Application of vibraimage technology and system for analysis of motor activity and study of functional state of the human body

Minkin, Viktor; Nikolaenko, N. N.

doi:10.1007/s10527-008-9045-9

Cited by 19 publications

(18 citation statements)

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“…In Figure 10c, FO5 is selected as BOA for Equation (15). Since the BOA divides the total region into two equal areas and the COG indicates the center of gravity, the obtained fuzzy output value may not be consistent all the time.…”

Section: Experimental Results and Analysesmentioning

confidence: 99%

“…Single modality-based methods include visible light camera-based methods [8][9][10][11][12][13][14][15], thermal camera-based methods [16,17], voice-based methods [2,[12][13][14]18,19], physiological signal-based methods [20][21][22][23][24][25], and functional magnetic resonance imaging (fMRI)-based methods [26]. As for visible light camera-based methods, images of subjects' facial expression at different emotions are captured by a camera and the generated data used to study the information on subjects' facial expression (changes in facial feature points by comparison between previous image frames and present image frames, etc.)…”

Section: Related Workmentioning

confidence: 99%

“…As for visible light camera-based methods, images of subjects' facial expression at different emotions are captured by a camera and the generated data used to study the information on subjects' facial expression (changes in facial feature points by comparison between previous image frames and present image frames, etc.) [8][9][10][11][12][13][14][15].…”

Section: Related Workmentioning

confidence: 99%

“…By referring to a study [15] conducted based on vibraimages that are known to capture subtle movements observed in the body or head when in a state of anxiety or stress, this study also measured NM in order to observe such subtle movements in the subjects' heads. To do this, the horizontal and vertical movements in two successive images at point 30 were calculated, and the average value of the experimental images was used as NM.…”

Section: Measurement Of Ebr Dlrl Dull Em and Nm (Feature Values 3mentioning

confidence: 99%

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Fuzzy System-Based Fear Estimation Based on the Symmetrical Characteristics of Face and Facial Feature Points

2017

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Abstract:The application of user emotion recognition for fear is expanding in various fields, including the quantitative evaluation of horror movies, dramas, advertisements, games, and the monitoring of emergency situations in convenience stores (i.e., a clerk threatened by a robber), in addition to criminal psychology. Most of the existing methods for the recognition of fear involve referring to a single physiological signal or recognizing circumstances in which users feel fear by selecting the most informative one among multiple physiological signals. However, the level of accuracy as well as the credibility of these study methods is low. Therefore, in this study, data with high credibility were obtained using non-intrusive multimodal sensors of near-infrared and far-infrared light cameras and selected based on t-tests and Cohen's d analysis considering the symmetrical characteristics of face and facial feature points. The selected data were then combined into a fuzzy system using the input and output membership functions of symmetrical shape to ultimately derive a new method that can quantitatively show the level of a user's fear. The proposed method is designed to enhance conventional subjective evaluation (SE) by fuzzy system based on multi-modalities. By using four objective features except for SE and combining these four features into a fuzzy system, our system can produce an accurate level of fear without being affected by the physical, psychological, or fatigue condition of the participants in SE. After conducting a study on 20 subjects of various races and genders, the results indicate that the new method suggested in this study has a higher level of credibility for the recognition of fear than the methods used in previous studies.Keywords: fear; multimodal sensors of near-infrared and far-infrared light cameras; symmetrical characteristics of face and facial feature points; fuzzy system; input and output membership functions of symmetrical shape

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Section: Experimental Results and Analysesmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Measurement Of Ebr Dlrl Dull Em and Nm (Feature Values 3mentioning

confidence: 99%

See 2 more Smart Citations

Fuzzy System-Based Fear Estimation Based on the Symmetrical Characteristics of Face and Facial Feature Points

2017

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“…This approach allows obtaining information only on moving objects and enhancing the signals of the objects making vibrations. The head of a person in a quasi-stationary state constantly makes slight micromovements and movements (vibrations), and the parameters of these micromovements depend on a psycho-emotional and psychophysiological state of a person and are conditioned by the vestibular-emotional reflex [23]. There is quite a large number of modern scientific works associating brain activity, including intelligence level, with topological features of brain development [19] [24] [25].…”

Section: Vibraimage Technology and Multiple Intelligencesmentioning

confidence: 99%

Application of New Concept for Multiple Intelligences Calculation for Personality and Social Groups Comparison Research

Minkin¹,

Nikolaenko²

2017

JBBS

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A person is considered as information-energy system with a host of feedbacks. The possibility of determining the statistical characteristics in a multiple intelligences profile of various social groups' representatives using the vibraimage technology is investigated. Theft and alcohol abuse have been chosen as examples of significant social problems including deviant behavior and the trigger of formation of various socially vulnerable groups. The comparative analysis of conscious and unconscious attitudes in multiple intelligences structure of individuals prone to deviant behavior and the control group allows differentiating professional preferences and the impact of society on different social groups.

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Results of recording electrophysiological signals by nanosensors during tests on volunteers

Avdeeva

Guo

Nguyen

et al. 2020

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Purpose The purpose of this paper is to analyze the results of recording electrophysiological signals by nanosensors during tests on volunteers using neutral questions and questions that cause excitement. Design/methodology/approach The nanosensor-based hardware and software complex (HSC) was used for simultaneous recording of electrocardiogram, electroencephalogram and galvanic skin response during tests on volunteers using neutral questions and questions that cause excitement. The recording was carried out in real time without averaging and filtering in the extended frequency range from 0 to 10,000 Hz, level of more than 1 µV and sampling frequency equal to 64 kHz. Findings For the first time, the following signals were recorded by nanosensors without filtering and averaging in the measuring channels: real-time micropotentials on an electrocardiogram with a duration of 0.2 ms and a level of 1 µV or more. Also, for the first time, changes in the shape and amplitude of the P wave, slow waves on the electroencephalography (EEG), high impulse activity of the EEG and impulse activity of short duration on the GSR were recorded in response to questions that cause excitement. Practical implications The obtained results will be used for high-resolution equipment to develop additional measuring channels in existing types of equipment for psychophysiological studies. Originality/value For the first time, new data undistorted by filters was obtained on the amplitude and time parameters of electrophysiological signals in the frequency range from 0 to 10,000 Hz in response to questions that cause excitement, which was due to high sensitivity and noise immunity of nanosensors in comparison with existing electrodes for biopotential recording.

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Application of vibraimage technology and system for analysis of motor activity and study of functional state of the human body

Cited by 19 publications

References 0 publications

Fuzzy System-Based Fear Estimation Based on the Symmetrical Characteristics of Face and Facial Feature Points

Fuzzy System-Based Fear Estimation Based on the Symmetrical Characteristics of Face and Facial Feature Points

Application of New Concept for Multiple Intelligences Calculation for Personality and Social Groups Comparison Research

Results of recording electrophysiological signals by nanosensors during tests on volunteers

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