scholarly journals Green Communications: Techniques and Challenges

2021 ◽  
pp. 55-59
Author(s):  
Dr. M. V. Karthikeyan ◽  
R. Rakshana ◽  
M. Sanjana
Keyword(s):  
Time Delay ◽  
Pulse Rate ◽  
Brain Activity ◽  
Cloud Platform ◽  
Green Communications ◽  
Patient Health ◽  
Patient Will ◽  
The Brain ◽  
Bedridden Patient

Virtual Brain Model is one of the interesting research works. In this paper we have developed a model to ensure security for E-Will using IOT and also monitor the Patient Health using Sweat Sensor. The Brain Activity of the patient is monitored using EEG electrodes and the collected data are stored in the cloud platform with the help of IOT Module. The E-Will will be uploaded in cloud Platform in presence of Notary. Hence, The Brain Activity of the patient will be monitored accurately and once the electrodes senses there is no brain activity, Then the device wait for certain time delay and confirms there is no brain activity. Therefore, after the confirmation the E-Will will be sent to the authorized person through mail or a message. The patient health is Monitored with the help of Sweat Sensor. When the bedridden patient has any heart related abnormalities the person starts to sweat initially, indication with this temperature and pulse rate is monitored if any abnormalities found the information is sent to the doctor immediately via GSM Module. This ensures that the patients can be taken much care and the life of the patient can be saved without any delay.

scholarly journals Virtual Brain: Model Based Framework for Dependable EEG Sensing and Actuation In Intelligent Brain IoT System

2021 ◽  
pp. 55-59
Author(s):  
Dr. M. V. Karthikeyan ◽  
R. Rakshana ◽  
M. Sanjana
Keyword(s):  
Time Delay ◽  
Pulse Rate ◽  
Brain Activity ◽  
Cloud Platform ◽  
Model Based ◽  
Patient Health ◽  
Patient Will ◽  
The Brain ◽  
Bedridden Patient

Virtual Brain Model is one of the interesting research works. In this paper we have developed a model to ensure security for E-Will using IOT and also monitor the Patient Health using Sweat Sensor. The Brain Activity of the patient is monitored using EEG electrodes and the collected data are stored in the cloud platform with the help of IOT Module. The E-Will will be uploaded in cloud Platform in presence of Notary. Hence, The Brain Activity of the patient will be monitored accurately and once the electrodes senses there is no brain activity, Then the device wait for certain time delay and confirms there is no brain activity. Therefore, after the confirmation the E-Will will be sent to the authorized person through mail or a message. The patient health is Monitored with the help of Sweat Sensor. When the bedridden patient has any heart related abnormalities the person starts to sweat initially, indication with this temperature and pulse rate is monitored if any abnormalities found the information is sent to the doctor immediately via GSM Module. This ensures that the patients can be taken much care and the life of the patient can be saved without any delay.

Complexity Measures of Brain Electrophysiological Activity

2010 ◽  
Vol 24 (2) ◽  
pp. 131-135 ◽  
Author(s):  
Włodzimierz Klonowski ◽  
Pawel Stepien ◽  
Robert Stepien
Keyword(s):  
Brain Activity ◽  
Deterministic Chaos ◽  
Epileptic Seizures ◽  
Eeg Signal ◽  
Eeg Signals ◽  
Complexity Measures ◽  
Electrophysiological Activity ◽  
Signal Complexity ◽  
Physiological Sleep ◽  
The Brain

Over 20 years ago, Watt and Hameroff (1987 ) suggested that consciousness may be described as a manifestation of deterministic chaos in the brain/mind. To analyze EEG-signal complexity, we used Higuchi’s fractal dimension in time domain and symbolic analysis methods. Our results of analysis of EEG-signals under anesthesia, during physiological sleep, and during epileptic seizures lead to a conclusion similar to that of Watt and Hameroff: Brain activity, measured by complexity of the EEG-signal, diminishes (becomes less chaotic) when consciousness is being “switched off”. So, consciousness may be described as a manifestation of deterministic chaos in the brain/mind.

Relation Between Level of Prefrontal Activity and Subject's Performance

1999 ◽  
Vol 13 (2) ◽  
pp. 117-125 ◽  
Author(s):  
Laurence Casini ◽  
Françoise Macar ◽  
Marie-Hélène Giard
Keyword(s):  
Brain Activity ◽  
Sensory Information ◽  
Practice Phase ◽  
Trained Subjects ◽  
Anagram Task ◽  
Economic Information ◽  
Long Duration ◽  
Level Of Activity ◽  
The Brain ◽  
Processing Mechanism

Abstract The experiment reported here was aimed at determining whether the level of brain activity can be related to performance in trained subjects. Two tasks were compared: a temporal and a linguistic task. An array of four letters appeared on a screen. In the temporal task, subjects had to decide whether the letters remained on the screen for a short or a long duration as learned in a practice phase. In the linguistic task, they had to determine whether the four letters could form a word or not (anagram task). These tasks allowed us to compare the level of brain activity obtained in correct and incorrect responses. The current density measures recorded over prefrontal areas showed a relationship between the performance and the level of activity in the temporal task only. The level of activity obtained with correct responses was lower than that obtained with incorrect responses. This suggests that a good temporal performance could be the result of an efficacious, but economic, information-processing mechanism in the brain. In addition, the absence of this relation in the anagram task results in the question of whether this relation is specific to the processing of sensory information only.

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 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.

scholarly journals Consciousness, decision making, and volition: freedom beyond chance and necessity

2021 ◽  
Author(s):  
Hans Liljenström
Keyword(s):  
Decision Making ◽  
Free Will ◽  
Brain Activity ◽  
Brain Structures ◽  
Complex Process ◽  
Neural Information ◽  
Neural Information Processing ◽  
Stochastic Population Model ◽  
The Brain

AbstractWhat is the role of consciousness in volition and decision-making? Are our actions fully determined by brain activity preceding our decisions to act, or can consciousness instead affect the brain activity leading to action? This has been much debated in philosophy, but also in science since the famous experiments by Libet in the 1980s, where the current most common interpretation is that conscious free will is an illusion. It seems that the brain knows, up to several seconds in advance what “you” decide to do. These studies have, however, been criticized, and alternative interpretations of the experiments can be given, some of which are discussed in this paper. In an attempt to elucidate the processes involved in decision-making (DM), as an essential part of volition, we have developed a computational model of relevant brain structures and their neurodynamics. While DM is a complex process, we have particularly focused on the amygdala and orbitofrontal cortex (OFC) for its emotional, and the lateral prefrontal cortex (LPFC) for its cognitive aspects. In this paper, we present a stochastic population model representing the neural information processing of DM. Simulation results seem to confirm the notion that if decisions have to be made fast, emotional processes and aspects dominate, while rational processes are more time consuming and may result in a delayed decision. Finally, some limitations of current science and computational modeling will be discussed, hinting at a future development of science, where consciousness and free will may add to chance and necessity as explanation for what happens in the world.

Information-based decoding of the coupling among human brain activity and movement paths

2021 ◽  
pp. 1-10
Author(s):  
Shahul Mujib Kamal ◽  
Norazryana Mat Dawi ◽  
Hamidreza Namazi
Keyword(s):  
Brain Activity ◽  
Point Of View ◽  
Physiological Signals ◽  
Human Walking ◽  
Eeg Signals ◽  
Rehabilitation Science ◽  
Information Contents ◽  
First Time ◽  
The Brain ◽  
Brain Reaction

BACKGROUND: Walking like many other actions of a human is controlled by the brain through the nervous system. In fact, if a problem occurs in our brain, we cannot walk correctly. Therefore, the analysis of the coupling of brain activity and walking is very important especially in rehabilitation science. The complexity of movement paths is one of the factors that affect human walking. For instance, if we walk on a path that is more complex, our brain activity increases to adjust our movements. OBJECTIVE: This study for the first time analyzed the coupling of walking paths and brain reaction from the information point of view. METHODS: We analyzed the Shannon entropy for electroencephalography (EEG) signals versus the walking paths in order to relate their information contents. RESULTS: According to the results, walking on a path that contains more information causes more information in EEG signals. A strong correlation (p= 0.9999) was observed between the information contents of EEG signals and walking paths. Our method of analysis can also be used to investigate the relation among other physiological signals of a human and walking paths, which has great benefits in rehabilitation science.

scholarly journals Negative Emotions in Migraineurs Dreams: The Increased Prevalence of Oneiric Fear and Anguish, Unrelated to Mood Disorders

2014 ◽  
Vol 2014 ◽  
pp. 1-4 ◽  
Author(s):  
F. De Angeli ◽  
C. Lovati ◽  
L. Giani ◽  
C. Mariotti D'Alessandro ◽  
E. Raimondi ◽  
...  
Keyword(s):  
Motor Skills ◽  
De Novo ◽  
Tension Type Headache ◽  
Anxiety And Depression ◽  
Generalized Anxiety ◽  
Migraine Pain ◽  
Patient Health ◽  
Type Headache ◽  
The Brain ◽  
Negative Connotation

Background. Migraineurs brain has shown some functional peculiarities that reflect not only in phonophobia, and photophobia, but also in mood and sleep. Dreaming is a universal mental state characterized by hallucinatory features in which imagery, emotion, motor skills, and memory are created de novo. We evaluated dream contents and associated emotions in migraineurs.Materials and Methods. 412 subjects: 219 controls; and 148 migraineurs (66 with aura, MA; 82 without aura, MO), and 45 tension type headache patients (TTH). A semistructured retrospective self-reported questionnaire was used to evaluate dreams. The Generalized Anxiety Disorder Questionnaire (GAD-7), and the Patient Health Questionnaire (PHQ-9) were administered to evaluate anxiety and depression.Results. Migraineurs showed increased levels of anxiety (P=0.0002for MA versus controls,P=0.004for MO versus controls). Fear and anguish during dreaming were more frequently reported by migraine patients compared to controls, independently by anxiety and depression scores.Discussion. The brain of migraineurs seems to dream with some peculiar features, all with a negative connotation, as fear and anguish. It may be due to the recorded negative sensations induced by recurrent migraine pain, but it may just reflect a peculiar attitude of the mesolimbic structures of migraineurs brain, activated in both dreaming and migraine attacks.

Neurodevelopment in the first three years: implications for child development, professional practice and policy

2014 ◽  
Vol 9 (2) ◽  
pp. 154-164 ◽  
Author(s):  
Danya Glaser
Keyword(s):  
Brain Development ◽  
Brain Activity ◽  
Brain Maturation ◽  
Policy And Practice ◽  
Content Type ◽  
Key Issues ◽  
And Function ◽  
The Relationship ◽  
The Brain ◽  
Brain Connections

Purpose – The purpose of this paper is to outline brain structure and development, the relationship between environment and brain development and implications for practice. Design/methodology/approach – The paper is based on a selected review of the literature and clinical experience. Findings – While genetics determine the sequence of brain maturation, the nature of brain development and functioning is determined by the young child's caregiving environment, to which the developing brain constantly adapts. The absence of input during sensitive periods may lead to later reduced functioning. There is an undoubted immediate equivalence between every mind function – emotion, cognition, behaviour and brain activity, although the precise location of this in the brain is only very partially determinable, since brain connections and function are extremely complex. Originality/value – This paper provides an overview of key issues in neurodevelopment relating to the development of young children, and implications for policy and practice.

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