scholarly journals The effects of Michelia alba oil against mould on brown rice and assessing the brain response using electroencephalogram (EEG)

2020 ◽  
Author(s):  
Sumethee Songsamoe ◽  
Phanit Koomhin ◽  
Narumol Matan
Keyword(s):  
Brown Rice ◽  
Brain Response ◽  
Electroencephalogram Eeg ◽  
The Brain

scholarly journals Comparison between Daytime and Nighttime Scenery Focusing on Restorative and Recovery Effect

2019 ◽  
Vol 11 (12) ◽  
pp. 3326
Author(s):  
SangHyun Cheon ◽  
Soyoung Han ◽  
Mintai Kim ◽  
Yoonku Kwon
Keyword(s):  
Psychological Impact ◽  
Brain Regions ◽  
Visual Images ◽  
Built Environments ◽  
Brain Response ◽  
Reported Data ◽  
Physiological Variations ◽  
Negative Relationships ◽  
Electroencephalogram Eeg ◽  
The Brain

The overall purpose of this study was to investigate psycho-physiological variations in human bodies by observing visual images of daytime and nighttime scenery to focus on restorative and recovery effects. Unlike previous studies that have focused on the natural versus built environments, this study aims to compare restorative and recovery potentials between daytime and nighttime. The experiment was conducted by showing a total of 12 images to 60 participants in order to measure the brain response with an electroencephalogram (EEG). As measures of the psychological impact of the images, perceived restorative and recovery scales were used. The self-reported data indicates that daytime sceneries are rated more positively than nighttime sceneries in terms of restorative and recovery effects. According to the EEG results, restorative and recovery feelings have negative relationships with the relative theta band, while positive relationships are shown with the relative alpha band. The correlation analysis between EEG bands and brain regions showed a significant correlation (p < 0.05) with 46 pairs for the daytime scenery stimuli and 52 pairs for the nighttime scenery stimuli. Through the results of the study, we conclude that daytime and nighttime scenery affect restorative feelings and the human brain response through both verbal and non-verbal methods.

Consumer neuroscience: Assessing the brain response to marketing stimuli using electroencephalogram (EEG) and eye tracking

2013 ◽  
Vol 40 (9) ◽  
pp. 3803-3812 ◽  
Author(s):  
Rami N. Khushaba ◽  
Chelsea Wise ◽  
Sarath Kodagoda ◽  
Jordan Louviere ◽  
Barbara E. Kahn ◽  
...  
Keyword(s):  
Eye Tracking ◽  
Brain Response ◽  
Consumer Neuroscience ◽  
Electroencephalogram Eeg ◽  
The Brain

scholarly journals Conditional Entropy: A Potential Digital Marker for Stress

Entropy ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. 286
Author(s):  
Soheil Keshmiri
Keyword(s):  
Resting State ◽  
Nearest Neighbor ◽  
Brain Activity ◽  
Solution Concept ◽  
Conditional Entropy ◽  
K Nearest Neighbor ◽  
Brain Response ◽  
Substantial Progress ◽  
Eeg Recordings ◽  
The Brain

Recent decades have witnessed a substantial progress in the utilization of brain activity for the identification of stress digital markers. In particular, the success of entropic measures for this purpose is very appealing, considering (1) their suitability for capturing both linear and non-linear characteristics of brain activity recordings and (2) their direct association with the brain signal variability. These findings rely on external stimuli to induce the brain stress response. On the other hand, research suggests that the use of different types of experimentally induced psychological and physical stressors could potentially yield differential impacts on the brain response to stress and therefore should be dissociated from more general patterns. The present study takes a step toward addressing this issue by introducing conditional entropy (CE) as a potential electroencephalography (EEG)-based resting-state digital marker of stress. For this purpose, we use the resting-state multi-channel EEG recordings of 20 individuals whose responses to stress-related questionnaires show significantly higher and lower level of stress. Through the application of representational similarity analysis (RSA) and K-nearest-neighbor (KNN) classification, we verify the potential that the use of CE can offer to the solution concept of finding an effective digital marker for stress.

Information-based analysis of the coupling between brain and heart reactions to olfactory stimulation

2021 ◽  
pp. 1-11
Author(s):  
Najmeh Pakniyat ◽  
Mohammad Hossein Babini ◽  
Vladimir V. Kulish ◽  
Hamidreza Namazi
Keyword(s):  
Time Series ◽  
Biomedical Science ◽  
Strongly Correlated ◽  
Eeg Signals ◽  
Ecg Signals ◽  
Olfactory Stimuli ◽  
Electrocardiogram Ecg ◽  
First Time ◽  
Electroencephalogram Eeg ◽  
The Brain

BACKGROUND: Analysis of the heart activity is one of the important areas of research in biomedical science and engineering. For this purpose, scientists analyze the activity of the heart in various conditions. Since the brain controls the heart’s activity, a relationship should exist among their activities. OBJECTIVE: In this research, for the first time the coupling between heart and brain activities was analyzed by information-based analysis. METHODS: Considering Shannon entropy as the indicator of the information of a system, we recorded electroencephalogram (EEG) and electrocardiogram (ECG) signals of 13 participants (7 M, 6 F, 18–22 years old) in different external stimulations (using pineapple, banana, vanilla, and lemon flavors as olfactory stimuli) and evaluated how the information of EEG signals and R-R time series (as heart rate variability (HRV)) are linked. RESULTS: The results indicate that the changes in the information of the R-R time series and EEG signals are strongly correlated (ρ=-0.9566). CONCLUSION: We conclude that heart and brain activities are related.

Effects of CSF Properties on Brain Response Under Impact Loading

2009 ◽  
Author(s):  
M. S. Chafi ◽  
V. Dirisala ◽  
G. Karami ◽  
M. Ziejewski
Keyword(s):  
Human Head ◽  
Brain Response ◽  
Pia Mater ◽  
Mechanical Shocks ◽  
The Central Nervous System ◽  
Simultaneous Loading ◽  
The Impact ◽  
Impact Experiments ◽  
The Brain

In the central nervous system, the subarachnoid space is the interval between the arachnoid membrane and the pia mater. It is filled with a clear, watery liquid called cerebrospinal fluid (CSF). The CSF buffers the brain against mechanical shocks and creates buoyancy to protect it from the forces of gravity. The relative motion of the brain due to a simultaneous loading is caused because the skull and brain have different densities and the CSF surrounds the brain. The impact experiments are usually carried out on cadavers with no CSF included because of the autolysis. Even in the cadaveric head impact experiments by Hardy et al. [1], where the specimens are repressurized using artificial CSF, this is not known how far this can replicate the real functionality of CSF. With such motivation, a special interest lies on how to model this feature in a finite element (FE) modeling of the human head because it is questionable if one uses in vivo CSF properties (i.e. bulk modulus of 2.19 GPa) to validate a FE human head against cadaveric experimental data.

scholarly journals Context-Based Filtering for Assisted Brain-Actuated Wheelchair Driving

2007 ◽  
Vol 2007 ◽  
pp. 1-12 ◽  
Author(s):  
Gerolf Vanacker ◽  
José del R. Millán ◽  
Eileen Lew ◽  
Pierre W. Ferrez ◽  
Ferran Galán Moles ◽  
...  
Keyword(s):  
Control System ◽  
Shared Control ◽  
Eeg Signals ◽  
Intelligent Processing ◽  
Intelligent Wheelchair ◽  
Brain Signals ◽  
Brain Interface ◽  
The Subject ◽  
Electroencephalogram Eeg ◽  
The Brain

Controlling a robotic device by using human brain signals is an interesting and challenging task. The device may be complicated to control and the nonstationary nature of the brain signals provides for a rather unstable input. With the use of intelligent processing algorithms adapted to the task at hand, however, the performance can be increased. This paper introduces a shared control system that helps the subject in driving an intelligent wheelchair with a noninvasive brain interface. The subject's steering intentions are estimated from electroencephalogram (EEG) signals and passed through to the shared control system before being sent to the wheelchair motors. Experimental results show a possibility for significant improvement in the overall driving performance when using the shared control system compared to driving without it. These results have been obtained with 2 healthy subjects during their first day of training with the brain-actuated wheelchair.

Electroencephalogram activity in the anoxic turtle brain

1997 ◽  
Vol 273 (3) ◽  
pp. R911-R919 ◽  
Author(s):  
J. A. Fernandes ◽  
P. L. Lutz ◽  
A. Tannenbaum ◽  
A. T. Todorov ◽  
L. Liebovitch ◽  
...  
Keyword(s):  
Transition Period ◽  
Activity Level ◽  
Sharp Waves ◽  
Energy Demands ◽  
Order Of Magnitude ◽  
Activity State ◽  
Low Amplitude ◽  
Electroencephalogram Eeg ◽  
Electrical Activities ◽  
The Brain

The anoxia-tolerant turtle brain slowly undergoes a complex sequence of changes in electroencephalogram (EEG) activity as the brain systematically downregulates its energy demands. Following N2 respiration, the root mean square voltage rapidly fell, reaching approximately 20% of normoxic levels after approximately 100 min of anoxia. During the first 20- to 40-min transition period, the power of the EEG decreased substantially, particularly in the 12- to 24-Hz band, with low-amplitude slow wave activity predominating (3-12 Hz). Bursts of high voltage rhythmic slow (approximately 3-8 Hz) waves were seen during the 20- to 100-min period of anoxia, accompanied by large sharp waves. During the next 400 min of N2 respiration, two distinct patterns of electrical activity characterized the anoxic turtle brain: 1) a sustained but depressed activity level, with an EEG amplitude approximately 20% of the normoxic control and with total EEG power reduced by one order of magnitude at all frequencies, and 2) short (3-15 s) periodic (0.5-2/min) bursts of mixed-frequency activity that interrupted the depressed activity state. We speculate that the EEG patterns seen during sustained anoxia represent the minimal or basic electrical activities that are compatible with the survival of the anoxic turtle brain as an integrated unit, which allow the brain to return to normal functioning when air respiration resumed.

scholarly journals EEG and Sonic Platforms to Enhance Mindfulness Meditation

2016 ◽  
Vol 5 (9) ◽  
pp. 1
Author(s):  
Caitilin De Berigny ◽  
Freya Zinovieff ◽  
Karen Cochrane ◽  
Youngdong Kim ◽  
Zhepeng Rui
Keyword(s):  
Clinical Practice ◽  
Mindfulness Meditation ◽  
Interactive Design ◽  
Historical Background ◽  
Technology Research ◽  
Interactive Installation ◽  
Interactive Applications ◽  
Physiological Processes ◽  
Electroencephalogram Eeg ◽  
The Brain

<p>This paper explores interactive applications that encourage mindfulness through sensors and novel input technology. Research in psychology and neuroscience demonstrating the benefits of mindfulness is initiating a new movement in interactive design. As cutting edge technologies become more accessible they are being employed to research and explore the practice of mindfulness. We examine three interactive installation artworks that promote mindfulness. In order to contextualize the interactive artworks discussed we first examine the historical background of the Electroencephalogram (EEG). We then discuss the physiological processes of meditation and the history behind the clinical practice of mindfulness. We show how artists and designers employ EEG sensors, to record the electrical activity of the brain to visualize mindfulness meditation practices. Lastly, we conclude the paper by discussing the future of the three artworks.</p>

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