scholarly journals Human Emotion Detection using Eeg Sensor

2020 ◽  
Vol 9 (5) ◽  
pp. 409-413
Keyword(s):  
Data Visualization ◽  
Concentration Level ◽  
Brain Activity ◽  
Emotion Detection ◽  
Attention Span ◽  
Brain Waves ◽  
Alpha Beta ◽  
The Right ◽  
The Waves ◽  
The Brain

This is a data visualization art piece using 10 seconds of mind waves recordings of the human, captured with EEG sensor.10 seconds of Alpha, Beta, Gamma & Theta brain waves while meditating are recorded, the different wave channels are categorized to state when the right brain representing artistic brain activity, isolating the ranges for each channel when the brain channels were more meditating and imaginative. Based on the waves of the brain obtained, we will be able to deduce few attributes such as attention span and mood. The moods we will be trying to assess and display here the level of happiness, sadness, anger along with attention span and meditation level (Concentration level).

Cerebral Activation Patterns Of Older Adults While Performing The Functional Gait Test

2020 ◽  
Author(s):  
Larissa Bastos Tavares ◽  
Idaliana Fagundes de Souza ◽  
Bartolomeu Fagundes de Lima Filho ◽  
Kim Mansur Yano ◽  
Juliana Maria Gazzola ◽  
...  
Keyword(s):  
Older Adults ◽  
Dual Task ◽  
Right Hemisphere ◽  
Brain Activity ◽  
Complex Task ◽  
Simple Task ◽  
Brain Waves ◽  
The Right ◽  
Functional Gait ◽  
The Brain

Abstract Dual-task activities are common in daily life and have greater motor/cognitive demands. These are conditions that increase the risk of older adult falls. Falls are a public health problem. Brain mapping during dual-task activities can inform which therapeutic activities stimulate specific brain areas, improving functionality, and decreasing dependence and the risk of falls. The objective of the study was to characterize the brain activity of healthy older adults while performing a dual-task activity called the Functional Gait Test (FGT). Method : This observational study included 30 older adults aged 65 to 75 years, and it was approved by the institutional review board. The FGT consists of walking following a sequence of numbers (simple task), and a sequence of alternating letters and numbers (complex task). During the activity, the subjects had their cortical activation pattern measured using the Emotiv EPOC® electroencephalogram. Complete data was obtained for analysis on 13 participants. The data was analyzed using descriptive statistics (mean and standard deviation), and paired T-tests to compare the brain activity during the conditions (simple vs. complex task). Results : Alpha brain waves were activated in the right and left hemispheres during the simple task, while Alpha brain waves’ activation during the complex task was predominant in the right hemisphere. However, the differences were not statistically significant. The Betha waves had predominant activation in the left hemisphere during the simple task, and predominant activation in the right hemisphere during the complex task. The difference was statistically significant in 11 out of the 14 channels evaluated ( P <0.04). Conclusion: The results corroborates the increased complexity of dual-tasks due to the predominant activation of the right hemisphere, which is related to motor learning process and new stimulus processing.

Adaptation of Rehabilitation System Based on User’s Mental Engagement

2015 ◽  
Author(s):  
Ehsan T. Esfahani ◽  
Shrey Pareek ◽  
Pramod Chembrammel ◽  
Mostafa Ghobadi ◽  
Thenkurussi Kesavadas
Keyword(s):  
Brain Activity ◽  
Difficulty Level ◽  
The Novel ◽  
Theta Band ◽  
Robotic Rehabilitation ◽  
Designed Experiments ◽  
Power Spectral ◽  
Rehabilitation System ◽  
Alpha Beta ◽  
The Brain

Recognition of user’s mental engagement is imperative to the success of robotic rehabilitation. The paper explores the novel paradigm in robotic rehabilitation of using Passive BCI as opposed to the conventional Active ones. We have designed experiments to determine a user’s level of mental engagement. In our experimental study, we record the brain activity of 3 healthy subjects during multiple sessions where subjects need to navigate through a maze using a haptic system with variable resistance/assistance. Using the data obtained through the experiments we highlight the drawbacks of using conventional workload metrics as indicators of human engagement, thus asserting that Motor and Cognitive Workloads be differentiated. Additionally we propose a new set of features: differential PSD of Cz-Poz at alpha, Beta and Sigma band, (Mental engagement) and relative C3-C4 at beta (Motor Workload) to distinguish Normal Cases from those instances when haptic where applied with an accuracy of 92.93%. Mental engagement is calculated using the power spectral density of the Theta band (4–7 Hz) in the parietal-midline (Pz) with respect to the central midline (Cz). The above information can be used to adjust robotic rehabilitation parameters I accordance with the user’s needs. The adjustment may be in the force levels, difficulty level of the task or increasing the speed of the task.

Consciousness Emanates from the Neuronal Network of Coordination, A Fact Endorsed by Preserved Consciousness in Focal Ischemic Infarctions

2021 ◽  
Vol 19 (3) ◽  
pp. 17-25
Author(s):  
Dr. Sohail Adnan ◽  
Dr. Mubasher Shah ◽  
Dr. Syed Fahim Shah ◽  
Dr. Fahad Naim ◽  
Dr. Akhtar Ali ◽  
...  
Keyword(s):  
Cerebral Cortex ◽  
Neuronal Network ◽  
Brain Activity ◽  
Cross Sectional Study ◽  
Difficult Problem ◽  
Altered Consciousness ◽  
Cross Sectional ◽  
Consciousness Disorder ◽  
The Right ◽  
The Brain

Background: Consciousness has remained a difficult problem for the scientists to explore its relationship to the brain activity. This is the first paper that presents the significance of focal areas of the cerebral cortex for consciousness. Objectives: To determine if consciousness is produced by the activity of the whole brain or one of its focal areas. Methods: We have performed a prospective cross-sectional study in eighty patients of acute ischemic stroke. The neurovascular territory of the middle cerebral artery (MCA) was sectioned into four similar areas. The association of any of these focal areas to consciousness was observed after their dysfunction with ischemic strokes. Results: Of the eighty patients, 57.5 % were males and 42.5 % were females. Mean age was 63 years ± 7 SD. The righthanded patients were 90 % (72) of the whole sample. Focal areas of the right MCA were generally less prone to consciousness disorder. Average statistics of the focal infarctions of the right MCA showed no tendency for consciousness disorder on the Glasgow coma scale (GCS) [Mean GCS of all focal areas; 14.5, SD; 0.71, 95 % CI; 14.27 to 14.72, P= 0.0000004]. Altered consciousness with focal infarctions of the territory of left MCA was also less likely [Mean GCS of all focal areas; 14.2, SD; 1.01, 95 % CI; 13.88 to 14.51, P= 0.0004]. Conclusion: Consciousness is not determined by the activity of a focal area of the cerebral cortex. Perhaps, we get our consciousness from the activity of “Neuronal Network of Coordination”.

scholarly journals Association Between Trait Empathy and Resting Brain Activity in Women With Primary Dysmenorrhea During the Pain and Pain-Free Phases

2020 ◽  
Vol 11 ◽  
Author(s):  
Wanghuan Dun ◽  
Tongtong Fan ◽  
Qiming Wang ◽  
Ke Wang ◽  
Jing Yang ◽  
...  
Keyword(s):  
Brain Activity ◽  
Inferior Frontal Gyrus ◽  
Brain Network ◽  
Primary Dysmenorrhea ◽  
Pain Experience ◽  
Current State ◽  
The Neural Network ◽  
The Right ◽  
The Brain

Empathy refers to the ability to understand someone else's emotions and fluctuates with the current state in healthy individuals. However, little is known about the neural network of empathy in clinical populations at different pain states. The current study aimed to examine the effects of long-term pain on empathy-related networks and whether empathy varied at different pain states by studying primary dysmenorrhea (PDM) patients. Multivariate partial least squares was employed in 46 PDM women and 46 healthy controls (HC) during periovulatory, luteal, and menstruation phases. We identified neural networks associated with different aspects of empathy in both groups. Part of the obtained empathy-related network in PDM exhibited a similar activity compared with HC, including the right anterior insula and other regions, whereas others have an opposite activity in PDM, including the inferior frontal gyrus and right inferior parietal lobule. These results indicated an abnormal regulation to empathy in PDM. Furthermore, there was no difference in empathy association patterns in PDM between the pain and pain-free states. This study suggested that long-term pain experience may lead to an abnormal function of the brain network for empathy processing that did not vary with the pain or pain-free state across the menstrual cycle.

scholarly journals Fractal Dimension as Quantifier of EEG Activity in Driving Simulation

Mathematics ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1311
Author(s):  
Mª Victoria Sebastián ◽  
Mª Antonia Navascués ◽  
Antonio Otal ◽  
Carlos Ruiz ◽  
Mª Ángeles Idiazábal ◽  
...  
Keyword(s):  
Fractal Dimension ◽  
Brain Activity ◽  
Fractal Theory ◽  
Driving Simulation ◽  
Geometric Complexity ◽  
Eeg Activity ◽  
Modeling And Analysis ◽  
Brain Waves ◽  
Electroencephalographic Signals ◽  
The Brain

Dynamical systems and fractal theory methodologies have been proved useful for the modeling and analysis of experimental datasets and, in particular, for electroencephalographic signals. The computation of the fractal dimension of approximation curves in the plane enables the assignment of numerical values to bioelectric recordings in order to discriminate between different states of the observed system. The procedure does not require the stationarity of the signals nor extremely long segments of data. In previous works, we checked that this parameter is a good index for brain activity. In this paper, we consider this measurement in order to quantify the geometric complexity of the brain waves in states of rest and during vehicle driving simulation in different scenarios. This work presents evidence that the fractal dimension allows the detection of the brain bioelectric changes produced in the areas that carry out the different driving simulation tasks, increasing with their complexity.

scholarly journals Dissociating Neural Correlates of Action Monitoring and Metacognition of Agency

2011 ◽  
Vol 23 (11) ◽  
pp. 3620-3636 ◽  
Author(s):  
David B. Miele ◽  
Tor D. Wager ◽  
Jason P. Mitchell ◽  
Janet Metcalfe
Keyword(s):  
Brain Activity ◽  
Dorsal Striatum ◽  
Neural Correlates ◽  
Action Monitoring ◽  
Fmri Study ◽  
Metacognitive Judgments ◽  
The Right ◽  
Reflective Processing ◽  
Increased Activity ◽  
The Brain

Judgments of agency refer to people's self-reflective assessments concerning their own control: their assessments of the extent to which they themselves are responsible for an action. These self-reflective metacognitive judgments can be distinguished from action monitoring, which involves the detection of the divergence (or lack of divergence) between observed states and expected states. Presumably, people form judgments of agency by metacognitively reflecting on the output of their action monitoring and then consciously inferring the extent to which they caused the action in question. Although a number of previous imaging studies have been directed at action monitoring, none have assessed judgments of agency as a potentially separate process. The present fMRI study used an agency paradigm that not only allowed us to examine the brain activity associated with action monitoring but that also enabled us to investigate those regions associated with metacognition of agency. Regarding action monitoring, we found that being “out of control” during the task (i.e., detection of a discrepancy between observed and expected states) was associated with increased brain activity in the right TPJ, whereas being “in control” was associated with increased activity in the pre-SMA, rostral cingulate zone, and dorsal striatum (regions linked to self-initiated action). In contrast, when participants made self-reflective metacognitive judgments about the extent of their own control (i.e., judgments of agency) compared with when they made judgments that were not about control (i.e., judgments of performance), increased activity was observed in the anterior PFC, a region associated with self-reflective processing. These results indicate that action monitoring is dissociable from people's conscious self-attributions of control.

Perspective-taking in blindness: electrophysiological evidence of altered action representations

2013 ◽  
Vol 109 (2) ◽  
pp. 405-414 ◽  
Author(s):  
Luís Aureliano Imbiriba ◽  
Maitê Mello Russo ◽  
Laura Alice Santos de Oliveira ◽  
Ana Paula Fontana ◽  
Erika de Carvalho Rodrigues ◽  
...  
Keyword(s):  
Motor Imagery ◽  
Brain Activity ◽  
Motor Preparation ◽  
Middle Finger ◽  
Mental Simulation ◽  
Movement Imagery ◽  
Similar Motor ◽  
The Right ◽  
The Brain ◽  
Action Representations

It is well established that the mental simulation of actions involves visual and/or somatomotor representations of those imagined actions. To investigate whether the total absence of vision affects the brain activity associated with the retrieval of motor representations, we recorded the readiness potential (RP), a marker of motor preparation preceding the execution, as well as the motor imagery of the right middle-finger extension in the first-person (1P; imagining oneself performing the movement) and in the third-person (3P; imagining the experimenter performing the movement) modes in 19 sighted and 10 congenitally blind subjects. Our main result was found for the single RP slope values at the Cz channel (likely corresponding to the supplementary motor area). No difference in RP slope was found between 1P and 3P in the sighted group, suggesting that similar motor preparation networks are recruited to simulate our own and other people's actions in spite of explicit instructions to perform the task in 1P or 3P. Conversely, reduced RP slopes in 3P compared with 1P found in the blind group indicated that they might have used an alternative, nonmotor strategy to perform the task in 3P. Moreover, movement imagery ability, assessed both by means of mental chronometry and a modified version of the Movement Imagery Questionnaire-Revised, indicated that blind and sighted individuals had similar motor imagery performance. Taken together, these results suggest that complete visual loss early in life modifies the brain networks that associate with others' action representations.

scholarly journals Deep Learning on Game Addiction Detection Based on Electroencephalogram

2021 ◽  
Vol 5 (3) ◽  
pp. 963
Author(s):  
Lalu Arfi Maulana Pangistu ◽  
Ahmad Azhari
Keyword(s):  
Brain Activity ◽  
Late Adolescence ◽  
Wave Activity ◽  
Test Results ◽  
Brain Wave ◽  
Brain Waves ◽  
Game Addiction ◽  
Brain Wave Activity ◽  
Electroencephalogram Eeg ◽  
The Brain

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. 

scholarly journals Comparing Concentration Levels and Emotional States of Children Using Electroencephalography during Horticultural and Nonhorticultural Activities

HortScience ◽  
2021 ◽  
pp. 1-6
Author(s):  
Seon-Ok Kim ◽  
Ji-Eun Jeong ◽  
Yun-Ah Oh ◽  
Ha-Ram Kim ◽  
Sin-Ae Park
Keyword(s):  
Power Spectrum ◽  
Brain Activity ◽  
Differential Method ◽  
Emotional States ◽  
University Campus ◽  
School Students ◽  
Folding Paper ◽  
The Right ◽  
Math Problems ◽  
The Brain

This study aimed to compare the brain activity and emotional states of elementary school students during horticultural and nonhorticultural activities. A total of 30 participants with a mean age of 11.4 ± 1.3 years were included. This experiment was conducted at Konkuk University campus in Korea. Participants performed horticultural activities such as harvesting, planting, sowing seeds, and mixing soil. Nonhorticultural activities included playing with a ball, solving math problems, watching animation videos, folding paper, and reading a book. The study had a crossover experimental design. Brain activity of the prefrontal lobes was measured by electroencephalography during each activity for 3 minutes. On completion of each activity, participants answered a subjective emotion questionnaire using the semantic differential method (SDM). Results showed that relative theta (RT) power spectrum was significantly lower in both prefrontal lobes of participants when engaged in harvesting and reading a book. The relative mid beta (RMB) power spectrum was significantly higher in both prefrontal lobes when participants engaged in harvesting and playing with a ball. The ratio of the RMB power spectrum to the RT power spectrum reflects concentration. This ratio increased during harvesting activity, indicating that children’s concentration also increased. The sensorimotor rhythm (SMR) from mid beta to theta (RSMT), another indicator of concentration, was significantly higher in the right prefrontal lobe during harvesting than during other activities. Furthermore, SDM results showed that the participants felt more natural and relaxed when performing horticultural activities than nonhorticultural activities. Horticultural activities may improve brain activity and psychological relaxation in children. Harvesting activity was most effective for improving children’s concentration compared with nonhorticultural activities.

Development of a Hardware Circuit for Real-Time Acquisition of Brain Activity Using NI myDAQ

2020 ◽  
Vol 29 (10) ◽  
pp. 2050170
Author(s):  
Oinam Robita Chanu ◽  
R. Kalpana ◽  
B. Soorya ◽  
R. Santhosh ◽  
V. Karthik Raj
Keyword(s):  
Electrical Activity ◽  
Virtual Instrument ◽  
Single Channel ◽  
Electrode Placement ◽  
Eeg Signal ◽  
Brain Waves ◽  
Theta Waves ◽  
Patient Preparation ◽  
Alpha Beta ◽  
The Brain

Electroencephalography (EEG) is the recording of electrical activity of the brain. The 10–20 system is the standard electrode location method used to acquire EEG data, which uses 21 electrodes to record the electrical activity of the brain. Patient preparation and correct electrode placement are important to obtain reliable outputs. The current 10–20 system consumes greater time for patient preparation and also causes discomfort due to a higher number of electrodes being used or wearing an uncomfortable cap. This paper focuses on reducing the number of electrodes, thus reducing patient discomfort as well as preparation time. Advancement in the field of hardware and software processing has led to the utilization of brain waves for communication between human and the computer. This work deals with EEG-based Brain–Machine Interface (BMI) intended for designing a portable single-channel EEG signal acquisition system. EEG signal was acquired using the data acquisition module [National Instruments (NI) myDAQ] and the signal was viewed in the NI Laboratory Virtual Instrument Engineering Workbench (LabVIEW) environment. It was observed that the peak-to-peak amplitude of alpha, beta and theta waves changes in accordance with the activity the subjects performed. Thus, the developed instrument was tested on 10 different subjects to acquire the alpha, beta and theta waves by performing different activities. From the results, it can be concluded that the developed system can be used for studying a person’s brain waves (alpha, beta and theta) based on the activity performed by the subject with a limited number of electrodes.

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