An equivalent current source model and Laplacian weighted minimum norm current estimates of brain electrical activity

2002 ◽  
Vol 49 (4) ◽  
pp. 277-288 ◽  
Author(s):  
Bin He ◽  
D. Yao ◽  
J. Lian ◽  
D. Wu
Keyword(s):  
Electrical Activity ◽  
Current Source ◽  
Source Model ◽  
Minimum Norm ◽  
Brain Electrical Activity ◽  
Equivalent Current

Fit Vs Faint: Assessing Work Causation in “Idiopathic Fall” Cases

2014 ◽  
Vol 19 (5) ◽  
pp. 3-12
Author(s):  
Lorne Direnfeld ◽  
David B. Torrey ◽  
Jim Black ◽  
LuAnn Haley ◽  
Christopher R. Brigham
Keyword(s):  
Blood Flow ◽  
Electrical Activity ◽  
Loss Of Consciousness ◽  
Brain Electrical Activity ◽  
Medical Terminology ◽  
Scientific Analysis ◽  
Medical Causation ◽  
The Individual ◽  
The Brain ◽  
Current Science

Abstract When an individual falls due to a nonwork-related episode of dizziness, hits their head and sustains injury, do workers’ compensation laws consider such injuries to be compensable? Bearing in mind that each state makes its own laws, the answer depends on what caused the loss of consciousness, and the second asks specifically what happened in the fall that caused the injury? The first question speaks to medical causation, which applies scientific analysis to determine the cause of the problem. The second question addresses legal causation: Under what factual circumstances are injuries of this type potentially covered under the law? Much nuance attends this analysis. The authors discuss idiopathic falls, which in this context means “unique to the individual” as opposed to “of unknown cause,” which is the familiar medical terminology. The article presents three detailed case studies that describe falls that had their genesis in episodes of loss of consciousness, followed by analyses by lawyer or judge authors who address the issue of compensability, including three scenarios from Arizona, California, and Pennsylvania. A medical (scientific) analysis must be thorough and must determine the facts regarding the fall and what occurred: Was the fall due to a fit (eg, a seizure with loss of consciousness attributable to anormal brain electrical activity) or a faint (eg, loss of consciousness attributable to a decrease in blood flow to the brain? The evaluator should be able to fully explain the basis for the conclusions, including references to current science.

scholarly journals Identification of Brain Electrical Activity Related to Head Yaw Rotations

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3345
Author(s):  
Enrico Zero ◽  
Chiara Bersani ◽  
Roberto Sacile
Keyword(s):  
Electrical Activity ◽  
Electrical Stimulus ◽  
Head Movements ◽  
Brain Electrical Activity ◽  
Output Function ◽  
Input Output ◽  
Eeg Signals ◽  
Head Turning ◽  
Identification Technique ◽  
The Brain

Automatizing the identification of human brain stimuli during head movements could lead towards a significant step forward for human computer interaction (HCI), with important applications for severely impaired people and for robotics. In this paper, a neural network-based identification technique is presented to recognize, by EEG signals, the participant’s head yaw rotations when they are subjected to visual stimulus. The goal is to identify an input-output function between the brain electrical activity and the head movement triggered by switching on/off a light on the participant’s left/right hand side. This identification process is based on “Levenberg–Marquardt” backpropagation algorithm. The results obtained on ten participants, spanning more than two hours of experiments, show the ability of the proposed approach in identifying the brain electrical stimulus associate with head turning. A first analysis is computed to the EEG signals associated to each experiment for each participant. The accuracy of prediction is demonstrated by a significant correlation between training and test trials of the same file, which, in the best case, reaches value r = 0.98 with MSE = 0.02. In a second analysis, the input output function trained on the EEG signals of one participant is tested on the EEG signals by other participants. In this case, the low correlation coefficient values demonstrated that the classifier performances decreases when it is trained and tested on different subjects.

Alteration of brain electrical activity by electromagnetic field

2007 ◽  
Vol 27 (4) ◽  
pp. 417-422 ◽  
Author(s):  
Marina Rezinkina ◽  
Eleonora Bydianskaya ◽  
Anatoliy Shcherba
Keyword(s):  
Electromagnetic Field ◽  
Electrical Activity ◽  
Brain Electrical Activity

Correlation of brain electrical activity and motivation in healthy people

2014 ◽  
Vol 40 (4) ◽  
pp. 390-396
Author(s):  
L. V. Bogovin ◽  
D. L. Nakhamchen ◽  
V. P. Kolosov ◽  
J. M. Perelman
Keyword(s):  
Electrical Activity ◽  
Healthy People ◽  
Brain Electrical Activity

Use of brain electrical activity to quantify traumatic brain injury in the emergency department

Brain Injury ◽  
2010 ◽  
Vol 24 (11) ◽  
pp. 1324-1329 ◽  
Author(s):  
Rosanne S. Naunheim ◽  
Matthew Treaster ◽  
Joy English ◽  
Teya Casner ◽  
Robert Chabot
Keyword(s):  
Traumatic Brain Injury ◽  
Emergency Department ◽  
Brain Injury ◽  
Electrical Activity ◽  
Brain Electrical Activity

Dynamics of brain electrical activity

1989 ◽  
Vol 2 (1-2) ◽  
pp. 99-118 ◽  
Author(s):  
Paul E. Rapp ◽  
Theodore R. Bashore ◽  
Jacques M. Martinerie ◽  
A. M. Albano ◽  
I. D. Zimmerman ◽  
...  
Keyword(s):  
Electrical Activity ◽  
Brain Electrical Activity
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