KR20170133346A - How to get information about the psychophysiological state of human - Google Patents

Abstract

In the present invention, a method for acquiring information on the psychophysiological state of a human is provided,
A movement parameter measuring means for measuring a movement activity by directly or indirectly making a physical contact with a human body part; a motion parameter switching sensor mounted inside the motion parameter measuring means and not in direct contact with a human body; And the parameter values measured by the motion parameter measuring means are converted into a motion velocity to analyze human motion activity.

Description

How to get information about the psychophysiological state of human

The present invention relates to the field of biometry, psychophysiology, functional diagnostics, and electronic engineering, and relates to the acquisition of information on the psychophysiological, psychosomatic, and physiological characteristics of human beings and the control of emotional states, functional diagnosis of humans and animals, This is a description of how to obtain psychophysiological status information that can be used in psychophysiological tests.

Today, human psychophysiological or psychosomatic information acquisition methods can be classified into contact type and non - contact type according to whether sensor is attached or not. Historically, the contact-type method of acquiring technically psychophysiological data was developed prior to the non-contact type, which was developed primarily for psychophysiological lie detection and was always used in a way that the sensor was always attached directly to the body part. Conventional traditional polygraph detection or polygraphing has several ways of obtaining psychophysiological information. Typically, data collection uses contact sensors to record the following physiological processes:

- Respiration (lung capacity curve)

- Skin electrical response (GSR or Leogram)

- Cardiovascular activity (pulse or heart rate)

- Cardiovascular activity (arterial pressure)

There are many theories to explain the relationship in psychological and physiological processes today, and their relevance is undoubtedly [cited in Prior Art Documents 1 and 2, below. Although many years have passed since John Larson, a medical scientist from the University of California in 1921, developed a polygraph [3], attempts to improve the intelligence of human psychophysiological information scans are still being made.

The method of acquiring non-contact information on the psychophysiological state is based on observing human fine movements or movements. And the scientific basis of the practical implementation of these techniques is the work of Sézinoff [4] and Darwin [5]. The technological feasibility of this technique has indeed emerged with the development of television and computer technology [1, 2]. Darwin's algorithmic transformations are still being studied today for the analysis of fine motion algorithms [6, 7]. In addition, the psychophysiological understanding of movement activity has been embodied in the Vibra image technology [8, 9].

The main challenge in enhancing the intelligence of the psychophysiological aspects is to increase the link between human brain activity and sympathetic activity and the measured physiological processes. One of the main limiting factors in applying physiological aspects to psychophysiological testing is the lack of interference prevention with respect to signal detection. Technically, the enhancement of the intelligibility of psychophysiological signal perception is related to the enhancement of the dynamic range of the measurement parameters and the improvement of the signal-to-noise ratio relationship.

For example, contact-type EEG scans and treatments for obtaining psychophysiological information [10, 11] are quite different from brain activity control, but an appropriate laboratory environment should be established because interference is not a limiting factor in testing.

Motion control methods using acceleration sensors that attach to human body parts are well known [12,13]. Although these techniques are usually used to control the patient's movement activity in the medical field, the main task of the technique is not to be used to acquire psychophysiological information because it is a macro-movement control related to the total energy consumption of the body's physiological processes . This is because macroscopic movement is not directly related to psychophysiological processes.

Although there is a technique for acquiring and processing voice information in a noncontact manner in a stable human emotional state analysis with a relatively wide range of interference, it has a low informational relationship with sympathetic nervous system activity and its utilization is limited as the probability of error is high.

Human psychophysiological information acquisition methods including human activity measurement are well known and information on the psychophysiological state of living organisms is obtained based on the result of measuring the movement activity according to the screen showing the head movement signal And processing the signal data that transforms the spatial and temporal distribution quantitative parameters of the head movements of the creature into informational statistical parameters and analyzes the statistical parameters of the vibra image information into the quantitative characteristics of the psychophysiological state of the organism Obtain information on the psychophysiological state of organisms based on the transformed data.

This technique [16] is used as a framework. It can acquire information about the psychophysiological state of human by scanning the fine movement of the human head using a screen scan, transforming the image into a vivid image, and acquiring information statistics psychophysiological parameters. The vestibular organs and electrograms function to maintain the equilibrium state and control the fine movement of the head. Since human precursors are functionally related to all other physiological activities in humans, their use is the most useful information in the analysis of psychophysiological information [17]. These typical techniques automatically and very objectively record information about human motion activity, and related information is transformed into mathematical formulas and converted into physiological numerical parameters that characterize human function and emotional states. However, this is equivalent to a non-contact television technique, in which brightness (contrast) sensitivity is important to the object and a large capacity processor is required for signal processing. Changes in brightness (contrast) can be perceived as vibrations of the subject, but in the absence of light, applying this technique is meaningless and the camera must be firmly fixed.

1. Alexeyev. Psychophysiological lie detection. Metodologia. M, 2011, 108p. 2. Machanov. Agrobin. Instrumental 'Lie Detection', Nuance, 2004, 464p. 3. https://en.wikipedia.org/wiki/John_Augustus_Larson 4. Szechenoff. Factor of thinking. St. Petersburg, 2001. 416p. 5. Charles Darwin. Expression of Emotion in Human and Animal. Peter, 2001. 6. Paul Eckman. Lie psychology. Peter, 2003. 7. A. J. Fridlund, Human facial expression. An evolutionary view. San Diego, CA, Academic Press. 8. RU 2187904, December 19, 2000 Priority. Image switching method and means. Minkin 9. RU 2289310 2004.02.16 Priority. How to obtain information on 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, 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 by 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 date October 26, 2009, Method of obtaining information on the psychophysiological state of an organism. Minkin. 17. RU 2515149, Minkin, Blanke M.A, Blanke O.A, Method of diagnosing prostate cancer, Priority date 02.02.06 18. Non-Electricity Measurement, 5th Edition, Nowitzki, Energia, 1975 19. LORENTZ 'Aggression, Progress 20. Tamar 'Basis of Sensor Physiology', Moscow, 1976 21. Capacitive Microelectromechanical Inertia Sensitive Factor Production Method (Patent RU 2207658): Mokroff et al. 22. Dissolved wafer fabrication process and associated microelectromechanical device having a supporting 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 accelerometers in mobile applications, and processing methods, apparatus and systems US 20130090881, Jayawardan Janardhanan et al. 27. Ceaser, 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 Accelerometer Energy Expenditure and MET Prediction Equantions, Eur J Appl Physiol (2011) 111: 187-201 29. Nowitzki, Joe Graff, Measurement error evaluation, Energo Atom, 1991 30. Sensors Overview, Google Publishing, February 2015 http://developer.android.com/guide/topics/sensors/sensors_overview.html 31. Human hearing emotional state control system technology, Vibra Image 8 PR, Elsys Publishing, http://www.psymaker.com/downloads/V18_1ManualRus.pdf 32. RU2384967 Tsjurdyn Alexandr Constantinović (RU), Parchimov Kivu Svěhović (RU), Perezpelov Anatoly Vitalávich (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.

The present invention aims to provide a method for acquiring information on psychophysiological conditions that can improve the convenience, accuracy, and reliability of the method of measuring the psychophysiological state parameters of human beings.

In the present invention, a method for acquiring information on the psychophysiological state of a human is provided,

A movement parameter measuring means for measuring a movement activity by directly or indirectly making a physical contact with a human body part; a motion parameter switching sensor mounted inside the motion parameter measuring means and not in direct contact with a human body; And the parameter values measured by the motion parameter measuring means are converted into a motion velocity to analyze human motion activity.

The motion parameter measurement means may be a mobile phone, and the motion parameter change sensor may be a microelectromechanical sensor mounted on the mobile phone, and the psychophysiological or functional state of the human being may be analyzed by the mobile phone. do.

The microelectromechanical sensor records the temporal dependence of the motion velocity and analyzes the correlation between the frequencies in the temporal dependency of the motion velocity to collect psychophysiological or functional state parameters.

When the psychophysiological or functional state parameters are summarized, the motion parameter data obtained from the mobile handset microelectromechanical sensors are compared with the mobile phone camera vibra image processing data, And acquires a vibra image correction signal.

The present invention relates to a method and apparatus for measuring the motion activity of a human by measuring the motion activity of a human by means of the motion parameter measuring means and converting the motion activity characteristic into a motion velocity, There is an effect of providing a method of acquiring information about a physiological state.

FIG. 1 shows a method of acquiring information on the psychophysiological state of a human being using a contact-type motion parameter measurement device and a contactless vira imaging method.
Figures 2 (a) and (b) show the parameter dependence determined by the contact-type movement device and the contactless vira imaging method in active psychophysiological state. FIG. 2A shows parameter dependency over time, and FIG. 2B shows correlation between parameters.
3 (a) and (b) show the parameter dependence determined by the contact-type movement device and the contactless vibraimage method in the passive psychophysiological state. Fig. 3a shows the parameter dependency with time, Correlation is suggested.

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

Human psychological or functional state parameters based on measurement of human motion activity characteristics and analysis of human motion activity, human mental states including measurement of human movement activity characteristics The technical problem is solved by applying the motion parameter measurement method in which the information about the physiological state is directly or indirectly physical contact with the human body. A parameter conversion sensor is mounted inside the motion parameter measurement means so that the motion parameter conversion sensor is not in 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 motion parameter measuring means, and a separate microelectromechanical sensor mounted on a mobile phone is used as a motion parameter switching device. The psychophysiological or functional state Is made up of a mobile phone processor using special programs pre-stored in the mobile phone.

The mobile phone microelectromechanical sensor records the temporal dependence of the motion rate parameter. The psychophysiological or functional parameter based on the motion measurement of the body part is based on the temporal dependence of the motion rate parameter acquired by the microelectromechanical sensor And the high or low frequency correlation is analyzed.

In order to obtain information on the psychophysiological state of the human being when the psychophysiological or functional state parameter is counted, data on the human motion velocity parameters acquired by the mobile phone microelectromechanical sensors are obtained from the human vira image vibraimage) and look at the relationship between the current vibra image signal value and the current microelectronic signal value to determine the vibra image correction signal.

With this technique, it is possible to directly analyze the physical characteristics of movement and movement activity of object without additional light signal conversion, and to improve the accuracy of human motion activity and precise activity parameter recognition. Thus, physical motion (movement, velocity, acceleration) has a fairly differential relationship [18]. Based on these parameters, the accuracy of all motion parameter aggregation increases during data processing with motion parameter measurement. In this case, there is no direct contact between the human body part and the motion parameter device, and the sensor can be mounted inside the small measuring device to obtain information about the psychophysiological state. The motion rate parameter showed the highest psychophysiological information among all motion parameters, which is unexpected as most previous studies on human motion energy consumption are based on accelerations [12,13].

It is well known that fine motion dependence on psychophysiological status is characterized by vestibular affective reflexes [19]. The human vestibular organ analyzes the imbalance of all body parts in the 3D state with the aid of a special receptor [20] and reflexively controls the body muscles for unbalanced movement in the opposite direction. In fact, a motion parameter conversion sensor (accelerometer, vibration device, gyroscope), called a microelectromechanical system, has the same function as the vestibular organ [21, 22]. Modern motion sensors measure acceleration, corners, or motion, and data is converted to independent electrical signals, usually considering motion in all directions with the help of technology devices along three orthogonal axes [23]. Thus, virtually every cell phone contains several sensors with similar functions to those of the human vestibule, so that if the movement of the cell phone follows the movement of the human, it can be used to control the psychophysiological state of the human being. The use of microelectromechanical system sensors in mobile phones today has solved technical operational challenges such as screen switching or game applications [24, 25]. Examples of similar psychophysiologic parameter measurements include calorie consumption calculations [27, 28] or the use of microelectromechanical system sensor information to compute the user's number of gaits according to periodic changes in the accelerometer signal [26].

The key to the psychophysiological information of the sensor signals mounted on the mobile device is that the microelectromechanical sensor is mounted at the human body part arbitrarily. In Vibra image technology [8, 9], vertical movement of body skeleton is required and body movement is controlled naturally and all movements are reflected as the human head part according to body dynamics is ideal object. However, a cellphone in a pants or jacket pocket reflects the movement of the upper body in direct contact with the mobile device.

Today, the technological approach of mounting existing physical sensors (acceleration, movement, vibration) requires strong physical contact when combining the sensor to the study subject. Naturally, when a mobile device is installed at an arbitrary position of a subject's clothes, a strong physical contact with a body part is not achieved, and an arbitrary contact position does not guarantee the information of motion activity.

However, according to the present invention, when the speed at which fine movement is controlled by an information signal is arbitrarily applied to a body part without direct physical contact, a motion sensor such as a microelectromechanical sensor attached to a general mobile device It is possible to experimentally demonstrate that it is possible to obtain an informational statistical psychophysiological signal. It is not the instantaneous value of the measured physical value that is fundamental to obtaining the psychophysiological signal (the contact made at any position of the body quadrant may be late and may not match the movement of the head) This is because statistical parameter integrated data reflecting the temporal dependence of physical values. Experimental evidence also suggests that the micro-movement and velocity characteristics of various body parts depend on the subject's psychophysiological status and are not significantly affected by movement activity itself or macroscopic movement.

In the active psychophysiological state, which is highly aggressive, stressful, and anxious, the fine movement characteristics of the body (physical vibration) are determined by the psychophysiological process, and the movements of the shoulders, chest and hips are highly correlated with the fine movement of the head . However, in a passive psychophysiological state, this association is lessened when body movements are determined solely by psychophysiological processes. The technical decisions in this regard are new and technically unpredictable to the general practitioner and are industrially available and are the subject matter of the present invention.

This technique allows us to analyze the psychophysiological state of a human being using a mobile device using motion device signals including standard mobile device microelectronics. Using wireless interfaces such as WiFi or Bluetooth, it is possible to analyze the psychophysiological state of human beings on mobile devices as well as on other processors. In addition, the informativeness of psychophysiological information is determined by the accuracy of the motion-speed switching performed by the measuring means itself and the information signal processing method [16, 29] rather than the position of the body sensor and the body contact method.

We will look at the proposal for acquiring information on the psychophysiological state of man composed of various motion parameter measurement methods.

Human motion activity characteristics are identified by motion parameter measurement using video image using external camera (Vibra image technology) and Samsung mobile phone model S4 (motion parameter contact setup method) equipped with Android 4.3 operating system. The handset microelectromechanical signal [30] is processed by the Vibra Image 8.1 program produced by Elsys Corporation [31]. The Viva image program visualizes and correlates the correlation between signals acquired from external devices and the Viva image parameters (including human psychophysiological parameters as determined by Viva image technology). The ViBra Image 8.1 program also analyzes the handheld microelectromechanical signals delivered to the WiFi interface using Android OS standard devices [30]. The mobile phone microelectromechanical sensor data transmission program [30] is stored and stored in the mobile phone in advance. The subject 1 (Fig. 1) is sitting in a chair 2 (Fig. 1) in front of the camera 3 (Fig. 1) with the computer 4 (Fig. 1) and the cellular phone 5 is placed in various positions Loses.

In order to verify the psychophysiological information of the signals obtained from the microelectromechanical sensor, we will look at the visual signal data on the computer screen on the interface of the Vibra Image 8.1 program. FIG. 2 shows a quick signal F1 (determined by the camera in accordance with the vibraimage technique) and a signal V (which determines the motion velocity total vector of the mobile-phone accelerometer microelectromechanical sensor) as the basic information signal. The first cell phone is located on the subject's head. In this case, if there is one physical figure, that is, movement of the human head, the speed of movement is measured by two devices: a vibra image and a microelectromechanical accelerometer. The Viva image program processes these signals and reveals a highly correlated relationship independent of the subject's psychophysiological status.

Let's look at a case where the phone is moved from the head to another position, such as the upper breast pocket. In this case, various body measurements are measured, the camera still illuminates the subject's head, and the cell phone located in the breast pocket of the upper garment measures the speed of movement of the person's chest-side shirt. In this case, there is a remarkably high correlation between F1 and V parameters, and the subject is in active state. Under active motor functional status, human psychophysiological status can be grasped. In this case, the energy consumption is over 3kcal / min [27, 28], and physiological processes as well as active psychological or emotional activities can be seen. For example, energy expenditure on physiological processes of a person sitting calmly does not exceed 2 kcal / min [27, 28] Energy consumption and metabolism are not only physiological processes of the body organs but also psychophysiological processes As shown in Fig.

2a shows the temporal dependence of the F1 and V signals appearing on the test subject in an active functional state where the mobile phone is located in the upper bag. In this case, the first part of the temporal dependence was the case of a minimum movement activity state (no macroscopic movement), 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. To mention the difference, the subject showed slight movement in the left part of the graph and macro movement in the right part of the graph (after 9 seconds). The fact that visually identifiable is the fact that both signals are highly correlated, which is confirmed by a vibra image program numeric aggregation in which these curves are expressed as a correlation coefficient of about 0.95 Pearson. These signals are displayed in relative units. In this case, the trend of all signals is informative rather than the body absolute value obtained at the time of measurement. The correlation dependence of F1 and V values is shown in FIG. 2B. Interestingly, two psychophysiological states (micro-movement and macroscopic movement) do not actually change the level of correlation between the vibration parameters of the human head and chest area. This similar inter-signal dependency was also observed when the cell phone was placed in a suitcase at various locations in the subject.

A similar dependence between signals acquired with the Viva image technique and motion parameter measurement device is observed not only in the original signal of the motion device but also in the information statistical signal in the case of active psychophysiological conditions [16]. An example is the use of an anomalous T-index, such as the correlation of high or low frequencies within the vibra image frequency signal range, as the signal used for contrast [16]. A similar method of aggregating the signals is highly correlated with the anxiety index, which is based on the vibra image, but is based on the range obtained from the motion speed of the mobile phone gyroscope and accelerometer sensors. Moreover, these high associations have little dependence on cell phone locations, such as headwear, topsuits, or trousers. Even when they did not move much while holding a cell phone in their hands, a similar level of anxiety (even in clothes) appeared.

The correlation dependence of humans in a passive psychophysiological state with energy consumption less than 2 kcal / min (energy consumption is mainly determined by physiological process) shows slightly different characteristics. When the subject's mobile phone moves to another location, the movement dependence characteristic of the head part changes significantly with respect to the movement of the other body part. FIG. 3A shows the temporal dependence of the F1 and V signals of the test subject in which the mobile phone is in a passive functional state in the upper bag. The first part related to temporal dependence is minimal movement activity, but does not mean that the subject is in a passive state. In the left part of the graph, there is no significant difference in energy consumption between the right part and the right part. However, in the left part, the subject showed fine movement and in the right part (after 17 seconds) showed macro movement. It is not easy to visually graphically evaluate the level of correlation between parameters, and the Vibra image system showed a significantly lower correlation coefficient (less than 0.2) between signals.

The correlation dependence of F1 and V values in the passive psychophysiological state is shown in FIG. The interesting fact is that in the two psychophysiological states (micro and macroscopic), the level of correlation between the vibration parameters of the human head and chest area is not changed and macro movement does not result in an increase in this. The low similarity between these signals was observed when mobile phones in passive conditions were moved to various locations.

For example, the possibility of acquiring psychophysiological information on the active psychophysiological state of humans could be obtained by using a means of measuring motion parameters that have direct or indirect physical contact with the human body part. In this case, since the motion parameter measurement sensor is attached to the inside of the motion parameter measurement device, there is no direct contact with the human body part, and then the measured motion parameter value is converted into the motion speed. The lack of correlation between movement parameters of the head and body regions informatively characterizes the passive psychophysiological state of man.

In order to improve the accuracy of simultaneous measurement of the motion parameters of the object, the following experiment was conducted. Microsoft Surface Pro 3 i5 128Gb Oc Windows 8 By using the ViBra Image 8.1 program installed on the PC, we used standard vibra image technology to determine the vibration frequency of the object. I selected a black and white circular hemisphere with a contrast of 5hz vibration frequency, and experimented with a screen on another computer monitor. At this time, Microsoft Surface PRO PC was fixed for mechanical safety first. In this case, the object motion frequency measurement result will be 5 ± 0.1 hz, which is a similar level to the proposed moving frequency.

In addition, the experiment was conducted with a monitor and vibration circle half-way distance almost similar to holding a cell phone in hand. In this case, although the video image stabilization method was well observed, the measurement frequency value showed a fairly large distribution of results. A well-known image stabilization method [32, 33, 34, 35] stabilizes macroscopic movements to a certain extent, but nevertheless works with fine motion stabilization algorithms of the body parts, . The measurement result will be 5 ± 2 hz.

The vibration frequency determination program of the object was changed by adding the signal acquisition function of the microelectromechanical sensor of the mobile device and the simultaneous recording of the signal together with the image processing of the vibra image data. In order to obtain a modified vibra image signal, the relationship between the current vibra image signal value and the current microelectronic sensor signal value must be understood. In this case, the object vibration frequency value measured by the modernized program will actually be 5 ± 0.15 hz. This progressive experiment shows that synchronization of motion parameter data obtained from microelectromechanical sensors and cameras improves accuracy of motion activity measurement and naturally increases accuracy of human psychophysiological state identification.

While the above examples illustrating specific experimental progresses show the possibility of a practical invention, the above scheme of the present invention is not limited to the above examples. Technical decisions and techniques of the present invention may be utilized to obtain psychophysiological information of users of mobile devices and other devices. As an example, a special program that can be installed on a mobile device and send data to the Internet for data processing and archiving will provide access to microelectromechanical sensor data. These methods can be used to obtain physiological information about health conditions, such as cardiovascular events, and may signal when a patient is out of normal cardiac activity.

Mobile Devices for Acquiring Information on Human Psychophysiological and Physiological Conditions Microelectromechanical system sensor data utilization is differentiated in terms of convenience and reliability and greatly extends the application field of mobile devices.

While the present invention has been described with reference to the exemplary embodiments, it is to be understood that the invention is not limited to the disclosed exemplary embodiments.

Claims (4)

A motion parameter measuring means for measuring a motion activity by direct or indirect physical contact with a human body part,
A motion parameter change sensor mounted in the motion parameter measurement means and not in direct contact with the human body,
Wherein the parameter values measured by the motion parameter measurement means are converted into a motion velocity to analyze human motion activity.
The method according to claim 1,
Wherein the means for measuring the motion parameter is a mobile phone or an electronic device,
Wherein the motion parameter change sensor is a microelectromechanical sensor mounted on the mobile phone or electronic device,
A method for acquiring information on a psychophysiological state of a human, characterized by analyzing a psychophysiological or functional state of a human by the mobile phone or the electronic device
3. The method of claim 2,
The microelectromechanical sensor records the temporal dependence of the motion velocity,
Wherein information on the psychophysiological state of a human is obtained by analyzing a correlation between frequencies exhibited in temporal dependence of the movement speed to collect psychophysiological or functional state parameters
The method of claim 3,
When aggregating the psychophysiological or functional status parameters,
Motion velocity parameter data obtained from microelectromechanical sensors of mobile handsets or electronic devices can be matched with camera vibra image processing data of mobile phones or electronic devices,
A method for acquiring information on the psychophysiological state of a human, characterized by acquiring a vibra image correction signal by grasping a numerical relationship between a vibra image value and a microelectronic device

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