WO2014168354A1

WO2014168354A1 - Moving-image-based physiological signal detection method, and device using same

Info

Publication number: WO2014168354A1
Application number: PCT/KR2014/002322
Authority: WO
Inventors: 최진관
Original assignee: Choi Jin Kwan
Priority date: 2013-04-11
Filing date: 2014-03-20
Publication date: 2014-10-16

Abstract

The present invention relates to a method and device for reliably and accurately measuring psychophysiological parameters in subjects. The measurement method comprises the steps of: acquiring moving images from psychophysiological test subjects via moving images; measuring vibration parameters of the test subjects from the moving images; generating biological signal images on the basis of the vibration parameters; and generating psychophysiological reaction parameters of the test subjects by processing the biological signal images.

Description

Video-based physiological signal detection method and apparatus applying same

The present invention relates to a method for acquiring a biosignal used in biometrics, electronics, medicine, and the like, and an apparatus for applying the same. Specifically, a method for acquiring a physiological signal using a video obtained from a living body and its application It relates to a device to.

The first scientifically based hypothesis of the inseparable relationship between human psychology and physiology was proposed between 1890 and 1895 by Sigmund Freud, the founder of analytical psychology. The hypothesis that any change in human psychology is related to the body's physiological response is widely accepted today. Of course, the interface between these correlations has not yet been defined, and it is true that there are many different approaches to this definition.

Therefore, there have been many studies to obtain such psychophysiologically integrated information about the human body, and some specific contact methods, devices, and systems have been known to date. They use well-known physiological parameters of the human body to assess human emotional and psychological conditions and to make medical diagnoses.

The most widely known system, also known as a "lie detector," is obtained through various channels to measure changes in psychophysiological (mental body) parameters when the body responds to certain external stimuli, especially horse stimuli. Using physiological information. Analyzing the condition of the human body in the above manner generally takes several hours, requires the sensor to be firmly attached to the subject's body and requires the participation of trained test personnel. Therefore, there are many practical limitations in using the above system extensively to make psychophysiological diagnosis of the human body.

Well-known wave systems (WO 02/065902, pulse measuring methods and devices and biometric systems), which have been used since ancient times in the East to make medical diagnoses as a result of fluctuations in the pulses of various parts of the human body. . With modern stereoscopic pulse measuring systems, pulses can be measured hundreds of thousands of times at the fingertips of the human body, which can accurately measure the psychophysiological changes occurring in the human body.

These systems provide sufficient information from the point of view of analyzing the overall condition of the human body, but they are limited in their use due to the attachment of sensors to the human body, and the integrated information obtained from the local area is not easy to analyze.

Another group of contact methods, devices and systems, aka `` aura viewer '' (US 5132714, RU2110824, RU 2217047), is a physiological technique obtained from a patient's hand or finger to conditionally aura around the patient. Use information. However, the electrophysical parameters of the palm skin or the gas discharge luminescence around the finger, which is manifested by the Kirlian effect, are not directly related to the bioenergy radiation (aura) of the entire human body.

Another problem with this contact method is that it is technically impossible to conduct the experiment without the subject's knowledge because the contact sensor is used. Persons undergoing contact psychophysiological tests are always aware of this fact, which adds another challenge to the analysis of test results. Because people who try to hide something try to hide information, and people who do nothing wrong feel the same stress and anxiety throughout the test. About half of the Internet sites dealing with polygraphs tell you how to trick them, and there are many examples of how this has been successful.

Since the test subject does not notice, the user does not try to hide his or her condition, and thus the state of the human body can be controlled by using a non-contact sensor for knowing the state of the human body. As a result, additional problems and errors in the analysis and diagnosis of the human condition can be avoided.

Methods and devices for contactlessly obtaining information about a subject (WO 02/51154) are also known. This method converts an object into an image, and projects the image of the object, converts the image of the object into an electrical signal that is a series of images, measures the difference between the images in the consecutive images, and obtains the information between the images to obtain the information of the object. Iii) accumulate and use differences.

Such a contactless device provides information on the psychophysiological state of the human body in a contactless manner in real time without being noticed by the subject (human). However, the information obtained does not always accurately reflect the change in state. Above all, this relates to the difference between the accumulated images does not always accurately reflect the difference between changes in the position of the object. In other words, it is difficult to analyze an object with a small change of position in space, thereby reducing the accuracy and reliability of measuring the psychophysiological parameters of the object.

Therefore, there is an increasing demand for a method of acquiring a biosignal of a subject that can overcome the unreasonable points of the conventional apparatus for providing psychophysiological information and improve sensitivity and reliability by being contactless. In addition, as portable devices such as smartphones are deeply introduced into daily life, numerous solutions are being developed that interoperate with smartphones, and thus, through portable devices such as smartphones, such as psychophysiological emotional parameters by bio-signals or diagnosis of medical diseases. The demand for available technologies and products is growing rapidly.

The present invention provides a method for measuring psychophysiological parameters of a subject having high reliability based on video and a device using the same.

The present invention provides a method for measuring a highly reliable psychophysiological signal from a subject or a video obtained from a subject, and a device for applying the same.

In addition, the present invention provides a method for quantifying a biosignal and visualizing it using psychophysiological parameters obtained based on a video, and a device for applying the same.

Biological signal acquisition method according to the present invention:

Photographing the subject to obtain a plurality of continuous image information;

Analyzing the image information to extract the vibration parameter of the subject; And

Generating psychophysiological parameters based on the vibration parameters;

Extracting the physiological signal of the subject from the parameter.

According to an embodiment of the present disclosure, the method may further include generating and visualizing a corresponding image of the physiological signal of the subject using the physiological signal.

Physiological signal detection device according to the present invention:

An image acquisition unit for photographing a subject and obtaining a continuous image;

A photodetector for continuously capturing the image of the A, an A / D converter for converting the captured image into image data, and measuring the vibration parameter by analyzing the converted continuous image data, based on the measured vibration parameter. And a display unit for displaying the generated biosignal image and a processor for generating a biosignal image.

According to the present invention as described above, there is an effect that can provide a portable device having a camera that can reliably and accurately measure the psychophysiological parameters of the subject.

In addition, a portable device having a camera capable of easily detecting or recognizing a psychophysiological state of a human body by imaging a psychophysiological response parameter of the human body may be provided.

In order to obtain information about the object, various methods and devices proposed here may be utilized. A device for obtaining biosignal information on a human body may be widely used in psychiatry by measuring a physiological state of a human body in a non-contact manner.

Portable devices using this method and device can also be used to measure, analyze, and manage human health by influencing humans using a number of factors.

1 is a flowchart illustrating a method of acquiring a biosignal according to an exemplary embodiment.

FIG. 2 is a schematic block diagram functionally classifying electronic devices implementing the method shown in FIG.

3A is a block diagram of an electronic device implementing the method illustrated in FIG. 1.

FIG. 3B is a block diagram showing correlations between components in the electronic device shown in FIG. 3.

4 is a flowchart illustrating a method of acquiring a biosignal according to another exemplary embodiment of the present invention.

This is a block diagram.

FIG. 5A illustrates the emission of bioenergy (aura) around a subject's human body image formed by the amplitude component of the vibration image.

5B shows bioenergetics radiated around the actual image of the human body.

6A and 6B show the biological image radiation according to the state of the subject, and FIG. 6A shows a stable state and FIG. 6B shows an unstable stress state.

7A is a distribution graph of frequency components (biosignal images) of a human body vibration image in a stable state.

FIG. 7B is a distribution graph of the frequency components (biosignal images) of the human body vibration image under stress.

FIG. 8A is a radial graph (chart) showing the emotional state of a subject according to the method of the present invention, and FIG. 8B shows a result display screen on a smartphone, which is a kind of portable device implemented by the present invention.

Hereinafter, a method of detecting a physiological signal and an apparatus applying the same according to the present invention will be described with reference to the accompanying drawings.

First, the concept of the present invention will be described below with reference to FIG.

As illustrated in FIG. 1, the present invention captures images that continuously change by photographing a living body, for example, a subject undergoing psychophysiological changes (11), and processes (analyzes) each image to generate vibration parameters. (12) and extract the physiological signal using the parameter (13). The physiological signals thus obtained are used for various purposes (14), in which the emotional state of the subject is evaluated and presented in the form of a text or an image, or various kinds of image contents are presented to the subject in response to the physiological signals. can do. This method may be implemented by a device having a structure as shown in FIG. 2. 2 is a functional block diagram of a physiological signal detection apparatus. Referring to FIG. 2, the physiological signal detecting apparatus according to the present invention includes a camera 21 for photographing a subject (or a subject 1), an image processor 22 for analyzing an image obtained from the camera 21, and an image processor. A signal analyzer 23 for extracting vibration parameters (parameters) using the signals from 22 and generating the physiological signals, and an application unit for applying the physiological signals obtained from the signal analyzer 23 ( 24), wherein the application unit 24 may include, for example, a display for generating a character or an image using the physiological signal and displaying the same. The image processor 22 and the application unit 24 as described above are implemented by an application program based on a central processing unit (CPU) or an application processor (AP). This technical scope of the present invention is not limited to the type of application, and therefore, it is obvious that it includes any application using vibration parameters.

Hereinafter, with reference to the vibration parameters used in the present invention, the relationship between the vibration of each part of the living body and the psychophysiological parameters will be described.

In small particle physics, there is no clear boundary between the wave and particulate properties of matter, and the photon energy (ε) is known to be linked to the frequency of photon energy (υ) through Planck's constant (ε = hυν). It is hypothesized that the energy emitted from each part of the organism is proportional to the vibration frequency of that part in the space. As a result, in order to record the energy coming from a living thing, it is necessary to record the vibrations (in or between spaces) that occur at various parts of the living thing. This can be done by using a contactless television system with sufficient resolution and fast processing power. In addition, the frequency components of the biosignal images obtained (ie, the vibration (position shift, wave) frequency at each site) have the most information on the bioenergy, or psychophysiological characteristics, of the observed organisms. Analysis of the obtained biosignal image may be performed by a person or mathematically by processing at least one of the obtained digital biosignal image and its components by a program. In order to prepare and analyze algorithms for mathematical processing, it is good to make a biosignal image which is convenient for visual analysis such as pseudo-color image of monitor screen.

In other words, the frequency component of the biosignal image to be obtained allows to continuously and clearly specify the levels of psychophysiological and emotional states of the human body and to distinguish the changes in the human state when various stimuli occur in humans. do. As it turns out, an image showing the human body's bioenergy field represented by an aura located around the human body can be used to evaluate the psychophysiological state of the human body faster and more accurately than other methods.

The term aura refers to an integral characteristic of the psychophysiological state of the human body. These auras appear around the human body and have specific relationships with the bioenergy components of the human body. The image of the human aura provides a lot of information when studying the psychophysiological parameters of the human body, and the following factors are considered. Human emotional state can literally change every second. The average person can not stay in one emotional state for a long time.

Every thought and action or reaction to a situation leads to a momentary change in the emotional state (images of each biosignal). Therefore, it is important to find the optimal correlation between the number of information on the obtained biosignal image (above all, the resolution of the camera) and the rapid processing of the system.

Adds an amplitude modulating of the aura size, and modulates the subject's maximum vibrational frequency by color modulating the frequency of the positional change or average value of the amplitude in a specific region of the human body, Changes can be recorded at a glance and instantaneously. Frequent fluctuations in the brain are known to play a key role in learning, memory, and solving a variety of tasks. Experiments have shown that the most intensive part of vibration in the human body is the brain, and in most cases auras (frequency components of vibration images) may be present only around the human head, much larger than the auras around the body. . Changes that occur in the human body are represented by the collapse of the aura or the appearance of asymmetry in color and form. This is clearly seen in the obtained biosignal image.

There is one point in that the elements of the biosignal image are topologically associated with the elements of the real image. Experimental results show that the emotional state of the human body that contains the most information is transmitted at the maximum oscillation frequency, and the average level of the frequency or the background level of adjacent points can be shrouded or cover up the true changes that occur when visually accepting the biosignal image. It may be.

Therefore, it is shown that the topological relationship between the elements of the biosignal image and the elements of the real image is less effective than the frequency components of the vibration image represented by the aura located around the real image. When the elements of the biosignal image are topologically related to the elements of the actual image, the elements with the maximum vibration frequency are not visible in the entire background when the image is subjected to color-frequency adjustment. In order to mathematically analyze the biosignal image in various forms, the biosignal image to be obtained must be visually controlled in advance. The proposed image of the frequency component of the biosignal image, in the form of an aura, is consistent with the physical concept of bioenergy radiation and enables visual control and analysis of the device-generated image.

Unlike frequency components, the use of amplitude components is more effective in topological relationships. First of all, the amplitude component of the biosignal image, which is topologically connected to the vibration point, can be used to evaluate the quality of the biosignal image obtained and to determine the exact parameters for tuning the system.

First, the measurement of the vibration image parameter will be described in detail.

Acquiring information about the level of aggression of a creature consists of constructing a frequency distribution histogram and measuring the head vibration image parameters of the creature.

Aggregation of Aggression Levels (Ag) consists of:

Fm: maximum frequency of frequency distribution density in the histogram

Fi: "I" frequency aggregation of frequency distribution density acquired over N frame time in histogram

Fin: Vibration image processing frequency

n: Aggregate amount including interframe differences over the limit in N frames

The biological head vibration image parameter is measured to obtain information about the stress level of the creature. The stress level St is calculated by the following Equation 2.

: Total Amplitude of "I" Thermal Vibration Image of Left Part of Subject

: Total amplitude of "I" thermal vibration image in the right region of the subject

:

From

Maximum value of liver

: Maximum frequency of "I" thermal vibration image in the left part of the object

: Maximum frequency of "I" thermal vibration image on the right side of the subject

:

From

Maximum value of liver

n: number of columns

To obtain information about the level of anxiety in the organism, the biological head vibration image parameters are measured. Anxiety level (Tn) is measured by the following Eq.

Pi (f): Vibration image frequency distribution power spectrum

fmax: maximum frequency of the vibration image frequency distribution spectrum

To obtain information about the level of compatibility of living things with other organisms, determine histograms of vibration frequency distributions for all individual organisms, construct each histogram, obtain common frequency distributions, and obtain the general law of distribution and the previously obtained co-distribution area. Make the same and find the difference between the general law of distribution and the frequency histogram. The compatibility level (C) is counted as the following <Equation 4>.

K: Frequency histogram generalized correlation coefficient obtained

y ’: general distribution density

In determining verbal or nonverbal falsehoods, vibration image parameters of the head of the organism are measured to obtain information about the integrated level of change in the psychophysiological state.

The integrated level of change (L) in the psychophysiological state used in the false decision is summed up by the formula:

P _м : parameter to change the higher set threshold

Pc: Vibration image parameter measured when determining false level

K: correlation coefficient

n: number of parameters measured

m: number of parameters changed

As is well known, cybernetics and information theory examines the applicability of operational methods and techniques to organisms and living systems. Modern concepts of cognitive biology are usually related to the concepts and definitions of signal information and transfer theory, and enable the psychophysiological information of mathematical parameters established in information theory. The author's long study and observation of the study of human head micromovement with the help of statistical parameters used in information theory shows that there is a statistically reliable dependence between the state of human psychophysiology and the head micromovement information statistics parameter. Could know.

The author is able to present his own interpretation of this phenomenon and vestibular emotion reflexes. First, we will define the interrelationship between psychophysiological energy coordination (metabolism). All typical emotional states can be characterized by a correlation between specific energy consumption and individual physiologically necessary energy and emotional energy. At this time, the physiological energy is formed to realize the physiological process, and the emotional energy is formed as a result of the conscious or unconscious process. For example, the attack state, if it is the same attack condition, should be expressed differently in various people, and natural adjustment process such as age, gender and education level should be considered. However, from a physiological point of view, these differences should not have a fundamental meaning in the relative amounts and locations of energy release within the body. All this leads to visible emotional signs, such as flushing of the face, frequent sighs, rapid heartbeats, and certain micromovements. The main reason for the external manifestation of the emotional state is due to the additional release of energy in the body organs which changes the correlation between physiological and emotional energy. It should be emphasized that the author took into account the body-chemical energy of natural physical processes, which are well known at the level of modern technology development. The progression of physiological processes, and the interruption and triggering processes for human thought and movement processes.

The main challenge of the vestibular system is, above all, to maintain a dynamic equivalence or equality. However, the study proved that the equilibrium state of the semi-closed system is possible only if the dynamics, chemistry, energy, and other systems (systems) forming the subject are equal. Unbalance in any one of these systems results in the destruction of the equilibrium state of the adjacent system, i.e. the breakdown of mechanical balance results in the breakdown of energy balance.

The human head in a vertical, semi-balanced state can be seen as an overly sensitive mechanical indicator of all the energy processes in the body. From a biomechanical point of view, maintaining the vertical balance and equilibrium of the heads far above the center of gravity requires tremendous continuous effort and reduction of the neck-head bone muscles. Moreover, this movement is realized reflexively under vestibular system. All meaningful phenomena in the organs lead to changes in the ongoing physiological process. This is similar to other physiological process changes traditionally used for psychophysiological analysis, such as galvanic skin response (GSR), arterial pressure, and heart rate. In addition, the parameters of head movement vary with the amount of energy expression and the location of energy expression. The spatial three-dimensional trajectory of head movements is very complicated because the shape of the head resembles a sphere. Also, the movement trajectory of each point can vary significantly in the movement of hundreds of neck muscles. Statistical analysis of informative motion parameters enables reliable quantitative parameter differentiation of head movements. In other words, it is possible to measure and confirm the emotional state through the measurement of energy and vestibular response. The laws of mechanics appear to be consistent, and behavior is always reactionary to maintain equality. Energy measurements in the body organs that naturally target a wide variety of people will result in consistent corresponding changes in head movement parameters through vestibular activity.

The overall emotional classification according to the informational / statistical parameters of the presented head movements confirms all emotional states. Currently there is no single, holistic approach to measuring emotional state, so it can be used for initial measurements in terms of other psychophysiological methods or independent experimental evaluations. Modern psychology mainly uses qualitative criteria in the evaluation of emotional state, which essentially makes it impossible to measure quantitatively, and the objective evaluation of human state is difficult. However, the suggested method allows us to measure all emotional states. Given that a change in head movement parameters is functionally related to a change in energy exchange, naturally, head movement parameters are a general characteristic psychophysiological state of man. The accuracy of agreement of the proposed formulas for counting emotional states according to existing assessment criteria is low compared to the emotional state assessment method through head micromovement. This is because there is no overall standard for assessing emotional state at the current level of technology. The proposed method is characteristic in that an integrated approach is possible for all emotion measurements. All previous methods were also used to assess various emotional states. Adopting the proposed concept for measuring emotional state allows the inclusion of psychology in precision science and enables the same emotional measurement.

Acquisition of the signal regarding the head movement of the subject is performed by comparing images by the camera. In terms of spatial and temporal distribution information statistics parameters, the movement speed of the head of the creature is measured as the average frequency of marker movement, determined in units of 10 seconds, which yields the maximum frequency of TV camera work. These characteristics can well reflect human emotional anxiety and can characterize anxiety levels.

When the vibration image simultaneously represents the spatial and temporal distribution of the target motion energy, the number of factors having the same vibration frequency for a specific time is aggregated to obtain a frequency histogram. Histograms therefore exclude information about the spatial distribution of vibration frequencies. This apparent loss of spatial information actually increases the motion information, because in terms of physiological energy, it is not very important in which part of the head the movement is performed unlike the fine movement of the face. The configuration of the frequency histogram is determined according to the following.

As is well known, a new formula has been proposed that takes into account two main factors that differ from the existing contradictory approaches that determine the level of aggression. Two main factors are the average vibration frequency, or the Fm micromovement and parameters, and the mean square deviation, which best show the characteristic spread of the vibration. This aggressive person has a high spreading frequency in movement of high frequency of hair fine movement and various points of the head part. Other official correlation coefficients show aggressive correlation coefficients for values from 0 to 1.

Fm: Maximum frequency of the frequency distribution density histogram

Fi: Number of i frequency aggregates in frequency distribution density histogram obtained per 50 frame time

Fin: Vibration image processing frequency

n: Aggregate number of interframe differences higher than the threshold at 50 frames

This equation allows everyone to determine their level of aggression, with naturally lower aggression levels approaching zero. People with high aggression are close to one. The use of a vibrating imaging system's security system to identify potentially dangerous ones uses a threshold of 0.75 to identify aggressive ones. Vibration Image 7.3 The left corner of the program (average histogram) continues to display the aggressor level calculated according to the frequency histogram and the formula presented for the operator's visual control.

The next step is to statistically identify meaningful vibration image information parameters that determine vibration image acquisition and subsequent aggression levels. This determines, among other things, vibration symmetry parameters for amplitude and frequency vibration images.

In contrast to the well-known and contradictory approaches that determine the level of aggression, a new formula has been proposed that takes into account the motion amplitude and frequency symmetry for individual columns that scan the human head. As such, the person with the highest level of aggression exhibits maximum symmetry in vibration and fine movement for processing amplitude and frequency vibration images for 20 seconds. At the same time it shows low levels of stress and anxiety.

: Total Amplitude of "I" Thermal Vibration Image of Left Part of Subject

:

From

Maximum value of liver

:

From

Maximum value of the liver

n: number of columns occupied by the target

Similar to the information statistics parameters presented previously, the formula presented allows us to measure the stress level (St) from 0 to 1, and above all, the minimum stress level corresponds to the minimum measurement, In people with stress levels close to one.

The following is a statistical analysis of meaningful vibration image information parameters that determine vibration image acquisition and subsequent anxiety levels. This relates, among other things, to the fast activity signal frequency spectrum construction of amplitude and frequency vibration images.

Unlike the well-known and contradictory existing approaches that determine the level of anxiety, a new formula has been proposed that takes into account the fact that high anxiety increases high frequency spectral density rather than low frequency spectral density.

Tn: level of anxiety

Pi (f): Vibration image frequency spread power spectrum

fmax: maximum frequency of the vibration image frequency spread spectrum

The presented formula, similar to the previously presented information statistics parameters, allows us to measure the level of anxiety from 0 to 1. In addition, the minimum level of anxiety meets the minimum measure, and those with high levels of anxiety have stress levels close to one. The fast signal frequency spread spectrum of the vibration image appears for the operator's or system operator's control.

Another example is to find statistically meaningful informative parameters of the vibration image that determine the vibration image acquisition and then the level of compatibility between the people. Best of all, this consists of a vibration image histogram configuration at each individual frequency.

In contrast to the well-known and contradictory existing approaches that determine the level of compatibility, a new formula that considers the compatibility possibility characterized by a close proximity to the total oscillation frequency histogram of both sides of the distribution normal law Presented.

K: Normalized correlation coefficient of initial histogram

Similar to the parameters presented previously, the proposed formula measures the level of compatibility from 0 to 1. In addition, the minimum measure corresponds to the minimum compatibility (compatibility), and the high level of compatibility measure on both sides appears close to one.

Next is to find a statistically meaningful information parameter of the vibration image that determines the vibration image acquisition and human false level. First of all, it is related to the acquisition of temporary dependence of the maximum amount of vibration image parameters with the least correlation between them.

A new formula has been proposed for the detection of lies that differs from the well-known existing psychophysiological approaches. False in this formula is determined by the change in vibration image parameter measurements compared to the reporting time. The formula presented allows us to determine whether we are verbal and nonverbal. Basically, the linguistic false decision in the time dimension utilizes the time to the start of the test subject's answer. In the case of non-verbal false analysis, it is made by comparing the parameters with one time period and another time period.

The integrated level of change (L) of the psychophysiological state used in the false decision is calculated by the formula:

Pм: change parameter of the higher set threshold

Pc: Vibration image parameter changes when determining false level

K: measured correlation coefficient

n: Number of measurement parameters (may vary from the number of visual parameters)

m: change parameter number

Similar to the parameters presented previously, the formula presented allows us to measure false levels from 0 to 1. In addition, the minimum level of false matches the minimum measure, while the highest level of false has a measure close to one.

This does not mean, however, that the present invention is utilized solely for the measurement of emotional and psychophysiological states of humans presented above. For reference, there are over 200 classifications of human state characteristics according to various classification systems. Above all, the present invention allows us to describe all human conditions through the head micromovement parameters and / or the head vibration image parameters. In psychology, it is an unclear principle to translate the traditional concept of motion into reflex micromovement of the human head using reliable statistical parameters. However, based on the proposed approach, it is possible to determine the human state similarly to the technical information system and to utilize the information parameters to characterize the human state. For example, it is possible to determine the level of human information and thermodynamic entropy according to the formula.

As a basis for the computation of information entropy, a head motion frequency distribution histogram is constructed. The computation of this information entropy follows the following formula.

As a basis for the thermodynamic entropy calculation, a histogram of the frequency distribution of the micro-movement of the head is constructed. The thermodynamic entropy (S) calculation follows the following formula.

These individual information statistics parameters are applied to better identify any emotional state in humans. For example, experiments have shown that there is a high correlation between informational entropy on false levels, and thermodynamic entropy is a state of anxiety in humans. It was found that there is a big connection with.

Based on body and thermodynamic parameters, we were able to more fully characterize and determine human behavior, energy and charismatic aspects. For example, using the vibration image 7.1 version system, based on the frequency histogram representing the highest frequency of vibration image recording, the human energy (E) can be known based on the difference between the mean square error and the maximum frequency.

Quantitative analysis of the reflexive micromovement of the head makes it possible to measure the psychophysiological state of humans more objectively and scientifically and to solve many problems in medicine, psychology, psychology, and everyday life. Through independent experiments with the system developed and the quantitative assessment of the psychological status of passengers at the airport according to aggression, stress, anxiety and potential risk levels, the present invention is positive (more than 90%) to the expert's professional evaluation. I could tell the truth. This confirms the practical feasibility of the present invention.

Hereinafter, with reference to the accompanying drawings will be described in detail a portable device for performing the method of the present invention as described above.

The device shown in FIG. 2 that is functionally blocked can perform the method of the present invention as described above.

The camera 21 includes an imaging device such as a CCD or a CMOS and an A / D converter for digitizing an analog signal therefrom, and the image processor 22 includes an encoder for generating a moving picture of a specific format.

The signal analyzer 23 measures the vibration parameter by the method described above using the image, and generates or extracts psychophysiological information (signal or physiological signal) from the vibration parameter. Here, the vibration parameters include vibration frequency, amplitude, and phase according to the change of position of each part of the subject. The psychophysiological information may include a psychological / emotional / emotional state such as a stable state, an excited state, and a stress state.

Meanwhile, the physiological signal application unit 14 may include a physiological signal processing algorithm for evaluating the mental and emotional state of the subject using the physiological signal and a display for displaying the result. For example, the physiological signal processing algorithm may classify the subject's states into nine emotional states according to, for example, James Russell's two-dimensional emotional model. The display provided in the application unit 24 displays the final result in the form of a text or an image as described above.

Such a device may be implemented through various types of systems. For example, a personal computer equipped with a camera, a portable terminal with a built-in camera, for example, a tablet PC based on a system such as Windows mobile, Android, iOS, Symbian, BlackBerry, Bada, tablet pad, PDA, smartphone In addition, OS-based digital cameras capable of executing internal applications are typical examples.

FIG. 3A is a hardware representation of the apparatus shown in FIG.

Referring to FIG. 3, the physiological signal detecting apparatus 30 includes an image capturing unit having an image capturing element, that is, an A / D converter 32 for digitizing analog video signals from the camera 31 and the camera 31. And a processor 34 for performing image analysis, parameter extraction and physiological signal generation, and a display unit 35 for displaying the result. In addition, the apparatus includes an input device for inputting information from the outside, for example, a key input unit 36 such as a keypad and the like, and a storage unit 33 including a memory used in the above-described image signal processing.

FIG. 3B is a block diagram illustrating a schematic configuration of a smartphone capable of implementing the device of FIG. 2 and illustrating an interaction relationship between the components.

Referring to FIG. 3B, reference numeral 1 is an electronic block including a wireless signal receiver, a transmitter, and an audio / video-signal and a signal-audio / video converter. Reference numeral 42 denotes a digital camera that acquires an image from a subject (subject or subject) and includes an image pickup device, an objective lens, and the like. Reference numeral 43 is a storage unit having a memory for storing the digital image, which is necessary for the operation of the entire smartphone. Reference numeral 44 is a display device for visualizing the user interface and processing results in the form of text and images. Reference numeral 45 is a processor that controls the electronic block, the digital camera, the storage unit, the display device, and the like and synchronizes each function. On the other hand, reference numeral 46 denotes a main body including a keypad for power input and user input required for driving the entire system.

4 is a flowchart illustrating a process of acquiring a biological signal through a camera based on a video according to the present invention, and this process may be the smart phone of FIG. 3A, specifically, FIG. 3B.

Referring to FIG. 4, first, an image of a subject is acquired by a camera 31 and converted into an analog electrical signal (S10 and S20). The electrical signal obtained from the subject's image is an analog signal and is therefore converted into digital image data by the A / D converter 32 (S30).

In a next step, the processor 34 calculates a vibration parameter by analyzing the change over time of each image data (S40). The vibration parameter includes at least one of a vibration frequency, an amplitude, and a phase according to a change in position of each part of the subject. That is, the processor 34 analyzes the position change of each part of the subject to calculate the vibration frequency, the magnitude of the position change (the magnitude of vibration), the phase, and the like of each part. Subsequently, the processor 34 may analyze the difference between the images using a vibration image analysis program, measure a position change with respect to the center of gravity, or calculate (calculate) a vibration parameter (parameter) using a Fourier transform.

The vibration parameter calculation is described in more detail as follows. The processor 34 grasps the motion or vibration of the contour according to the subject's movement from a plurality of successive images and separates the contour into two equal parts (left and right). Then, determine the point indicated by the maximum vibration frequency in two parts of the row divided in half. This frequency determines the color of the corresponding horizontal row of the biosignal image. The average amplitude of the positional variation in each of the two sections of the row divided in half located on the separate contour section determines the size (length) of the biosignal image. Vibration images obtained at each point have certain positive and static characteristics, but integrated biosignal images are associated with the psychophysiological parameters of the human body. This is the case in which the portable device with the camera is fixed to a non-moving support and is not affected by vibration from the outside.

If the handheld device is held by hand, when vibration or movement by the user occurs, it is preferable to go through the process of removing (filtering) the natural vibration component transmitted from the subject's hand. Such filtering may include some or all of the vibration components from the subject acting as noise as well as the subject's hand.

To this end, after A / D conversion of the target image converted into an electrical signal, it is necessary to perform a process of receiving and removing vibration transmitted from the hand as noise before calculating the vibration parameter (S40).

The processor 34 generates a biosignal image based on the calculated vibration parameter (S50). The biosignal image may include an amplitude component and a frequency component. Hereinafter, the amplitude component is referred to as "internal biosignal image" and the frequency component is referred to as "external biosignal image". The concept of this term definition will be understood in the description of FIG. 5 below.

Finally, the processor 34 obtains psychophysiological information of the subject 1 from the calculated vibration parameter (S60). That is, the processor 34 may know the psychological state of the object 20 by analyzing the vibration parameter.

FIG. 5A illustrates that aura, a bioenergy, is radiated around an image of a human body formed of an amplitude component of a vibration image.

As described above, the internal biosignal image expresses the magnitude of the change in position of each part in color. Through this it is possible to visualize the magnitude of the position change of each part of the subject (1). The external biosignal image appears around the internal biosignal image and modulates the average peak vibration frequency into color.

5B shows that a biosignal image, which is bioenergy, is radiated around an actual image of the human body. In FIG. 5B, the internal biosignal image is not represented and only the biosignal image is displayed around the actual image.

6A and 6B show biosignal images in a stable state and an unstable state, respectively. FIG. 6A shows a biosignal image of a subject in a stable or finished state and FIG. 6B in a stress state.

Referring to FIG. 6A, the biosignal image is sufficiently symmetrical in shape and color, and the color of the biosignal image is about halfway between the selected color scale (overall color-green). It can be seen from the biosignal image that the subject is in a stable state.

On the other hand, referring to FIG. 6B, the aura contains a lot of red components in the biosignal image. Therefore, it can be seen that the subject in this state is in an unstable state. When a person is stimulated, for example, exposed to a violent scene through the screen, the subject becomes stressed or aggressive and the color of the biosignal image changes to a reddish color.

FIG. 7A is a distribution graph of frequency components (biological signal images) of a human body vibration image in a stable state, and FIG. 7B is a distribution graph of frequency components (biological signal images) of a human body vibration image in a stress state.

The graph shown in FIG. 6A shows a typical frequency distribution of a person in normal working condition. The results show that the majority of people in a calm state generally have a distribution of distributions similar to a single-mode distribution rule. If the subject is subjected to a certain negative effect such as watching a violence scene on the screen, the state of the subject changes as shown in FIG. 6B. If in fear, stress and aggressive conditions, the mean (medium) value of the frequency distribution (M) shifts towards increasing. In a stable and relaxed state, the mean (middle) value of the frequency distribution value (M) is shifted toward decreasing. The frequency axis (X) can be expressed not only in relative units, but also in real units or time (㎐ or sec.). The distance between the readings is determined by the actual parameters of the camera's rapid processing and the settings of the software (time to accumulate images and the number of images in the processing sequence).

8A is a radial graph (chart) showing the emotional state of a subject according to the method of the present invention, and FIG. 8B shows a result display screen on a smartphone implemented by the present invention. In photographing a subject with a smartphone, it is necessary to position it at a certain distance from the smartphone (camera) and to make the actual image of the subject large enough on the screen.

A smart phone that performs the above functions has a structure as shown in FIG. 9 as is well known, and the method of the present invention is executed after being installed in an application form, and the application is various as described above. It involves a variety of processes, including functions represented by expressions.

To date, various exemplary embodiments of the present disclosure have been described and illustrated in the accompanying drawings. However, it should be understood that these embodiments are only part of the various embodiments. Various other modifications may occur to those skilled in the art.

Claims

Obtaining a video from a subject;
Measuring a vibration parameter of a subject from the video;
Generating a biosignal image based on the vibration parameter; And
Processing the biosignal image to generate psychophysiological response parameters of a subject; Biological signal acquisition method comprising a.
The method of claim 1,
The vibration parameter includes at least one of vibration frequency, amplitude, and phase according to a change in position of each part of the subject,
The measured value of the amplitude is represented by a coordinate value of the change in position of each part.
The method of claim 2,
And removing the natural frequency transmitted from the subject in the vibration parameter.
The method of claim 2,
The biosignal obtaining method, characterized in that the radiation of the bioenergy is displayed around the actual image of the subject in the biosignal image.
By carrying out the method according to any one of claims 1 to 4,
An imaging device for acquiring a video signal from the subject;
An A / D converter converting the video signal into image data;
A processor configured to analyze the image data to measure the vibration parameter and generate a biosignal image from the vibration parameter; And
And a display unit for displaying the biosignal image.
The method of claim 5,
And the imaging device, the A / D conversion unit, the processor, and the display unit are provided by a portable device.
The method of claim 6,
The portable device is an OS (Operating System) based device capable of installing and executing a software application.