Sergey A. Isaychev

Background. To assess the structure of inter-ethnic attitudes and the risks of ethnoreligious tension, psychologists mostly use questionnaires, interviews, subjective scaling, content analysis, and special tests. One possible approach to increasing the validity and reliability of these explicit methods is the use of the registration of psychophysiological indicators while a recipient completes the questionnaire or test forms.

Objective. The results of a pilot psychophysiological research are presented, which focus on the study of human psycho-emotional states during socio-psychological testing to identify attitudes in the field of interethnic and interfaith relations.

Design. The essence of the applied experimental approach is to control the functional (psycho-emotional) state of a respondent using the registration of complex psychophysiological (physiological and behavioral) responses in the process of completing the socio-psychological questionnaire.

Results. It was shown that the rhythmic brain activity (ratio of the power indexes of alpha and beta rhythms), the amplitude of the systolic wave (photoplethysmogram) (ASW PhPG) and the magnitude (length) of the ‘circumflex line of the Galvanic Skin Response’ (GSR-L) may be the complex of indicators that possess sufficiently high selective sensitivity to differentiate nonspecific reactions of the human nervous system to personally important (emotiogenic, stressful) questions in the questionnaire.

Conclusion. The proposed approach may help to identify stressful (emotiogenic) issues (questions) in socio-psychological tests and questionnaires that are of the greatest interest to the subject and, as a result, most adequately reflect individual and population attitudes in the field of social relations.

L. S. Vygotsky in his famous methodological essay “The historical meaning of psychological crisis” (1928) emphasized the importance of studying any psychological process or state as a “whole” — that is, as characterized from the subjective and objective sides at the same time. This position is fully relevant for studying the human functional states (FSes). Today the objective psychophysiological diagnostics of human FSes in activities associated with a high risk of technological disasters (in nuclear-power plants, transportation, the chemical industry) are extremely relevant and socially important. This article reviews some new psychophysiological methods of FS assessment that are being developed in Russia and abroad and discusses different aspects of developing integral psychophysiological FS assessment. The emphasis is on distant methods of FS diagnostics: the bioradiolocation method, laser Doppler vibrometry, eye tracking, audio and video recordings, infrared thermography. The possibilities and limitations of the most popular emotion atlases — the Facial Affect Scoring Technique (FAST) and the Facial Action Coding System (FACS) — in developing distant visual-range and infrared-range systems for automated classification of facial expressions are analyzed. A special section of the article concentrates on the problem of constructing an integral psychophysiological FS index. Mathematical algorithms that provide a partition of FS indicators into different FS types are based on various methods of machine learning. We propose the vector approach for construction of complex estimations of the human FSes.

Automated classification of a human functional state is an important problem, with applications including stress resistance evaluation, supervision over operators of critical infrastructure, teaching and phobia therapy. Such classification is particularly efficient in systems for teaching and phobia therapy that include a virtual reality module, and provide the capability for dynamic adjustment of task complexity.

In this paper, a method for automated real-time binary classification of human functional states (calm wakefulness vs. stress) based on discrete wavelet transform of EEG data is considered. It is shown that an individual tuning stage of the classification algorithm — a stage that allows the involvement of certain information on individual peculiarities in the classification, using very short individual learning samples, significantly increases classification reliability. The experimental study that proved this assertion was based on a specialized scenario in which individuals solved the task of detecting objects with given properties in a dynamic set of flying objects.

The original experimental scheme was developed to investigate athletes’ functional states (FS) dynamics. The procedure allowed modeling various FS important for predicting the professional success of athletes: psychological and physiological stress, fatigue, and optimal FS (OFS). There were two main criteria for differentiation of the FS under study: efficiency rates and the psychological and physiological costs of the achieved efficiency level. Analysis of the FS-dependent psychophysiological changes showed significant interindividual differences on a number of parameters. Thus, no single indicator could be used as effective diagnostics for the FS criteria. A minimum number of indicators need to be recorded included cardiovascular indicators (heart rate, ECG), respiration, muscle tension (EMG), and brain activity (EEG) in the range of alpha and beta waves. The main problem can be artifacts induced by movement and muscle tension. The special procedure for artifact rejection and reduction of the artifacts was developed. It allowed recording EEG, ECG, and EOG signals simultaneously. Another problem was related to the development of the mathematical algorithm to analyze individual data and differentiate patterns of the signals recorded from the athletes. An original approach to differentiate the FS – the k-means clustering algorithm – was offered based on seven psychophysiological indicators. Results of clustering showed that the k- means algorithm for seven-component vectors allows one with confidence to differentiate state of quiet wakefulness, states of psychological and physiological stress. As the number of parameters used is attenuated from seven to four (without the EEG parameters) the accuracy of distinguishing FS is significantly reduced. To construct a complete and accurate differentiation of an athlete’s FS one should collect some statistical data on the dynamics of each FS in different time periods of the person’s life – in the process of training, after successful competition, and after losing competition.

The problem of lie detection has a long history. Main achievements in this field are concerned with registration of peripheral nervous system indicators. Our experiment provides possibility for development of a new lie detection technology, based on neurophysiologic correlates of cognitive processes diagnostics that underlie deception. The experiments were conducted by “Audio-Visual Slider” software (by Medicom MTD), which performed synchronized stimuli presentation and electrophysiological recording.

Background. One promising direction in development of contactless techniques for assessment of the human psychoemotional state (PES) is elucidation of the relationships between psychophysiological indices and electromagnetic radiation in the IR and THz ranges.

Objective. To present a complex approach to assessing PESs based on combining psychological testing and psychophysiological diagnostics with measurements of radiation in the IR-THz range from face areas.

Methods. Stressful psychoemotional states were provoked by physical or cognitive stressors. The PES was monitored by psychological testing and registration of heart rate, photoplethysmogram, galvanic skin response, and respiration rate. The facial images in the IR-THz range were extracted by an IR/V-T0831Cdetector (NEC, Japan).

Results and Discussion. Different PESs are characterized by different specific patterns of psychophysiological parameters. Scores on the anxiety test are highly correlated with scores on the chronic stress questionnaire, but there are no reliable links between the data of psychological tests and the psychophysiological indicators. This discrepancy allows us to assume that for reliable identification of PESs, it is necessary to combine these technologies into one diagnostic complex. We found statistically significant correlations between the intensity of the IR-THz image in the forehead and the galvanic skin response.

Conclusion. For the effective diagnosis and forecast of changes in the PES, it is important to consider both the psychological and physiological data. Despite the relatively low signal-to-noise ratio and low frequency of image recording, it is possible to extract informative THz parameters of the broadband IR-THz signal and associate them with psychophysiological reactions. The improvement of IR-THz detectors and the development of new processing methods will allow wide use of the THz range for remote assessment of human PESs in real time.