with large traffic flow have chosen to use terahertz security inspection systems for security checks. Compared with traditional security inspection technologies, terahertz security inspection systems have a series of advantages, such as less damage to human functions, fast imaging and high resolution, strong detection capabilities for non-metallic materials, and fast detection speed. However, due to the poor penetration of terahertz waves into the human body, existing terahertz security inspection technologies cannot directly detect contraband hidden in the human body. How to more conveniently detect contraband hidden in the human body based on terahertz security inspection technology is a problem facing the industry. Summary of the Invention

[0004] The present application provides a security inspection control method and device based on terahertz wave detection of physiological parameters, so as to more easily detect whether contraband is hidden in the human body based on terahertz security inspection technology.

[0005] To solve the above technical problems, this application adopts the following technical solutions:

[0006] In a first aspect, the present application provides a security inspection and control method based on terahertz wave detection of physiological parameters, comprising the following steps:

[0007] Collecting a security inspection echo signal corresponding to the terahertz wave security inspection signal sent to the target security inspection object, performing echo phase difference measurement on the security inspection echo signal, and determining an offset change curve of the security inspection echo signal according to the result of the echo phase difference measurement;

[0008] Decomposing the offset variation curve of the security inspection echo signal to obtain echo offset components in different frequency bands, dividing the echo offset components into different component clusters according to the frequency bands in which the echo offset components are located, and determining the correlation between each echo offset component and the offset variation curve of the security inspection echo signal;

[0009] The echo offset component with the largest correlation in each component cluster is used as the physiological parameter signal of the target security inspection object, different types of security inspection physiological parameter frequency domain spectrograms are generated based on the physiological parameter signals of the target security inspection object, and security inspection frequency measurement values ​​from the different types of security inspection physiological parameter frequency domain spectrograms are respectively extracted to obtain security inspection frequency measurement values ​​of each type of security inspection physiological parameter;

[0010] Determine the difference coefficient between the security inspection frequency measurement value of each type of security inspection physiological parameter and the corresponding human standard physiological parameter, add each difference coefficient according to the corresponding weight coefficient to obtain the abnormality value of the security inspection physiological parameter;

[0011] The abnormality value of the security inspection physiological parameter is compared with a preset abnormality threshold. When the abnormality value of the security inspection physiological parameter is greater than the preset abnormality threshold, an early warning signal is issued and a body scanner is started to perform a security inspection on the inside of the body of the target security inspection object.

[0012] In some embodiments, determining the offset variation curve of the echo signal according to the phase difference measurement result specifically includes:

[0013] The phase tangent algorithm is used to obtain the linear change curve of phase information;

[0014] performing phase unwrapping on the phase information linear variation curve to obtain an echo phase signal;

[0015] An echo phase difference is obtained from the echo phase signal, and an offset variation curve of the security inspection echo signal is determined according to the echo phase difference.

[0016] In some embodiments, decomposing the offset variation curve of the security inspection echo signal to obtain echo offset components of different frequency bands specifically includes:

[0017] Analyzing the local maximum and local minimum of the offset variation curve of the security inspection echo signal;

[0018] Determine the upper envelope curve and the lower envelope curve according to the local maximum value and the local minimum value;

[0019] Adding the upper envelope curve and the lower envelope curve and dividing the sum by two to obtain an average envelope curve;

[0020] Subtracting the average envelope curve from the offset variation curve of the security inspection echo signal to obtain a transition curve signal;

[0021] The transition curve signal is tested, and if the transition curve signal satisfies both conditions of zero mean and local similarity of frequency, an echo offset component of a frequency band is obtained;

[0022] Decomposing the offset variation curve of the security inspection echo signal according to the determined echo offset component to obtain the offset variation curve of the next security inspection echo signal; determining the average envelope curve and transition curve signal of the offset variation curve of the next security inspection echo signal according to the above steps to obtain the echo offset component of the next frequency band;

[0023] Continue to perform decomposition according to the above steps until the standard deviation between the echo offset components is less than the preset standard deviation, and then end the decomposition.

[0024] In some embodiments, the correlation between each echo offset component and the offset variation curve of the security inspection echo signal is determined according to the following formula:

[0025]

[0026] in, represents the echo offset component, Indicates the offset of the echo signal, Indicates the correlation between the echo offset component and the offset of the echo signal, represents the covariance between the offset component of the echo and the offset of the echo signal, represents the standard deviation of the echo offset component, Indicates the standard deviation of the offset of the echo signal.

[0027] In some embodiments, the abnormality of the physiological parameters of the target security inspection object can be determined by the following formula:

[0028]

[0029] in, Indicates the abnormality of the physiological parameters of the target security inspection object, Indicates the weight coefficient of each physiological parameter, Indicates the difference coefficient between the security inspection frequency measurement value of each type of security inspection physiological parameter and the corresponding human standard physiological parameter.

[0030] In some embodiments, the terahertz wave security inspection signal sent to the target security inspection object is a linear frequency modulated continuous wave signal.

[0031] In some embodiments, the body scanner is an X-ray scanner.

[0032] In a second aspect, the present application provides a security inspection and control device for detecting physiological parameters based on terahertz waves, comprising:

[0033] An offset change curve determination module is used to collect a security inspection echo signal corresponding to a terahertz wave security inspection signal sent to a target security inspection object, perform echo phase difference measurement on the security inspection echo signal, and determine an offset change curve of the security inspection echo signal based on the result of the echo phase difference measurement;

[0034] a correlation determination module, configured to decompose the offset variation curve of the security inspection echo signal to obtain echo offset components in different frequency bands, divide the echo offset components into different component clusters based on the frequency bands in which the echo offset components are located, and determine the correlation between each echo offset component and the offset variation curve of the security inspection echo signal;

[0035] a security inspection frequency measurement value determination module, configured to use the echo offset component with the greatest correlation in each component cluster as the physiological parameter signal of the target security inspection subject, generate different types of security inspection physiological parameter frequency domain spectrograms based on the physiological parameter signals of the target security inspection subject, and extract the security inspection frequency measurement values ​​from the different types of security inspection physiological parameter frequency domain spectrograms to obtain the security inspection frequency measurement values ​​of each type of security inspection physiological parameter;

[0036] The physiological parameter abnormality value determination module is used to determine the difference coefficient between the security inspection frequency measurement value of each type of security inspection physiological parameter and the corresponding human standard physiological parameter, and add each difference coefficient according to the corresponding weight coefficient to obtain the abnormality value of the security inspection physiological parameter;

[0037] The security inspection control module is used to compare the abnormality value of the security inspection physiological parameter with a preset abnormality threshold. When the abnormality value of the security inspection physiological parameter is greater than the preset abnormality threshold, an early warning signal is issued and a body scanner is activated to perform a security inspection on the inside of the body of the target security inspection object.

[0038] In a third aspect, the present application provides a computer device comprising a memory and a processor, wherein the memory stores code, and the processor is configured to obtain the code and execute the above-mentioned security inspection and control method based on terahertz wave detection of physiological parameters.

[0039] In a fourth aspect, the present application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-mentioned security inspection and control method based on terahertz wave detection of physiological parameters.

[0040] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects:

[0041] In the security inspection control method and device based on terahertz wave detection of physiological parameters provided by the present application, the echo signal of the terahertz wave is first collected and the echo phase difference of the signal is measured, and the offset change curve of the echo signal is obtained from the result of the echo phase difference measurement; the offset change curve can be decomposed to obtain echo offset components of different frequency bands, and the echo offset components are divided into different component clusters according to the frequency band intervals, and the echo offset component with the largest correlation in each component cluster is extracted as the physiological parameter signal of the target security inspection object, and different types of physiological parameter frequency domain spectra are generated according to the physiological parameter signal of the target security inspection object and the frequency value of the physiological parameter frequency domain spectra is extracted; so that the security inspection device can According to the extracted frequency measurement value, the difference coefficient between the frequency measurement value of each physiological parameter and the corresponding standard physiological parameter of the human body is calculated, and the physiological parameter abnormality is obtained by adding the various difference coefficients according to the corresponding weight coefficients; thereby, the value of the physiological parameter abnormality is compared with the preset abnormality value. When the physiological parameter abnormality is greater than the preset abnormality value, an early warning signal is issued and the body of the target security inspection object is inspected; finally, the above method realizes the use of terahertz security inspection instrument for more accurate physiological parameter detection, which can quickly screen out target security inspection objects with abnormal physiological parameters for body scanning inspection, and is more convenient for detecting whether contraband is hidden in the human body based on terahertz security inspection technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 is an exemplary flow chart of a security inspection and control method based on terahertz wave detection of physiological parameters according to some embodiments of the present application;

[0043] Figure 2 is a schematic diagram of exemplary hardware and / or software of a security inspection and control device for detecting physiological parameters based on terahertz waves according to some embodiments of the present application;

[0044] Figure 3 It is a structural diagram of a computer device according to some embodiments of the present application using a security control method based on terahertz wave detection of physiological parameters. DETAILED DESCRIPTION

[0045] The core of this application is to detect specific physiological parameters of the target security subject using terahertz waves, determine the degree of abnormality of the target security subject's physiological parameters, and then determine whether the abnormality of the target security subject's physiological parameters exceeds a preset abnormality threshold. If the abnormality exceeds the preset abnormality threshold, the target security subject's body is inspected. This achieves relatively accurate physiological parameter detection using a terahertz security inspection device, can quickly screen target security subjects with abnormal physiological parameters for body scanning, and further facilitates the detection of contraband hidden in the human body based on terahertz security inspection technology.

[0046] In order to better understand the above technical solution, the following will be combined with the accompanying drawings and specific implementation methods to describe the above technical solution in detail. Figure 1 , which is an exemplary flow chart of a security inspection and control method based on terahertz wave detection of physiological parameters according to some embodiments of the present application. The security inspection and control method 100 based on terahertz wave detection of physiological parameters mainly includes the following steps:

[0047] In step 101, a security inspection echo signal corresponding to a terahertz wave security inspection signal sent to a target security inspection object is collected, an echo phase difference measurement is performed on the security inspection echo signal, and an offset variation curve of the security inspection echo signal is determined according to the result of the echo phase difference measurement.

[0048] In specific implementation, the terahertz wave security inspection signal sent to the target security inspection object in this step is a linear frequency modulated continuous wave signal. Since the linear frequency modulated continuous wave signal has the characteristics of large time width and large bandwidth, it has higher distance resolution and speed resolution than other signals, thereby making the information extracted from the security inspection echo signal more accurate. It will not be repeated here.

[0049] In addition, in this step, the echo phase difference of the security inspection echo signal is measured, and the offset variation curve of the echo signal is determined according to the result of the echo phase difference measurement, which can be specifically determined in the following manner, namely:

[0050] Firstly, the phase tangent algorithm is used to determine the phase angle information of the echo phase signal, and the phase information linear change curve is obtained according to the determined phase angle information of the phase signal;

[0051] Secondly, phase unwrapping is performed on the phase information linear change curve to obtain the echo phase signal;

[0052] Finally, an echo phase difference is obtained from the echo phase signal, that is, an echo phase difference measurement result is obtained, and an offset variation curve of the echo signal is determined according to the echo phase difference.

[0053] In a specific implementation, the echo phase difference measurement of the security inspection echo signal first requires obtaining the phase angle information of the echo phase signal. In some preferred embodiments, a phase tangent algorithm can be used to determine the phase angle information of the echo phase signal, wherein the phase angle information of the echo phase signal is determined according to the following formula:

[0054]

[0055] in, is the phase angle of the echo signal, is the real part of the echo signal, is the imaginary part of the echo signal.

[0056] The phase information linear variation curve can be determined according to the determined phase angle information of the echo phase signal.

[0057] It should be noted that since the above-mentioned phase tangent algorithm is not in the range of -π to π when determining the phase angle value, phase wrapping will occur. Values ​​exceeding this range will be added or subtracted by n 2π. Therefore, it is necessary to perform phase unwrapping on the signal of the phase information linear change curve determined by the phase tangent algorithm to obtain the echo phase signal, which is specifically determined according to the following formula:

[0058]

[0059] in, is the difference between the true value and the measured value of the phase at the k-th azimuth time sampling point, is an integer not less than 2, is the kth azimuth time sampling point, is the phase measurement value of the kth azimuth time sampling point, is the difference between the true value and the measured value of the phase at the k-1th azimuth time sampling point, is the phase measurement value of the k-1th azimuth time sampling point.

[0060] The phase value after unwrapping is obtained from the result of phase unwrapping calculation, and then the echo phase difference can be extracted, and the offset change curve of the security inspection echo signal can be obtained according to the echo phase difference. .

[0061] In step S102, the offset variation curve of the security inspection echo signal is decomposed to obtain echo offset components of different frequency bands. The echo offset components are divided into different component clusters according to the frequency bands in which the echo offset components are located, and the correlation between each echo offset component and the offset variation curve of the security inspection echo signal is calculated.

[0062] In some embodiments, the following method may be used to perform function decomposition based on the offset variation curve of the security inspection echo signal to obtain the echo offset components of different frequency bands, namely:

[0063] Performing function decomposition on the offset variation curve of the security inspection echo signal, and analyzing the local maximum and local minimum of the offset variation curve of the security inspection echo signal;

[0064] Determine the upper envelope curve and the lower envelope curve according to the local maximum value and the local minimum value;

[0065] Adding the upper envelope curve and the lower envelope curve and dividing the sum by two to obtain an average envelope curve;

[0066] Subtracting the average envelope curve from the offset variation curve of the security inspection echo signal to obtain a transition curve signal;

[0067] The transition curve signal is tested, and if the transition curve signal satisfies both conditions of a zero mean and local similarity of frequencies, an echo offset component of a frequency band is determined;

[0068] Decomposing the offset variation curve of the security inspection echo signal according to the determined echo offset component to obtain the offset variation curve of the next security inspection echo signal, and decomposing the offset variation curve of the next security inspection echo signal according to the above steps to obtain the echo offset component of the next frequency band;

[0069] Then, the decomposition is continued according to the above steps until the standard deviation between the echo offset components is less than the preset standard deviation, and the function decomposition is terminated.

[0070] The upper envelope curve can be fitted by the maximum point of the offset variation curve of the echo signal, and the lower envelope curve can be fitted by the minimum point. In some embodiments, the average envelope curve of the upper envelope curve and the lower envelope curve is calculated. The average envelope curve can be determined by the following formula:

[0071]

[0072] Among them, t represents the time point of security inspection echo signal sampling, represents the average envelope curve, represents the upper envelope curve, Represents the lower envelope curve.

[0073] In specific implementation, the envelope transition curve signal is determined by averaging the envelope curve, which can be determined according to the following formula:

[0074]

[0075] Among them, t represents the time point of security inspection echo signal sampling, is the envelope transition curve signal, is the offset change curve of the security inspection echo signal, is the average envelope curve.

[0076] In addition, when implementing it, check the envelope transition curve signal Whether the two conditions of zero mean and local similarity of frequency are met at the same time, if so, the envelope transition curve signal As the echo offset component of a frequency band, if it does not meet the requirements, the envelope transition curve signal As a new echo signal offset change curve Repeat the above average envelope curve calculation and envelope transition curve signal calculation, and test the re-determined transition curve signal. If the re-determined transition curve signal satisfies both the conditions of zero mean and local frequency similarity, the echo offset component of the frequency band is obtained.

[0077] The offset change curve of the security inspection echo signal is further decomposed according to the determined echo offset component to obtain the offset change curve of the next security inspection echo signal. In specific implementation, for example, the offset change curve of the echo signal calculated for the nth time and the echo offset component can be used to obtain the offset change curve of the next security inspection echo signal, that is, the offset change curve of the echo signal for the n+1th time, thereby obtaining the residual component of the next function decomposition. In this application, the offset change curve of the next security inspection echo signal, that is, the residual component, can be expressed by the following formula:

[0078]

[0079] Among them, t represents the time point of security inspection echo signal sampling, is the offset variation curve of the security inspection echo signal decomposed for the n+1th time, is the offset variation curve of the echo signal obtained by the nth calculation, is the echo offset component obtained by the nth calculation.

[0080] The offset change curve of the security inspection echo signal after the function decomposition for the n+1th time is the residual component Repeat the above average envelope curve calculation and envelope transition curve signal calculation to determine the echo offset component of the next frequency band until the standard deviation between the echo offset components is less than the preset standard deviation value, and then stop the decomposition. The standard deviation between the echo offset components in this application can be expressed by the following formula:

[0081]

[0082] in, is the standard deviation between echo offset components, is the number of decompositions, is any local extreme point of the offset variation curve of the echo signal before the nth decomposition, is the average value of all local extreme points in the nth decomposition.

[0083] In addition, the present application needs to divide the echo offset component into different component clusters according to the frequency band in which the echo offset component is located. The division of the component cluster interval can be clustered according to the frequency band interval of the measured physiological parameter type. For example, the measured physiological parameter type is respiratory frequency and heart rate, the human respiratory frequency is 0.2HZ to 0.8HZ, and the heart rate is 1HZ to 2HZ. Then the echo offset component with a frequency band of 0.2HZ to 0.8HZ is divided into the respiratory frequency component cluster, and the echo offset component with a frequency band of 1HZ to 2HZ is divided into the heart rate component cluster. The echo offset components in other frequency bands are regarded as non-correlated components and excluded. The correlation between the echo offset components in each component cluster and the offset of the echo signal is calculated one by one, where the correlation between the echo offset component and the offset of the echo signal can be calculated by the following formula:

[0084]

[0085] in, represents the echo offset component, Indicates the offset of the echo signal, Indicates the correlation between the offset component of the echo and the offset of the echo signal, represents the covariance between the offset component of the echo and the offset of the echo signal, represents the standard deviation of the echo offset component, Indicates the standard deviation of the offset of the echo signal.

[0086] In step 103, the echo offset component with the largest correlation in each component cluster is used as the physiological parameter signal of the target security inspection object, and different types of security inspection physiological parameter frequency domain spectrograms are generated according to the physiological parameter signals of the target security inspection object. The security inspection frequency measurement values ​​in the different types of security inspection physiological parameter frequency domain spectrograms are respectively extracted to obtain the security inspection frequency measurement values ​​of each type of security inspection physiological parameter.

[0087] In specific implementation, when there is only one echo offset component in a component cluster, correlation calculation is not required, and the echo offset component is directly used to generate a physiological parameter frequency domain spectrum of the corresponding type. If there are two or more echo offset components, the correlation of each echo offset component is obtained according to the above-mentioned correlation calculation formula, and the echo offset component with the largest correlation is selected as the physiological parameter signal of the target security inspection object, and then the corresponding type of physiological parameter frequency domain spectrum is generated according to the physiological parameter signal of the target security inspection object, and the frequency value information of the main components in the physiological parameter frequency domain spectrum is extracted as the physiological parameter frequency measurement value. For example, if the physiological parameter frequency domain spectrum is a heart rate frequency domain spectrum, and the frequency corresponding to the highest point of the normalized amplitude in the heart rate frequency domain spectrum is 1HZ, then the extracted heart rate measurement value of the target security inspection object is 60 beats / minute. In this application, the accuracy of the physiological parameter detection of the target security inspection object is improved by selecting the echo offset component with the highest correlation.

[0088] In some embodiments, the echo offset component with the greatest correlation in each component cluster may be used as the physiological parameter signal of the security inspection object in the following manner, namely:

[0089] extracting the echo offset component with the highest correlation;

[0090] Obtaining a time domain spectrogram of the physiological activity amplitude of the target security inspection subject based on the physiological activity amplitude information of the target security inspection subject from the echo offset component with the highest correlation;

[0091] Performing time-frequency transformation on the time-domain spectrogram of the physiological activity amplitude of the target security inspection object to obtain a physiological parameter signal of the target security inspection object.

[0092] In some embodiments, after extracting the echo offset component with the highest correlation, a time domain spectrogram of the target security object's chest motion amplitude and the target security object's physiological parameters is established based on the target security object's chest motion amplitude in the echo offset component.

[0093] In some embodiments, the following methods may be used to establish a time domain spectrogram of the chest cavity movement amplitude and the physiological parameters of the target security inspection object:

[0094] Determine the time it takes to receive the security check echo signal after transmitting the terahertz wave;

[0095] Obtain the physiological activity amplitude of the target security inspection object;

[0096] Determine the distance between the target security inspection object and the security inspection echo signal receiving sensor;

[0097] Obtain the range of motion of physiological activities of the human body under normal conditions;

[0098] Obtain the initial phase of human physiological activities;

[0099] A time domain spectrum of the chest motion amplitude of the target security object and the physiological parameters of the target security object is established based on the time taken to receive the security inspection echo signal after the terahertz wave is emitted, the physiological activity amplitude of the target security object, the distance between the target security object and the security inspection echo signal receiving sensor, the physiological activity amplitude of the human body in a normal state, and the initial phase of the human physiological activity. The relationship between the physiological activity amplitude of the target security object and the physiological parameters of the target security object satisfies the following expression:

[0100]

[0101] in, It is the time taken to receive the security check echo signal after transmitting the terahertz wave. is the physiological activity range of the target security inspection object, is the distance from the target security inspection object to the security inspection echo signal receiving sensor, Indicates the range of motion of physiological activities of the human body under normal conditions. It is the initial phase of human physiological activities. Physiological parameters of the target security inspection object.

[0102] In addition, it should be noted that, during the clustering process of the above-mentioned echo offset components, echo offset components that are not in the frequency band interval of the preset physiological parameter type will appear. These echo offset components reflect the inevitable noise interference in the surrounding area under actual use. Usually, the noise will cover the entire frequency band interval. Therefore, in the clustering process, the echo offset components are usually divided into n+1 intervals, where n is the number of physiological parameter types set to be measured. The echo offset components caused by noise interference are classified into the noise component cluster, and the echo offset components in the noise component cluster are not used for the calculation of the correlation degree.

[0103] In step 104, the difference coefficients between the security inspection frequency measurement values ​​of each type of security inspection physiological parameter and the corresponding standard human physiological parameters are determined, and the abnormality values ​​of the security inspection physiological parameters are obtained by adding the difference coefficients according to the corresponding weight coefficients.

[0104] In some embodiments, the coefficient of difference is the ratio of the deviation value of the security inspection frequency measurement value of a certain physiological parameter relative to the standard value of the corresponding human physiological parameter to the standard value of the corresponding human physiological parameter. In specific implementation, the coefficient of difference can be obtained by the following formula:

[0105]

[0106] in, is the coefficient of variation, is the security inspection frequency measurement value of any of the above physiological parameters, is the standard value of the corresponding human physiological parameter.

[0107] In addition, the abnormality of the physiological parameters can be obtained by adding the measured difference coefficients according to the weights corresponding to the difference coefficients, which can be expressed as follows:

[0108]

[0109] in, Indicates the abnormality of the physiological parameters of the target security inspection object, Indicates the weight of the difference coefficient of each physiological parameter, Indicates the difference coefficient between the security inspection frequency measurement value of each type of security inspection physiological parameter and the corresponding human standard physiological parameter.

[0110] In some embodiments, for example, the heart rate measurement value of the target security inspection object is 105 times / minute, and the security inspection breathing rate measurement value is 30 times / minute; the standard value of the human heart rate physiological parameter is 70 times / minute, and the standard value of the breathing rate physiological parameter is 15 times / minute; then the heart rate difference coefficient of the target security inspection object is 0.5, and the breathing rate difference coefficient is 1; the preset weight coefficient of the breathing rate physiological parameter is 0.3, and the weight coefficient of the heart rate physiological parameter is 0.7. According to the above formula, the physiological parameter abnormality of the target security inspection object is 0.65. In this application, by calculating the physiological parameter abnormality of the target security inspection object, the abnormality of the physiological parameters of the target security inspection object can be accurately and objectively reflected.

[0111] In step 105, the abnormality value of the security inspection physiological parameter is compared with a preset abnormality threshold. When the abnormality value of the security inspection physiological parameter is greater than the preset abnormality threshold, an early warning signal is issued and a body scanner is activated to perform a security inspection on the inside of the body of the target security inspection object.

[0112] It should be noted that for the preset abnormality threshold, the difference coefficient of the average of the difference between the extreme values ​​of the normal range of all detected physiological parameters and the standard value of the human physiological parameter should be calculated first, and then the difference coefficient of the average should be added according to the corresponding weight coefficient to obtain the preset abnormality threshold. The specific implementation process is as follows:

[0113] The average of the differences between the extreme values ​​of the normal range of the detected physiological parameter and the standard value of the human physiological parameter is calculated. The average can be expressed by the following formula:

[0114]

[0115] in, is the average of the differences between the extreme values ​​and the standard values ​​of the normal range of the physiological parameter, is the maximum value of the normal range of the physiological parameter, is the minimum value of the normal range of the physiological parameter, is the standard value of the corresponding human physiological parameter.

[0116] The average of the differences between the extreme values ​​of the normal range of physiological parameters and the standard values ​​obtained by the above formula According to the difference coefficient calculation formula in step 104 and the physiological parameter abnormality formula, the abnormality of the average of the difference between the extreme value and the standard value of the normal range of the physiological parameter can be obtained, and the abnormality of the average of the difference between the extreme value and the standard value of the normal range of the physiological parameter can be used as the preset abnormality threshold value. In specific implementation, it can also be determined according to the mean value obtained by statistical method based on the actually measured physiological parameter value, which is not specifically limited here.

[0117] In some embodiments, when the abnormality of the physiological parameter is greater than a preset abnormality threshold, a body scanner such as an X-ray scanner is started to perform a security inspection on the inside of the body of the target security inspection object whose abnormality of the physiological parameter is greater than the preset abnormality threshold. No further details are given here.

[0118] In addition, in another aspect of the present application, in some embodiments, the present application provides a security control device based on terahertz wave detection of physiological parameters, referring to Figure 2 This figure is a schematic diagram of exemplary hardware and / or software of a security inspection control device based on terahertz wave detection of physiological parameters according to some embodiments of the present application. The security inspection control device 200 includes: an offset change curve determination module 201, a correlation determination module 202, a security inspection frequency measurement value determination module 203, a physiological parameter abnormality value determination module 204, and a security inspection control module 205, which are described as follows:

[0119] The offset change curve determination module 201 in this application is mainly used to collect the security inspection echo signal corresponding to the terahertz wave security inspection signal sent to the target security inspection object, perform echo phase difference measurement on the security inspection echo signal, and determine the offset change curve of the security inspection echo signal based on the result of the echo phase difference measurement;

[0120] Correlation determination module 202. In the present application, correlation determination module 202 is mainly used to decompose the offset variation curve of the security inspection echo signal to obtain echo offset components in different frequency bands, divide the echo offset components into different component clusters based on the frequency bands in which the echo offset components are located, and determine the correlation between each echo offset component and the offset variation curve of the security inspection echo signal;

[0121] The security inspection frequency measurement value determination module 203 in the present application is mainly used to use the echo offset component with the largest correlation in each component cluster as the physiological parameter signal of the target security inspection object, generate different types of security inspection physiological parameter frequency domain spectrograms based on the physiological parameter signal of the target security inspection object, and extract the security inspection frequency measurement values ​​from the different types of security inspection physiological parameter frequency domain spectrograms to obtain the security inspection frequency measurement values ​​of each type of security inspection physiological parameter;

[0122] Physiological parameter abnormality value determination module 204, in this application, the physiological parameter abnormality value determination module 204 is mainly used to determine the difference coefficient between the security inspection frequency measurement value of each type of security inspection physiological parameter and the corresponding human standard physiological parameter, and add each difference coefficient according to the corresponding weight coefficient to obtain the security inspection physiological parameter abnormality value;

[0123] The security inspection control module 205 in this application is mainly used to compare the abnormality value of the security inspection physiological parameter with the preset abnormality threshold. When the abnormality value of the security inspection physiological parameter is greater than the preset abnormality threshold, an early warning signal is issued and the body scanner is started to perform a security inspection on the inside of the body of the target security inspection object.

[0124] In addition, the present application also provides a computer device, which includes a memory and a processor, wherein the memory stores code, and the processor is configured to obtain the code and execute the above-mentioned security inspection and control method based on terahertz wave detection of physiological parameters.

[0125] In some embodiments, reference Figure 3 , which is a schematic diagram of the structure of a computer device according to some embodiments of the present application using a security control method based on terahertz wave detection of physiological parameters. The security control method based on terahertz wave detection of physiological parameters in the above embodiment can be achieved by Figure 3 The computer device shown in FIG3 is implemented, and the computer device includes at least one processor 301 , a communication bus 302 , a memory 303 and at least one communication interface 304 .

[0126] The processor 301 can be a general-purpose central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more processors for controlling the execution of the security control method based on terahertz wave detection of physiological parameters in the present application.

[0127] The communication bus 302 may include a pathway for transmitting information between the aforementioned components.

[0128] Memory 303 may be, but is not limited to, a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, a random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disk storage, an optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk or other magnetic storage device, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer. Memory 303 may be independent and connected to processor 301 via communication bus 302. Memory 303 may also be integrated with processor 301.

[0129] Memory 303 is used to store program code for executing the solution of the present application, and is controlled by processor 301 for execution. Processor 301 is used to execute the program code stored in memory 303. The program code may include one or more software modules. In the above embodiment, the determination of the abnormality of the physiological parameter can be implemented by processor 301 and one or more software modules in the program code in memory 303.

[0130] The communication interface 304 uses any transceiver or other device for communicating with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area network (WLAN), etc.

[0131] In a specific implementation, as an example, a computer device may include multiple processors, each of which may be a single-core (single-CPU) processor or a multi-core (multi-CPU) processor. A processor herein may refer to one or more devices, circuits, and / or processing cores for processing data (e.g., computer program instructions).

[0132] The aforementioned computer device can be a general-purpose computer device or a dedicated computer device. In a specific implementation, the computer device can be a desktop computer, a portable computer, a network server, a personal digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, or an embedded device. The embodiments of this application do not limit the type of computer device.

[0133] In addition, the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the above-mentioned security inspection and control method based on terahertz wave detection of physiological parameters.

[0134] In summary, in the security inspection control method and device based on terahertz wave detection of physiological parameters disclosed in the embodiments of the present application, the security inspection echo signal of the terahertz wave is first collected and the echo phase difference of the signal is measured, and the offset change curve of the echo signal is obtained from the result of the echo phase difference measurement; the offset change curve can be decomposed to obtain echo offset components of different frequency bands, and the echo offset components are divided into different component clusters according to the frequency band intervals, and the echo offset component with the largest correlation in each component cluster is extracted as the physiological parameter signal of the target security inspection object, and different types of physiological parameter frequency domain spectra are generated according to the physiological parameter signals of the target security inspection object, and the physiological parameter frequency domain spectra are extracted. The method comprises the following steps: calculating the frequency value of the domain spectrum; calculating the difference coefficient between the frequency measurement value of each physiological parameter and the standard value of the corresponding human physiological parameter, and adding the difference coefficients according to the corresponding weight coefficients to obtain the abnormality degree of the physiological parameter; thereby comparing the value of the abnormality degree of the physiological parameter with a preset abnormality threshold value; when the abnormality degree of the physiological parameter is greater than the preset abnormality threshold value, issuing a warning signal and performing a security check on the inside of the body of the target security inspection object; thereby realizing more accurate physiological parameter detection using a terahertz security inspection instrument, being able to quickly screen out target security inspection objects with abnormal physiological parameters for body scanning and inspection, and being more convenient for detecting whether contraband is hidden in the human body based on terahertz security inspection technology.

[0135] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present application.

[0136] Obviously, those skilled in the art may make various changes and modifications to the present application without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present application fall within the scope of the claims and their equivalents, the present application is intended to include such modifications and variations.

Claims

1. A security inspection and control method based on terahertz wave detection of physiological parameters, characterized in that: include: Collecting a security inspection echo signal corresponding to the terahertz wave security inspection signal sent to the target security inspection object, performing echo phase difference measurement on the security inspection echo signal, and determining an offset change curve of the security inspection echo signal according to the result of the echo phase difference measurement; performing a function decomposition on the offset variation curve of the security inspection echo signal to obtain echo offset components in different frequency bands, dividing the echo offset components into different component clusters based on the frequency bands in which the echo offset components are located, and determining the correlation between each echo offset component and the offset variation curve of the security inspection echo signal; Performing function decomposition according to the offset variation curve of the security inspection echo signal to obtain echo offset components of different frequency bands specifically includes: Analyzing the local maximum and local minimum of the offset variation curve of the security inspection echo signal; Determine the upper envelope curve and the lower envelope curve according to the local maximum value and the local minimum value; Adding the upper envelope curve and the lower envelope curve and dividing the sum by two to obtain an average envelope curve; Subtracting the average envelope curve from the offset variation curve of the security inspection echo signal to obtain a transition curve signal; The transition curve signal is tested, and if the transition curve signal satisfies both conditions of zero mean and local similarity of frequency, an echo offset component of a frequency band is obtained; Decomposing the offset variation curve of the security inspection echo signal according to the determined echo offset component to obtain the offset variation curve of the next security inspection echo signal; determining the average envelope curve and transition curve signal of the offset variation curve of the next security inspection echo signal according to the above steps to obtain the echo offset component of the next frequency band; The offset change curve of the echo signal obtained by the n-th calculation and the echo offset component can be used to obtain the offset change curve of the next security inspection echo signal, that is, the offset change curve of the n+1-th echo signal, thereby obtaining the residual component for the next function decomposition. The offset change curve of the next security inspection echo signal, that is, the residual component, can be expressed by the following formula: Among them, t represents the time point of security inspection echo signal sampling, is the offset variation curve of the security inspection echo signal decomposed for the n+1th time, is the offset variation curve of the echo signal obtained by the nth calculation, is the echo offset component obtained by the nth calculation; Continue to decompose according to the above steps until the standard deviation between the echo offset components is less than the preset standard deviation, and then end the decomposition; The echo offset component with the largest correlation in each component cluster is used as the physiological parameter signal of the target security inspection object, different types of security inspection physiological parameter frequency domain spectrograms are generated based on the physiological parameter signals of the target security inspection object, and security inspection frequency measurement values ​​from the different types of security inspection physiological parameter frequency domain spectrograms are respectively extracted to obtain security inspection frequency measurement values ​​of each type of security inspection physiological parameter; Determine the difference coefficient between the security inspection frequency measurement value of each type of security inspection physiological parameter and the corresponding human standard physiological parameter, add each difference coefficient according to the corresponding weight coefficient to obtain the abnormality value of the security inspection physiological parameter; The abnormality value of the security inspection physiological parameter is compared with a preset abnormality threshold. When the abnormality value of the security inspection physiological parameter is greater than the preset abnormality threshold, an early warning signal is issued and a body scanner is started to perform a security inspection on the inside of the body of the target security inspection object.

2. The method according to claim 1, wherein Determining the offset variation curve of the echo signal according to the result of the phase difference measurement specifically includes: The phase tangent algorithm is used to obtain the linear change curve of phase information; performing phase unwrapping on the phase information linear variation curve to obtain an echo phase signal; An echo phase difference is obtained from the echo phase signal, and an offset variation curve of the security inspection echo signal is determined according to the echo phase difference.

3. The method according to claim 1, wherein The correlation between each echo offset component and the offset variation curve of the security inspection echo signal is determined according to the following formula: in, represents the echo offset component, Indicates the offset of the echo signal, Indicates the correlation between the echo offset component and the offset of the echo signal, represents the covariance between the offset component of the echo and the offset of the echo signal, represents the standard deviation of the echo offset component, Indicates the standard deviation of the offset of the echo signal.

4. The method according to claim 1, wherein The abnormality of the physiological parameters of the target security inspection object is determined by the following formula: in, Indicates the abnormality of the physiological parameters of the target security inspection object, Indicates the weight coefficient of each physiological parameter, Indicates the difference coefficient between the security inspection frequency measurement value of each type of security inspection physiological parameter and the corresponding human standard physiological parameter.

5. The method according to claim 1, wherein The terahertz wave security inspection signal sent to the target security inspection object is a linear frequency modulated continuous wave signal.

6. The method according to claim 1, wherein The body scanner is an X-ray scanner.

7. A security inspection and control device based on terahertz wave detection of physiological parameters, characterized in that: include: An offset change curve determination module is used to collect a security inspection echo signal corresponding to a terahertz wave security inspection signal sent to a target security inspection object, perform echo phase difference measurement on the security inspection echo signal, and determine an offset change curve of the security inspection echo signal based on the result of the echo phase difference measurement; a correlation determination module, configured to perform a functional decomposition on the offset variation curve of the security inspection echo signal to obtain echo offset components in different frequency bands, divide the echo offset components into different component clusters based on the frequency bands in which the echo offset components are located, and determine the correlation between each echo offset component and the offset variation curve of the security inspection echo signal; Performing function decomposition according to the offset variation curve of the security inspection echo signal to obtain echo offset components of different frequency bands specifically includes: Analyzing the local maximum and local minimum of the offset variation curve of the security inspection echo signal; Determine the upper envelope curve and the lower envelope curve according to the local maximum value and the local minimum value; Adding the upper envelope curve and the lower envelope curve and dividing the sum by two to obtain an average envelope curve; Subtracting the average envelope curve from the offset variation curve of the security inspection echo signal to obtain a transition curve signal; The transition curve signal is tested, and if the transition curve signal satisfies both conditions of zero mean and local similarity of frequency, an echo offset component of a frequency band is obtained; Decomposing the offset variation curve of the security inspection echo signal according to the determined echo offset component to obtain the offset variation curve of the next security inspection echo signal; determining the average envelope curve and transition curve signal of the offset variation curve of the next security inspection echo signal according to the above steps to obtain the echo offset component of the next frequency band; The offset change curve of the echo signal obtained by the n-th calculation and the echo offset component can be used to obtain the offset change curve of the next security inspection echo signal, that is, the offset change curve of the n+1-th echo signal, thereby obtaining the residual component for the next function decomposition. The offset change curve of the next security inspection echo signal, that is, the residual component, can be expressed by the following formula: Among them, t represents the time point of security inspection echo signal sampling, is the offset variation curve of the security inspection echo signal decomposed for the n+1th time, is the offset variation curve of the echo signal obtained by the nth calculation, is the echo offset component obtained by the nth calculation; Continue to decompose according to the above steps until the standard deviation between the echo offset components is less than the preset standard deviation, and then end the decomposition; a security inspection frequency measurement value determination module, configured to use the echo offset component with the greatest correlation in each component cluster as the physiological parameter signal of the target security inspection subject, generate different types of security inspection physiological parameter frequency domain spectrograms based on the physiological parameter signals of the target security inspection subject, and extract the security inspection frequency measurement values ​​from the different types of security inspection physiological parameter frequency domain spectrograms to obtain the security inspection frequency measurement values ​​of each type of security inspection physiological parameter; The physiological parameter abnormality value determination module is used to determine the difference coefficient between the security inspection frequency measurement value of each type of security inspection physiological parameter and the corresponding human standard physiological parameter, and add each difference coefficient according to the corresponding weight coefficient to obtain the abnormality value of the security inspection physiological parameter; The security inspection control module is used to compare the abnormality value of the security inspection physiological parameter with a preset abnormality threshold. When the abnormality value of the security inspection physiological parameter is greater than the preset abnormality threshold, an early warning signal is issued and a body scanner is activated to perform a security inspection on the inside of the body of the target security inspection object.

8. A computer device, characterized in that: The computer device includes a memory and a processor, the memory stores code, and the processor is configured to obtain the code and execute the security inspection and control method based on terahertz wave detection of physiological parameters as described in any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the security inspection and control method based on terahertz wave detection of physiological parameters as claimed in any one of claims 1 to 6 is implemented.

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