scholarly journals Power-law scaling of brain wave activity associated with mental fatigue

2020 ◽  
Author(s):  
Vo V. Anh ◽  
Hung T. Nguyen ◽  
Ashley Craig ◽  
Yvonne Tran ◽  
Yu Guang Wang

AbstractThis paper investigates the cause and detection of power-law scaling of brain wave activity due to the heterogeneity of the brain cortex, considered as a complex system, and the initial condition such as the alert or fatigue state of the brain. Our starting point is the construction of a mathematical model of global brain wave activity based on EEG measurements on the cortical surface. The model takes the form of a stochastic delay-differential equation (SDDE). Its fractional diffusion operator and delay operator capture the responses due to the heterogeneous medium and the initial condition. The analytical solution of the model is obtained in the form of a Karhunen-Loève expansion. A method to estimate the key parameters of the model and the corresponding numerical schemes are given. Real EEG data on driver fatigue at 32 channels measured on 50 participants are used to estimate these parameters. Interpretation of the results is given by comparing and contrasting the alert and fatigue states of the brain.The EEG time series at each electrode on the scalp display power-law scaling, as indicated by their spectral slopes in the low-frequency range. The diffusion of the EEG random field is non-Gaussian, reflecting the heterogeneity of the brain cortex. This non-Gaussianity is more pronounced for the alert state than the fatigue state. The response of the system to the initial condition is also more significant for the alert state than the fatigue state. These results demonstrate the usefulness of global SDDE modelling complementing the time series approach for EEG analysis.

2021 ◽  
Vol 5 (3) ◽  
pp. 963
Author(s):  
Lalu Arfi Maulana Pangistu ◽  
Ahmad Azhari

Playing games for too long can be addictive. Based on a recent study by Brand et al, adolescents are considered more vulnerable than adults to game addiction. The activity of playing games produces a wave in the brain, namely beta waves where the person is in a focused state. Brain wave activity can be measured and captured using an Electroencephalogram (EEG). Recording brain wave activity naturally requires a prominent and constant brain activity such as when concentrating while playing a game. This study aims to detect game addiction in late adolescence by applying Convolutional Neural Network (CNN). Recording of brain waves was carried out three times for each respondent with a stimulus to play three different games, namely games included in the easy, medium, and hard categories with a consecutive taking time of 10 minutes, 15 minutes, and 30 minutes. Data acquisition results are feature extraction using Fast Fourier Transform to get the average signal for each respondent. Based on the research conducted, obtained an accuracy of 86% with a loss of 0.2771 where the smaller the loss value, the better the CNN model built. The test results on the model produce an overall accuracy of 88% with misclassification in 1 data. The CNN model built is good enough for the detection of game addiction in late adolescence. 


2002 ◽  
Vol 95 (3) ◽  
pp. 955-962 ◽  
Author(s):  
Jong Ran Park ◽  
Takami Yagyu ◽  
Naomi Saito ◽  
Toshihiko Kinoshita ◽  
Takane Hirai

The brain wave activity of a professional Salpuri dancer was observed while the subject recalled her performance of the Salpuri dance when sitting in a chair with closed eyes. As she recalled the feeling of the ecstatic trance state induced by the dance, an increase in alpha brain activity was observed together with marked frontal midline theta activity. Compared to a resting state, the dynamics of the electrical activity in the brain showed an increase in the global field power integral and a decrease in generalized frequency and spatial complexity.


2019 ◽  
Vol 10 (1) ◽  
pp. 76-80 ◽  
Author(s):  
Yunjuan Liu ◽  
Yan Wang

AbstractDespite the importance of clothing pressure discomfort in the undergarment industry, a reliable unbiased measurement of clothing pressure discomfort has not been well-established. In the present study, we investigate changes in brain wave activity as a potential objective and consistent measuring tool for clothing pressure discomfort. We recorded α wave activity in 5 functional regions (30 channels) of the brain in 10 females with or without a girdle. We determined that α wave power spectrum significantly increases when the girdle is worn compared to when it is not worn, specifically in the parietal and occipital regions. These findings suggest that clothing pressure exerted by wearing a girdle mostly stimulates the parietal and occipital regions and that these regions should be investigated in future studies using α wave energy to measure clothing pressure discomfort.


1998 ◽  
Vol 34 (1) ◽  
pp. 84-91 ◽  
Author(s):  
A Bufalari ◽  
SM Miller ◽  
C Giannoni ◽  
CE Short

Cardiovascular, pulmonary, and quantitative electroencephalographic parameters were assessed in 12 anesthetized dogs to determine the compatibility of the injectable anesthetic propofol with halothane and isoflurane. No cases of apnea were observed during induction of anesthesia. An adequate level of anesthesia was established in each protocol as judged by both the lack of response to mechanical noxious stimuli (i.e., tail clamping) and evidence of reduction in total amplitude of brain wave activity. The initial propofol-mediated decrease in arterial blood pressure continued during either halothane (52.4%) or isoflurane (38%) anesthesia without a simultaneous increase in heart rate. The results of this study suggest that propofol, in combination with inhalant agents, can be used effectively and safely for canine anesthesia in veterinary practice.


2007 ◽  
Vol 117 (12) ◽  
pp. 1731-1746 ◽  
Author(s):  
D. HERBERT ◽  
Y. TRAN ◽  
A. CRAIG ◽  
P. BOORD ◽  
J. MIDDLETON ◽  
...  

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