Using BCI and EEG to process and analyze driver’s brain activity signals during VR simulation

2021 ◽  
Vol 60 (4) ◽  
pp. 137-153
Author(s):  
Mirosław Nader ◽  
Ilona Jacyna-Gołda ◽  
Stanisław Nader ◽  
Karol Nehring
Keyword(s):  
Virtual Reality ◽  
Brain Activity ◽  
Age Groups ◽  
Functional Model ◽  
Flow Simulation ◽  
Human Mind ◽  
Pilot Studies ◽  
Computer Interfaces ◽  
External Stimuli ◽  
Electroencephalogram Eeg

The use of popular brain–computer interfaces (BCI) to analyze signals and the behavior of brain activity is a very current problem that is often undertaken in various aspects by many researchers. This comparison turns out to be particularly useful when studying the flows of information and signals in the human-machine-environment system, especially in the field of transportation sciences. This article presents the results of a pilot study of driver behavior with the use of a proprietary simulator based on Virtual Reality technology. The study uses the technology of studying signals emitted by the human mind and its specific zones in response to given environmental factors. A solution based on virtual reality with the limitation of external stimuli emitted by the real world was proposed, and computational analysis of the obtained data was performed. The research focused on traffic situations and how they affect the subject. The test was attended by representatives of various age groups, both with and without a driving license. This study presents an original functional model of a research stand in VR technology that we designed and built. Testing in VR conditions allows to limit the influence of undesirable external stimuli that may distort the results of readings. At the same time, it increases the range of road events that can be simulated without generating any risk for the participant. In the presented studies, the BCI was used to assess the driver's behavior, which allows for the activity of selected brain waves of the examined person to be registered. Electroencephalogram (EEG) was used to study the activity of brain and its response to stimuli coming from the Virtual Reality created environment. Electrical activity detection is possible thanks to the use of electrodes placed on the skin in selected areas of the skull. The structure of the proprietary test-stand for signal and information flow simulation tests, which allows for the selection of measured signals and the method of parameter recording, is presented. An important part of this study is the presentation of the results of pilot studies obtained in the course of real research on the behavior of a car driver.

BCI-Touch Based System: A Multimodal CAD Interface for Object Manipulation

2013 ◽  
Author(s):  
Rohit Bhat ◽  
Akshay Deshpande ◽  
Rahul Rai ◽  
Ehsan Tarkesh Esfahani
Keyword(s):  
Computer Aided Design ◽  
Brain Activity ◽  
Temporal Cortex ◽  
Target Object ◽  
Time Frequency ◽  
System A ◽  
Computer Interfaces ◽  
Brain Signals ◽  
Aided Design ◽  
Electroencephalogram Eeg

The aim of this paper is to explore a new multimodal Computer Aided Design (CAD) platform based on brain-computer interfaces and touch based systems. The paper describes experiments and algorithms for manipulating geometrical objects in CAD systems using touch-based gestures and movement imagery detected though brain waves. Gestures associated with touch based systems are subjected to ambiguity since they are two dimensional in nature. Brain signals are considered here as the main source to resolve these ambiguities. The brainwaves are recorded in terms of electroencephalogram (EEG) signals. Users wear a neuroheadset and try to move and rotate a target object on a touch screen. As they perform these actions, the EEG headset collects brain activity from 14 locations on the scalp. The data is analyzed in the time-frequency domain to detect the desynchronizations of certain frequency bands (3–7Hz, 8–13 Hz, 14–20Hz 21–29Hz and 30–50Hz) in the temporal cortex as an indication of motor imagery.

scholarly journals Multimodal-Multisensory Experiments

2020 ◽  
Author(s):  
Moein Razavi ◽  
Takashi Yamauchi ◽  
Vahid Janfaza ◽  
Anton Leontyev ◽  
Shanle Longmire-Monford ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Response Time ◽  
Galvanic Skin Response ◽  
Low Cost ◽  
Body Movement ◽  
Human Mind ◽  
Body Motion ◽  
Mouse Cursor ◽  
Skin Response ◽  
Electroencephalogram Eeg

The human mind is multimodal. Yet most behavioral studies rely on century-old measures of behavior—task accuracy and latency (response time). Multimodal and multisensory analysis of human behavior creates a better understanding of how the mind works. The problem is that designing and implementing these experiments is technically complex and costly. This paper introduces versatile and economical means of developing multimodal-multisensory human experiments. We provide an experimental design framework that automatically integrates and synchronizes measures including electroencephalogram (EEG), galvanic skin response (GSR), eye-tracking, virtual reality (VR), body movement, mouse/cursor motion and response time. Unlike proprietary systems (e.g., iMotions), our system is free and open-source; it integrates PsychoPy, Unity and Lab Streaming Layer (LSL). The system embeds LSL inside PsychoPy/Unity for the synchronization of multiple sensory signals—gaze motion, electroencephalogram (EEG), galvanic skin response (GSR), mouse/cursor movement, and body motion—with low-cost consumer-grade devices in a simple behavioral task designed by PsychoPy and a virtual reality environment designed by Unity. This tutorial shows a step-by-step process by which a complex multimodal-multisensory experiment can be designed and implemented in a few hours. When conducting the experiment, all of the data synchronization and recoding of the data to disk will be done automatically.

scholarly journals Experimental Diagnostics of the Emotional State of Individuals Using External Stimuli and a Model of Neurocognitive Brain Activity

Diagnostics ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 125
Author(s):  
Alexandr Y. Petukhov ◽  
Sofia A. Polevaya ◽  
Anna V. Polevaya
Keyword(s):  
Emotional State ◽  
Brain Activity ◽  
Human Mind ◽  
One Dimensional ◽  
Experimental Scheme ◽  
The Subject ◽  
Audiovisual Stimuli ◽  
External Stimuli ◽  
Internal Potential ◽  
Experimental Diagnostics

In this paper, we study ways and methods to diagnose the emotional state of individuals using external audiovisual stimuli and heart telemetry tools. We apply a mathematical model of neurocognitive brain activity developed specifically for this study to interpret the experimental scheme and its results. This experimental technique is based on monitoring and analyzing the dynamics of heart rate variability (HRV), taking into account the particular context and events occurring around the subject of the study. In addition, we provide a brief description of the theory of information images/representations used for the paradigm and interpretation of the experiment. For this study, we viewed the human mind as a one-dimensional potential hole with finite walls of different sizes and an internal potential barrier modeling the border between consciousness and subconsciousness. We also provided the foundations of the mathematical apparatus for this particular view. This experiment allowed us to identify the characteristic markers of influencing external stimuli, which form a foundation for diagnosing the emotional state of an individual.

scholarly journals Embodiment is related to better performance on an immersive brain computer interface in head-mounted virtual reality: A pilot study

2019 ◽  
Author(s):  
Julia M Juliano ◽  
Ryan P Spicer ◽  
Athanasios Vourvopoulos ◽  
Stephanie Lefebvre ◽  
Kay Jann ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Brain Activity ◽  
Sensory Information ◽  
Individual Performance ◽  
Motor Rehabilitation ◽  
Computer Screen ◽  
Computer Interfaces ◽  
Sense Of Presence ◽  
Immersive Systems ◽  
Sensorimotor Rhythms

AbstractBrain computer interfaces (BCI) can be used to provide individuals with neurofeedback of their own brain activity and train them to learn how to control their brain activity. Neurofeedback-based BCIs used for motor rehabilitation aim to ‘close the loop’ between attempted motor commands and sensory feedback by providing supplemental sensory information when individuals successfully establish specific brain patterns. Existing neurofeedback-based BCIs have used a variety of displays to provide feedback, ranging from devices that provide a more immersive and compelling experience (e.g., head-mounted virtual reality (HMD-VR) or CAVE systems) to devices that are considered less immersive (e.g., computer screens). However, it is not clear whether more immersive systems (i.e., HMD-VR) improve neurofeedback performance compared to computer screens, and whether there are individual performance differences in HMD-VR versus screen-based neurofeedback. In this pilot experiment, we compared neurofeedback performance in HMD-VR versus on a computer screen in twelve healthy individuals. We also examined whether individual differences in presence or embodiment correlated with neurofeedback performance in either environment. Participants were asked to control a virtual right arm by imagining right hand movements. Real-time brain activity indicating motor imagery, which was measured via electroencephalography (EEG) as desynchronized sensorimotor rhythms (SMR; 8-24 Hz) in the left motor cortex, drove the movement of the virtual arm towards (increased SMR desynchronization) or away from (decreased SMR desynchronization) targets. Participants performed two blocks of 30 trials, one for each condition (Screen, HMD-VR), with the order of conditions counterbalanced across participants. After completing each block, participants were asked questions relating to their sense of presence and embodiment in each environment. We found that, while participants’ performance on the neurofeedback-based BCI task was similar between conditions, the participants’ reported levels of embodiment was significantly different between conditions. Specifically, participants experienced higher levels of embodiment in HMD-VR compared to the computer screen. We further found that reported levels of embodiment positively correlated with neurofeedback performance only in the HMD-VR condition. Overall, these preliminary results suggest that embodiment may improve performance on a neurofeedback-based BCI and that HMD-VR may increase embodiment during a neurofeedback-based BCI task compared to a standard computer screen.

Decoding of the coupling between the brain and facial muscle reactions in auditory stimulation

2021 ◽  
pp. 1-10
Author(s):  
Mirra Soundirarajan ◽  
Kamil Kuca ◽  
Ondrej Krejcar ◽  
Hamidreza Namazi
Keyword(s):  
Shannon Entropy ◽  
Rock Music ◽  
Brain Activity ◽  
Entropy Method ◽  
Pop Music ◽  
Facial Muscle ◽  
Eeg Signals ◽  
External Stimuli ◽  
Electroencephalogram Eeg ◽  
The Brain

BACKGROUND: Analysis of the reactions of different organs to external stimuli is an important area of research in physiological science. OBJECTIVE: In this paper, we investigated the correlation between the brain and facial muscle activities by information-based analysis of electroencephalogram (EEG) signals and electromyogram (EMG) signals using Shannon entropy. METHOD: The EEG and EMG signals of thirteen subjects were recorded during rest and auditory stimulations using relaxing, pop, and rock music. Accordingly, we calculated the Shannon entropy of these signals. RESULTS: The results showed that rock music has a greater effect on the information of EEG and EMG signals than pop music, which itself has a greater effect than relaxing music. Furthermore, a strong correlation (r= 0.9980) was found between the variations of the information of EEG and EMG signals. CONCLUSION: The activities of the facial muscle and brain are correlated in different conditions. This technique can be utilized to investigate the correlation between the activities of different organs versus brain activity in different situations.

scholarly journals Multimodal-Multisensory Experiments: Design and Implementation

2020 ◽  
Author(s):  
Moein Razavi ◽  
Takashi Yamauchi ◽  
Vahid Janfaza ◽  
Anton Leontyev ◽  
Shanle Longmire-Monford ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Response Time ◽  
Galvanic Skin Response ◽  
Low Cost ◽  
Body Movement ◽  
Human Mind ◽  
Body Motion ◽  
Mouse Cursor ◽  
Skin Response ◽  
Electroencephalogram Eeg

AbstractThe human mind is multimodal. Yet most behavioral studies rely on century-old measures of behavior - task accuracy and latency (response time). Multimodal and multisensory analysis of human behavior creates a better understanding of how the mind works. The problem is that designing and implementing these experiments is technically complex and costly. This paper introduces versatile and economical means of developing multimodal-multisensory human experiments. We provide an experimental design framework that automatically integrates and synchronizes measures including electroencephalogram (EEG), galvanic skin response (GSR), eye-tracking, virtual reality (VR), body movement, mouse/cursor motion and response time. Unlike proprietary systems (e.g., iMotions), our system is free and open-source; it integrates PsychoPy, Unity and Lab Streaming Layer (LSL). The system embeds LSL inside PsychoPy/Unity for the synchronization of multiple sensory signals - gaze motion, electroencephalogram (EEG), galvanic skin response (GSR), mouse/cursor movement, and body motion - with low-cost consumer-grade devices in a simple behavioral task designed by PsychoPy and a virtual reality environment designed by Unity. This tutorial shows a step-by-step process by which a complex multimodal-multisensory experiment can be designed and implemented in a few hours. When conducting the experiment, all of the data synchronization and recoding of the data to disk will be done automatically.

Quantitative evaluation of slow fluctuations of the volume of liquids inside cranial cavity

2019 ◽  
pp. 51-63 ◽  
Author(s):  
Yu. E. Moskalenko ◽  
T. I. Kravchenko ◽  
Yu. V. Novozhilova
Keyword(s):  
Brain Activity ◽  
Sampling Rate ◽  
Age Groups ◽  
Pulse Amplitude ◽  
Cranial Cavity ◽  
Current Frequency ◽  
Physiological Indicators ◽  
Physiological Phenomenon ◽  
Long Time ◽  
Manned Space

Introduction. Slow fl uctuations in the volume and pressure of liquids in the cranial cavity have been known for a long time and have been studied for more than 100 years. However, their quantitative indicators and their practical signifi cance remain unclear until now due to the diffi culties of research. Nevertheless, it was found that they were connected with the brain activity, which made it possible to use them as one of the physiological indicators in studying the problems of manned space fl ights. Goal of research — to study the possibility of using spectral analysis of slow fl uctuations of the volume of liquids inside the cranium in order to realize the quantitative assessment of their indicators with the use of modern microelectronics and computer technology.Materials and methods. In order to solve this problem we created a complex, in which rheoencephalograph-RG-01 («Mizar») was used as a converter-modulator of physiological signals into electrical oscillations. The device was connected with the ADC (Firm «ADIstrument»), Its software allows to calculate the spectrogram with a sampling rate of 128 kHz. Studies were conducted on volunteers of younger, middle and older age groups. The respiratory rate and the electrocardiography were registered together with the rheoencephalography. Electrodes were fi xed on the volonteers′ fronto-mastoid area.Results. Slow fl uctuations the cranium representan independent physiological phenomenon. The most considerable and valuable were fl uctuations in 0,1–0,3 Hz. It was found that current frequency of 100 or 200 kHz and frequency for quantization of 80–100 kHz was optimal for performing their spectrograms. The structure of such diagram consists of 4–7 peaks with amplitude of 0,4–0,7 units compared with REG pulse amplitude. They depend on age and are characterized by hemispheric asymmetry. Spectral diagrams of slow fl ucation inside cranium are representing inpendent physiological phenomenon. These fl uctuations are not connected by common origin, with heart activity and respiration. They are connected by nature with brain activity and PRM.Conclusion. Can be an informative method for diagnostic and assessment of general status of osteopathic patients well as for the assessment of mechanisms of action of some osteopathic techniques.

Automated System for Epileptic Seizures Prediction based on Multi-Channel Recordings of Electrical Brain Activity

2018 ◽  
pp. 115-122 ◽  
Author(s):  
V. A. Maksimenko ◽  
A. A. Harchenko ◽  
A. Lüttjohann
Keyword(s):  
Epileptic Seizure ◽  
Brain Activity ◽  
Epileptic Seizures ◽  
Automated System ◽  
Brain Computer Interfaces ◽  
Electrical Brain Activity ◽  
Computer Interfaces ◽  
Prediction And Prevention ◽  
The Brain

Introduction: Now the great interest in studying the brain activity based on detection of oscillatory patterns on the recorded data of electrical neuronal activity (electroencephalograms) is associated with the possibility of developing brain-computer interfaces. Braincomputer interfaces are based on the real-time detection of characteristic patterns on electroencephalograms and their transformation  into commands for controlling external devices. One of the important areas of the brain-computer interfaces application is the control of the pathological activity of the brain. This is in demand for epilepsy patients, who do not respond to drug treatment.Purpose: A technique for detecting the characteristic patterns of neural activity preceding the occurrence of epileptic seizures.Results:Using multi-channel electroencephalograms, we consider the dynamics of thalamo-cortical brain network, preceded the occurrence of an epileptic seizure. We have developed technique which allows to predict the occurrence of an epileptic seizure. The technique has been implemented in a brain-computer interface, which has been tested in-vivo on the animal model of absence epilepsy.Practical relevance:The results of our study demonstrate the possibility of epileptic seizures prediction based on multichannel electroencephalograms. The obtained results can be used in the development of neurointerfaces for the prediction and prevention of seizures of various types of epilepsy in humans. 

scholarly journals Mind-wandering Is Accompanied by Both Local Sleep and Enhanced Processes of Spatial Attention Allocation

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Christian Wienke ◽  
Mandy V Bartsch ◽  
Lena Vogelgesang ◽  
Christoph Reichert ◽  
Hermann Hinrichs ◽  
...  
Keyword(s):  
Search Task ◽  
Brain Activity ◽  
Target Selection ◽  
Mind Wandering ◽  
Attentional Selection ◽  
Self Report ◽  
Cortical Processing ◽  
High Frequency Activity ◽  
External Stimuli ◽  
Local Sleep

Abstract Mind-wandering (MW) is a subjective, cognitive phenomenon, in which thoughts move away from the task toward an internal train of thoughts, possibly during phases of neuronal sleep-like activity (local sleep, LS). MW decreases cortical processing of external stimuli and is assumed to decouple attention from the external world. Here, we directly tested how indicators of LS, cortical processing, and attentional selection change in a pop-out visual search task during phases of MW. Participants’ brain activity was recorded using magnetoencephalography, MW was assessed via self-report using randomly interspersed probes. As expected, the performance decreased under MW. Consistent with the occurrence of LS, MW was accompanied by a decrease in high-frequency activity (HFA, 80–150 Hz) and an increase in slow wave activity (SWA, 1–6 Hz). In contrast, visual attentional selection as indexed by the N2pc component was enhanced during MW with the N2pc amplitude being directly linked to participants’ performance. This observation clearly contradicts accounts of attentional decoupling that would predict a decrease in attention-related responses to external stimuli during MW. Together, our results suggest that MW occurs during phases of LS with processes of attentional target selection being upregulated, potentially to compensate for the mental distraction during MW.

scholarly journals The relationship between fasting-induced torpor, sleep and waking in laboratory mice

SLEEP ◽  
2021 ◽  
Author(s):  
Yi-Ge Huang ◽  
Sarah J Flaherty ◽  
Carina A Pothecary ◽  
Russell G Foster ◽  
Stuart N Peirson ◽  
...  
Keyword(s):  
Body Temperature ◽  
Rem Sleep ◽  
Brain Activity ◽  
Mammalian Species ◽  
Nrem Sleep ◽  
Laboratory Mice ◽  
State Classification ◽  
Metabolic Suppression ◽  
The Relationship ◽  
Electroencephalogram Eeg

Abstract Study objectives Torpor is a regulated and reversible state of metabolic suppression used by many mammalian species to conserve energy. Whereas the relationship between torpor and sleep has been well-studied in seasonal hibernators, less is known about the effects of fasting-induced torpor on states of vigilance and brain activity in laboratory mice. Methods Continuous monitoring of electroencephalogram (EEG), electromyogram (EMG) and surface body temperature was undertaken in adult, male C57BL/6 mice over consecutive days of scheduled restricted feeding. Results All animals showed bouts of hypothermia that became progressively deeper and longer as fasting progressed. EEG and EMG were markedly affected by hypothermia, although the typical electrophysiological signatures of NREM sleep, REM sleep and wakefulness enabled us to perform vigilance-state classification in all cases. Consistent with previous studies, hypothermic bouts were initiated from a state indistinguishable from NREM sleep, with EEG power decreasing gradually in parallel with decreasing surface body temperature. During deep hypothermia, REM sleep was largely abolished, and we observed shivering-associated intense bursts of muscle activity. Conclusions Our study highlights important similarities between EEG signatures of fasting-induced torpor in mice, daily torpor in Djungarian hamsters and hibernation in seasonally-hibernating species. Future studies are necessary to clarify the effects on fasting-induced torpor on subsequent sleep.

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