KR102090988B1 - How to obtain information about the human psychophysiological state - Google Patents

Abstract

In the present invention, a method for acquiring information about a human psychophysiological state,
A motion parameter measurement means for measuring motion activity by direct or indirect physical contact with a human body part, and a motion parameter conversion sensor mounted inside the motion parameter measurement means and not in direct contact with the human body , The parameter value measured by the motion parameter measuring means is converted into a movement speed and is characterized by analyzing human motion activity.

Description

How to obtain information about the human psychophysiological state

The present invention relates to the fields of biomeasurement, psychophysiology, functional diagnosis, and electronics, and acquires information on the psychophysiological, psychophysical, and physiological characteristics of humans and controls the emotional state, functional diagnosis of humans and animals, and psychological and This is a technique for obtaining psychophysiological status information that can be used for psychophysiological testing.

Today, human psychophysiological or psychophysical information acquisition methods can be categorized into contact and contactless conditions depending on whether or not a sensor is attached. Historically, the contact method of acquiring technically psychophysiological data was developed prior to the non-contact method, which was developed for psychophysiological lie detection above all, and was always used as a method of attaching sensors directly to body parts. Traditional traditional polygraphs or polygraphs have several methods for obtaining psychophysiological information. In general, contact sensors that record the following physiological processes are used for data collection.

-Breathing (pulmonary capacity curve)

-Skin electrical reaction (GSR or Leogram)

-Cardiovascular activity (pulse or heart rate)

-Cardiovascular activity (arterial pressure)

Today, there are many theories that attempt to explain relationships in psychological and physiological processes, and their relevance is undoubtedly described [preceding technical documents 1, 2, hereinafter referred to as document numbers]. Many years have passed since the development of the polygraph by John Larson, a medical scientist from the University of California in 1921 [3], but attempts to improve information in human psychophysiological information scans are still ongoing.

The method of acquiring contactless information about a psychophysiological state is based on observing human microscopic movements or movements. And it is the achievements of Cesenov [4] and Darwin [5] that are the scientific basis for the practical implementation of these techniques. The technical feasibility of this technique has in fact emerged with the development of television and computer technology [1, 2]. Darwin's algorithm transformation is still ongoing in the analysis of micro-motion algorithms [6, 7]. In addition, the psychophysiological understanding of movement activity was realized by vibra image technology [8, 9].

The main task in improving information in psychophysiological aspects is to increase the correlation between human brain activity and sympathetic nervous system activity and pre-measured physiological processes. The main limitation in applying physiological aspects to psychophysiological tests is that interference prevention related to signal detection is not properly performed. In technical terms, improving the informationality of psychophysiological signal detection is related to increasing the dynamic range of measurement parameters and improving the signal-to-noise ratio relationship.

For example, the contact EEG scanning and processing method for obtaining psychophysiological information is quite different from the control of brain activity [10, 11], but it is necessary to establish an appropriate laboratory environment because interference prevention, a limiting factor in testing, is not achieved.

A method of controlling movement activity using an acceleration sensor attached to a human body part is well known [12, 13]. These techniques are usually used in the medical field to control the movement activity of patients, but the main task of the technique is macroscopic movement control related to the total energy consumption of the physiological processes of the body organs, so it is not used to acquire psychophysiological information. . This is because macromovements are not directly related to psychophysiological processes.

Although there is a technique for acquiring and processing voice information in a non-contact manner in the analysis of a human emotion state that is stable against relatively various interferences, it has a low information relationship with the sympathetic nervous system activity and has high error potential, so its use is limited.

The method of acquiring human psychophysiological information, including measuring the characteristics of human mobility, is well known, and acquires information on the psychophysiological state of living organisms based on the result of measuring the movement activity according to the screen representing the motion signal of the head. And processing characteristics and processing signal data that converts spatial and temporal distributions of the head movements of living organisms into statistical information, and converts vibra image information statistical parameters into quantitative characteristics of the psychophysiological state of living organisms. Based on the converted data, information on the psychophysiological state of the organism is obtained.

This technique [16] is used as a basic framework. By scanning the fine movements of the human head using a screen scan, transforming the image into a vibra image, and acquiring information statistical psychophysiological parameters, information on the human psychophysiological state can be obtained. The vestibular organs and the vestibular system are responsible for maintaining the mechanical equilibrium and control the fine movements of the head. Since the human vestibular system is functionally related to all other physiological activities of humans, its use becomes the most useful information when analyzing psychophysiological information [17]. This typical technique automatically and very objectively records information about human movement activity, and the relevant information is substituted into mathematical formulas and converted into information physiological numerical parameters that characterize human functions and emotional states. However, this is a non-contact television technique, and the brightness (contrast) sensitivity to the object is important, and a large processor is required for signal processing. The change in brightness (contrast) can be perceived as the vibration of the object, but in the absence of light, applying these techniques is pointless and the camera must be fixed.

Alekseyev. Psychophysiological lie detection. Metodolgia. M, 2011, 108p. 2. Matchanov. Aglobin. Toolological 'Lie Detection', Nuance, 2004, 464p. 3. https://en.wikipedia.org/wiki/john_Augustus_Larson 4. Sechenov. Elements of thinking. St. Petersburg, 2001. 416p. 5. Charles Darwin. About the expression of emotions in humans and animals. Peter, 2001. 6. Paul Eckman. Lying psychology. Peter, 2003. 7. A. J. Fridlund, Human facial expression. An evolutionary view. San Diego, CA, Academic Press. 8. RU 2187904, priority on December 19, 2000. Image conversion method and means. Minkin et al. 9. RU 2289310 Priority on 16 February 2004. How to get information about the psychophysiological state of an organism 10.Method for psychophysiological detection of deception through brain function analysis US 10 / 213,089 Lawrence Farwell 11.Method an apparatus for brain fingerprinting, measurement, assessment and analysis of brain function, EP1401330 Lawrence Farwell 12.A guide to assessing physical activity using accelerometry in cancer patients J.M.Broderick & J.Ryan & D.M.O? Donnell & J.Hussey. Springer-Verlag Berlin Heidelberg 2014. 13.Accelerometry analysis of physical activity and sedentary behavior in older adults: a systematic review and data analysis / E.Gorman & H.M.Hanson & P.H.Yang & K.M.Khan & T. Liu-Ambrose & M.C. Ashe Received: 8 March 2013 / Accepted: 23 August 2013 / Published online: 17 September 2013. #The Author (s) 2013.This article is published with open access at Springerlink.com 14.Apparatus and methods for detecting emotions US6638217 B1 Amir Liberman. 15.Detecting emotions using voice signal analysis US7222075 Valery A.Petrushin. 16. Prototype. RU 2510238, Priority October 26, 2009, How to obtain information about the psychophysiological state of an organism. Minkin. 17.RU 2515149, Minkin, Blank M.A, Blank O.A, Prostate Cancer Screening Method, Priority 2012.02.06 18. Non-electrical electricity measurement, 5th edition printing, Nowitzki, Energia, 1975 19. Lorenz 'Aggression, Progress 20. Tamar 'Basic of Sensor Physiology', Moscow, 1976 21. Capacitive Microelectromechanical Inertial Sensitive Factor Production Method (Patent RU 2207658): Mocrof et al. 22.Dissolved wafer fabrication process and associated microelectromechanical device having a support substrate with spacing mesas US6143583. Ken Maxwell Hays. 23.Method of manufacturing a vibrating structure gyroscope US 6471883 Christopher P Fell. 24.Game drum having micro electrical mechanical system pressure sensing module US8287376 Hai Lan et.al. 25.Operating apparatus for game machine US 7479064 B2 Noboru Wakitani etc. 26.Robust step detection using low cost mems accelerometer in mobile applications, and processing methods, apparatus and systems US 20130090881, Jayawardan Janardhanan et.al. 27.Ceraser, Tyrone Gene, The Estimation of Caloric Expenditure Using Three Triaxial Accelerometers. PhD diss., University of Tennessee, 2012. 28.J. Kate Lyden, Sarah L. Kozey, John W. Staudenmeyer Patty S.Freedson, A comprehensive evaluation of commonly used accelerometer energy expenditure and MET prediction equantions, Eur J Appl Physiol (2011) 111: 187-201 29. Nowitzki, Jograph, measurement result error evaluation, Energo Atom, 1991 30.Sensors Overview, published by Google, February 2015 http://developer.android.com/guide/topics/sensors/sensors_overview.html 31. Human psychological state control system technology, Vibra Image 8 PR, Elsis Publishing, http://www.psymaker.com/downloads/V18_1ManualRus.pdf 32. RU2384967 Zzcúlin Alexandre Constantinovic (RU), Pachmi Yonkiv Subhiević (RU), Perespelov Anatoly Vitalevich (RU) image stabilization method 33. US 8,896,713 B2 Motion-based video stabilization Brandon Corey et.al. 34.US 8,159,541 B2 Image stabilization method and apparatus, Stuart McLend. 35.US 2011/0234825 Accelerometer / gyro-facilitated Video Stabilization, YIIXIII LIU et.al.

An object of the present invention is to provide a method for acquiring information on a psychophysiological state that can increase convenience, accuracy, and reliability of a method for measuring a psychophysiological state parameter of a human.

In the present invention, a method for acquiring information about a human psychophysiological state,

A motion parameter measurement means for measuring movement activity by direct or indirect physical contact with a human body part, and a motion parameter conversion sensor mounted inside the motion parameter measurement means and not in direct contact with the human body , The parameter value measured by the motion parameter measuring means is converted into a movement speed and is characterized by analyzing human motion activity.

In addition, the motion parameter measurement means is a mobile cell phone, the motion parameter conversion sensor is a micro electromechanical sensor mounted on the mobile cell phone, characterized in that the analysis of the human psychophysiological or functional state is made by the mobile cell phone do.

In addition, the microelectromechanical sensor records the temporal dependence of the movement speed and analyzes the correlation between the frequency signal (V) and the vibra image frequency signal (F1) obtained by the camera from the temporal dependence of the movement speed. Characterized by the aggregation of physiological or functional state parameters,

When the psychophysiological or functional state parameters are aggregated, the movement speed parameter data obtained from the mobile cell phone microelectromechanical sensor is matched with the mobile cell phone camera vibra image processing data, and the values displayed by the vibra image value and the microelectronic device. It is characterized by acquiring a correction signal for a vibra image by grasping the relationship.

The present invention measures a human motion activity by means of a motion parameter measurement means and converts it into a motion speed to analyze the motion activity characteristics, thereby improving the convenience, accuracy, and reliability of the human psychophysiological state parameter measurement method. It has the effect of providing a method for obtaining information about a physiological condition.

FIG. 1 shows a method of acquiring information on a psychophysiological state of a human using a contact motion parameter measurement device and a non-contact vibra image method.
2 (a, b) shows parameter dependence determined by a contact-motion device and a non-contact vibra image method in an active psychophysiological state. 2A shows parameter dependence over time, and FIG. 2B shows correlations between parameters.
3 (a, b) shows a parameter dependency determined by a contact motion device and a non-contact vibra image method in a passive psychophysiological state, and FIG. 3a shows a parameter dependence over time and a parameter in 3b Cross-correlation is presented.

Hereinafter, a preferred embodiment of the present invention will be described in detail.

Human psychology, including the aggregation of psychophysiological or functional state parameters based on measurement of human motion activity characteristics and analysis of human movement activity, and measurement of human movement activity characteristics The technical task is solved by applying a method of measuring motion parameters that directly or indirectly makes physical contact with the human body to obtain information about the physiological state. The parameter conversion sensor is mounted inside the motion parameter measurement means so that the motion parameter conversion sensor does not come into direct contact with the human body part. speed of motion).

In the case of the present invention, a mobile phone or other processor device (electronic device) is used as a means for measuring motion parameters, and an individual microelectromechanical sensor mounted on the phone is used as a device for converting motion parameters, and analysis of a human psychophysiological or functional state Consists of a mobile phone processor that utilizes a special program pre-stored in the mobile phone.

The cell phone microelectromechanical sensor records the temporal dependence of the motion speed parameter, and the psychophysiological or functional parameter based on the motion measurement of the body part is based on the temporal dependence of the motion speed parameter obtained from the microelectromechanical sensor. It is aggregated by analyzing high or low frequency correlations.

Human vibra images obtained from cell phone cameras are obtained from mobile phone cameras to obtain data on human motion speed parameters acquired by cell phone microelectromechanical sensors to grasp information about human psychophysiological states when counting psychophysiological or functional state parameters. vibraimage) In order to understand the vibra image correction signal by matching with the processing data, the relationship between the current vibra image signal value and the current microelectronic device signal value is grasped.

With this technique, the physical characteristics of the movement and movement activity of the object can be directly analyzed without additional light signal conversion, and the accuracy of human movement activity and vestibular activity parameter identification can be improved. As such, the main parameters of physical motion (movement, speed, and acceleration) have a simple differential relationship [18]. On the basis of these parameters, the accuracy of counting all motion parameters increases when processing data with the means for measuring motion parameters. In this case, there is no direct contact between the human body part and the motion parameter device, and a sensor can be mounted inside the small measuring device to obtain information about the psychophysiological state. The motion velocity parameter showed the highest psychophysiological information among all the motion parameters, which is an unexpected result as most existing studies related to human motion energy consumption are based on accelerated aggregation [12, 13].

It is well known that micro-movement dependence on psychophysiological conditions is characterized by vestibular emotional reflection [19]. The human vestibular organ analyzes the imbalance of all body parts in the 3D state with the help of a special receptor [20] and reflexively manipulates the body muscles for unbalanced movement in the opposite direction. In fact, motion parameter change sensors (accelerometers, vibrating devices, gyroscopes) called microelectromechanical systems have the same function as the vestibular organs [21, 22]. Modern motion sensors measure acceleration, corner or motion, and data are converted into independent electrical signals that take into account movement in all directions, usually with the aid of technological devices along three mutually perpendicular axes [23]. As such, virtually every cell phone contains several sensors with functions similar to those of the human vestibular organ, so if the movement of the cell phone follows human motion, it can be used to control the psychophysiological state of humans. Today, technical operation tasks such as screen switching or game applications have been solved by using microelectromechanical system sensors in mobile phones [24, 25]. In addition, the use of microelectromechanical system sensor information for counting the number of steps of a user according to a regular change of the accelerometer signal [27, 28] or caloric consumption counting [27] is an example similar to psychophysiological parameter measurement.

The key to the psychophysiological informationality of sensor signals mounted on mobile devices is the fact that the microelectromechanical sensors are randomly mounted on human body parts. In the vibra image technology [8, 9], vertical movement of the body skeleton is required, and as the human head is an ideal object according to body dynamics, body movement is naturally controlled and all movements are reflected. However, the mobile phone in the pants or jacket pockets primarily reflects the movement of the upper body in direct contact with the mobile device.

Today, the technical approach of mounting existing physical sensors (acceleration, movement, vibration) requires strong physical contact when combining the sensor with the study object. Naturally, when a mobile device is installed at a random location on a subject's clothing, a strong physical contact with a body part is not required, and the random contact location does not guarantee the information of movement activity.

However, the present inventors do not have direct physical contact, but use a speed that allows fine movement to be controlled by an informational signal in connection with arbitrary mounting on a body part, such as a motion sensor such as a microelectromechanical sensor attached to a general mobile device. It was able to prove experimentally that it was possible to acquire psychological signals in information statistics. Setting the basic information in obtaining psychophysiological signals is not the signal instantaneous value of the measured physical value (contact made at an arbitrary position in the body's position may be delayed and may not fall due to the movement of the head). This is because it is a statistical parameter integrated data reflecting the temporal dependence of physical values. In addition to this, the experimentally proven fact is that the fine movement and speed characteristics of various body parts depend on the psychophysiological state of the subject and are not affected by the movement activity itself or macroscopic movement.

In an active psychophysiological state with high aggression, stress, and anxiety, the body's micro-motion characteristics (vibration from a physical point of view) are determined by the psychophysiological process, and the movements of the shoulders, chest, and hips are highly correlated with the fine movements of the head. There was. However, in a passive psychophysiological state, this association decreases when body movement is determined only by a psychophysiological process. The technical decision in this regard is new, technically unpredictable to the general expert, and is an industrially available part of the present invention.

These techniques enable the analysis of the psychophysiological state of a human using a mobile device by utilizing a motion device signal including a standard mobile device microelectromechanical device. In addition, by using a wireless interface such as Wi-Fi or Bluetooth, it is possible to analyze the human psychophysiological state on mobile devices as well as other processors. In addition to this, the informationality of psychophysiological information is determined by the accuracy of the movement speed conversion and the informational signal processing method performed by the measurement means itself, not by the position of the body's motion sensor and the body contact method [16, 29].

Let's look at the suggestions for acquiring information about the psychophysiological state of a human being, which consists of various methods of measuring motion parameters.

The characteristics of human motion activity are identified by video images using an external camera (vibra image technology) and motion parameter measurements using a Samsung mobile phone model S4 (motion parameter contact method) equipped with the Android 4.3 operating system. The cell phone microelectromechanical signal [30] is processed by the Vibra Image 8.1 program produced by Elsis Co., Ltd. [31]. The Vibra image program visualizes and correlates the correlation between signals acquired from an external device and vibra image parameters (including human psychophysiological parameters determined by vibra image technology). In addition, the Vibra Image 8.1 program analyzes the microelectromechanical signal of the mobile phone transmitted through the Wi-Fi interface using the Android OS standard device [30]. The cell phone microelectromechanical sensor data transmission program [30] is stored and stored in the cell phone in advance. Subject 1 (Fig. 1) sits on chair 2 (Fig. 1) in front of camera 3 (Fig. 1) with computer 4 (Fig. 1) monitor and cell phone 5 is placed in various positions as in Fig. 1 Lose.

In order to confirm the psychophysiological information of the signal obtained from the microelectromechanical sensor, we will examine the visual signal data displayed on the computer screen on the interface of the Vibra Image 8.1 program. FIG. 2 shows a fast signal F1 (determined by a camera according to a vibra image technology) and a signal V (determining the total velocity of motion of the microelectromechanical sensor of the mobile phone accelerometer) as a basic informational signal. The first cell phone is located on the subject's head. In this case, when there is a single physical value, that is, when there is movement of the human head, the movement speed is measured by two devices: a vibra image and a microelectromechanical accelerometer. The Vibra image program processes these signals and reveals a highly correlated relationship independent of the subject's psychophysiological state.

Let's take a look at a case where the phone is moved from the head to another location, such as an upper chest pocket. In this case, various body measurements are made, the camera still illuminates the subject's head, and the mobile phone located in the upper chest pocket measures the movement speed of the subject's chest shirt. In this case, there is a noticeable high correlation between the F1 and V parameters, and the subject can be considered to be in an active state of movement. Under the active motor functional state, it is possible to grasp the psychophysiological state of the human. In this case, energy consumption exceeds 3 kcal / min and [27, 28] not only physiological processes but also active psychological or emotional activity can be known. For example, energy consumption and metabolism are not only the physiological processes of the body organs, but also the psychophysiological processes, as the energy consumption for the physiological process of a sedentary person does not exceed the level of 2 kcal / min [27, 28]. It can be seen that it is determined.

2A shows the temporal dependence of the F1 and V signals appearing on the subject in an active functional state where the cell phone is located in the top pocket. In this case, the first part of the temporal dependence appeared to be in a minimally motile state (no macroscopic motion), but this does not mean that the subject is passive. The left part of the graph is virtually no different from the right part in energy consumption. In order to mention the difference, the subject showed slight movement in the left part of the graph and the macro movement in the right part (after 9 seconds) of the graph. Visually, the fact is that both signals are highly correlated, which is confirmed by the vibra image program numerical aggregation, in which these curves are represented by a 0.95 Pearson correlation coefficient. These signals are displayed in relative units. In this case, the change trend of all signals is informative, not the absolute value of the body obtained during measurement. The correlation dependence of F1 and V values is shown in Figure 2b. Interestingly, the two psychophysiological states (fine motion and macroscopic motion) actually do not change the level of correlation between the vibration parameters of the human head and chest. This similar signal-to-signal dependence was observed even when the cell phone was placed in a pocket of clothes at various locations in the test subject.

Similar dependence between signals acquired by vibra imaging technology and motion parameter measurement devices is observed not only in the initial signals of motion devices, but also in statistical information in the case of active psychophysiological conditions [16]. An example of selecting an anxiety T index, such as a correlation between high and low frequencies within a vibra image frequency signal range, is used as a signal for comparison [16]. Signals aggregated in a similar way have a high correlation with anxiety indicators aggregated based on vibra images, but in this case, they are based on the range obtained from the movement speed of the mobile phone gyroscope and accelerometer sensor. Moreover, this high relevance has little dependence on the location of the cell phone, such as the head or the top or trouser pocket. A similar level of anxiety (even in clothes) was observed, even when the mobile phone was held in the hand and not very mobile.

In humans with passive psychophysiological conditions of less than 2kcal / min of energy consumption (energy consumption is mainly determined by physiological processes), the correlation dependence is slightly different. When the subject's cell phone location moves to a different location, the movement dependence characteristic of the head region relative to the movement of other body parts changes significantly. Fig. 3a shows the temporal dependence of the F1 and V signals of the test subject in which the mobile phone shows a passive functional state in the top pocket. The first part with respect to temporal dependence showed minimal mobility, but this does not mean that the subject is in a passive state. In the left part of the graph, there is virtually no difference in energy consumption from the right part, but to find the difference, the subject showed fine motion in the left part and macroscopic motion in the right part (after 17 seconds). In this regard, it is not easy to visually evaluate the correlation level between parameters, and the Vibra image system showed a significantly low correlation coefficient (less than 0.2) between signals.

The correlation dependence of F1 and V values in a passive psychophysiological state is shown in Figure 3b. Interestingly, the low level of correlation between vibrational parameters of the human head and chest region in two psychophysiological states (fine motion and macroscopic motion) does not change, and macroscopic motion does not result in its augmentation. A low similarity dependency between these signals was observed when the mobile phone in the subject's pocket in a passive state was moved to various locations.

For example, the possibility of acquiring psychophysiological information about an active psychophysiological state of a human was found by using a means of measuring motion parameters having direct or indirect physical contact with a human body part. In this case, since the motion parameter conversion sensor is attached to the inside of the motion parameter measurement device, there is no direct contact with the human body part, and the measured motion parameter value is then converted to the motion speed. The lack of correlation between the motion parameters of the head and body parts informally characterizes the passive psychophysiological state of humans.

The following experiment was conducted to improve the accuracy of simultaneous measurement of the motion parameters of the object. Microsoft Surface Pro 3 i5 128Gb Oc Using a vibra image 8.1 program installed on a Windows 8 PC, the vibration frequency of the object was determined using standard vibra image technology. A black-and-white circular hemisphere with contrast that exhibits vibration at a frequency of 5hz was selected as an object, but the experiment was conducted with a screen displayed on another computer monitor. At this time, the Microsoft Surface PRO PC was fixed for mechanical safety. In this case, the measurement result of the object's motion frequency will be 5 ± 0.1 hz, which is quite similar to the proposed moving frequency.

In addition to this, the experiment was conducted at a distance between the monitor and the oscillation circular half-section, almost the same as holding a cell phone in hand. In this case, although the video image stabilization method was well observed, the measurement frequency number showed a fairly large result distribution, and the measurement error was large in nature. The well-known image stabilization method [32, 33, 34, 35] stabilizes macroscopic movements to some extent, but nevertheless, since the micro-motion stabilization algorithm works on the body parts, the camera's micro-motion and vibra image errors increase. Is caused. The measurement result will be 5 ± 2 hz level.

The vibration frequency determination program of the target object was changed by adding the signal acquisition function of the mobile device microelectromechanical sensor signal and the simultaneous recording of the vibra image data. In order to obtain a modified vibra image signal, it is necessary to grasp the relationship between the current vibra image signal value and the current microelectronic device sensor signal value. In this case, the object vibration frequency measured by the modernized program will be virtually 5 ± 0.15 hz. As a result of this experiment, it can be seen that synchronization of motion parameter data obtained from microelectromechanical sensors and cameras increases the accuracy of motion activity measurement and naturally increases the accuracy of human psychophysiological state identification.

The above example showing the specific experimental progress shows the possibility of a practical invention, but the above technique of the present invention is not limited to the above example. Technical decisions and techniques of the present invention for obtaining psychophysiological information of users of mobile devices and other devices may be utilized. For example, a special program that can be installed on a mobile device to send data over the Internet for data processing and storage will enable access to microelectromechanical sensor data. This method can be used to obtain physiological information about a health condition such as the cardiovascular system, etc., and may also signal when normal cardiac activity is out of range.

The use of microelectromechanical system sensor data for mobile devices to acquire information about the psychophysiological and physiological state of humans is differentiated in terms of convenience and reliability, and greatly expands the field of mobile device applications.

In the above, the present invention has been described with reference to the above embodiments, but it is of course possible to perform various modifications within the technical scope of the present invention.

Claims (4)

In the information acquisition method for obtaining the human psychophysiological state information using a camera and a micro-electromechanical,
A motion parameter measuring means for measuring movement activity through direct or indirect physical contact with a human body part,
A motion parameter conversion sensor mounted inside the motion parameter measurement means and not in direct contact with the human body;
The parameter value measured by the motion parameter measuring means is converted into a motion speed to analyze the human motion activity,
The motion parameter measuring means is a mobile phone or an electronic device,
The motion parameter conversion sensor is a micro electromechanical sensor mounted on the mobile phone or electronic device,
The microelectromechanical sensor records the temporal dependence of the speed of movement,
A human being characterized in that a psychophysiological or functional state parameter is aggregated by analyzing a correlation between the frequency signal (V) and the vibra image frequency signal (F1) obtained by the camera in the temporal dependence of the movement speed. Methods of obtaining information about psychophysiological conditions


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