This document outlines a study that aims to evaluate stress levels precisely using physiological signals like EEG, EOG, and GSR. It details a protocol involving a letter identification task with three difficulty levels to induce varying stress levels. References are provided on related studies using wavelet transforms of EEG to assess mental workload and the effects of mental stress on heart rate variability and blood pressure during computer work.
EXAMINATION OF THE SKIN CONDUCTANCE LEVEL (SCL) AS AN INDEX OF THE ACTIVITY O...ijbesjournal
This paper displays standardized measurements to examine the skin conductance level (SCL) as an index for the sympathetic nervous system’s activity considering a possible standardization of personal variability. SCL measurements were performed at baseline, Cold-Pressor-Tests and Stroop Tests for 15 subjects and inter- and intra-individual mean SCL values were examined. The logarithmic representation displays a high inter-individual variability, denoted by a high fluctuation range of the absolute values and SCL amplitudes. A standardization of inter-individuality could not be achieved by the applied methods (range correction and z-transformation). For the relative intra-individual comparison of the stress situation to the baseline, a method of correction for the determination of the real effect of sympathetic activation was established. EDA should be combined with other parameters of the ANS for a more precise evaluation of stress situations in the context of changes in blood pressure.
Feature Extraction Techniques and Classification Algorithms for EEG Signals t...Editor IJCATR
EEG (Electroencephalogram) signal is a neuro signal which is generated due the different electrical activities in the brain.
Different types of electrical activities correspond to different states of the brain. Every physical activity of a person is due to some
activity in the brain which in turn generates an electrical signal. These signals can be captured and processed to get the useful information
that can be used in early detection of some mental diseases. This paper focus on the usefulness of EGG signal in detecting the human
stress levels. It also includes the comparison of various preprocessing algorithms ( DCT and DWT.) and various classification algorithms
(LDA, Naive Bayes and ANN.). The paper proposes a system which will process the EEG signal and by applying the combination of
classifiers, will detect the human stress levels.
EXAMINATION OF THE SKIN CONDUCTANCE LEVEL (SCL) AS AN INDEX OF THE ACTIVITY O...ijbesjournal
This paper displays standardized measurements to examine the skin conductance level (SCL) as an index for the sympathetic nervous system’s activity considering a possible standardization of personal variability. SCL measurements were performed at baseline, Cold-Pressor-Tests and Stroop Tests for 15 subjects and inter- and intra-individual mean SCL values were examined. The logarithmic representation displays a high inter-individual variability, denoted by a high fluctuation range of the absolute values and SCL amplitudes. A standardization of inter-individuality could not be achieved by the applied methods (range correction and z-transformation). For the relative intra-individual comparison of the stress situation to the baseline, a method of correction for the determination of the real effect of sympathetic activation was established. EDA should be combined with other parameters of the ANS for a more precise evaluation of stress situations in the context of changes in blood pressure.
Feature Extraction Techniques and Classification Algorithms for EEG Signals t...Editor IJCATR
EEG (Electroencephalogram) signal is a neuro signal which is generated due the different electrical activities in the brain.
Different types of electrical activities correspond to different states of the brain. Every physical activity of a person is due to some
activity in the brain which in turn generates an electrical signal. These signals can be captured and processed to get the useful information
that can be used in early detection of some mental diseases. This paper focus on the usefulness of EGG signal in detecting the human
stress levels. It also includes the comparison of various preprocessing algorithms ( DCT and DWT.) and various classification algorithms
(LDA, Naive Bayes and ANN.). The paper proposes a system which will process the EEG signal and by applying the combination of
classifiers, will detect the human stress levels.
Emotions are an unstoppable and uncontrollable aspect of mental state of human. Some bad situations give
stress and leads to different sufferings. One can’t avoid situation but can have awareness when body feel
stress or any other emotion. It becomes easy for doctors whose patient is not in condition to speak. In that
case person’s physiological parameters are measured to decide emotional status. While experiencing
different emotion, there are also physiological changes taking place in the human body, like variations in
the heart rate (ECG/HRV), skin conductance (GSR), breathing rate(BR), blood volume pulse(BVP),brain
waves (EEG), temperature and muscle tension. These were some of the metrics to sense emotive coefficient.
This research paper objective is to design and develop a portable, cost effective and low power
embedded system that can predict different emotions by using Naïve Bayes classifiers which are based on
probability models that incorporate class conditional independence assumptions. Inputs to this system are
various physiological signals and are extracted by using different sensors. Portable microcontroller used
in this embedded system is MSP430F2013 to automatically monitor the level of stress in computer. This
paper reports on the hardware and software instrumentation development and signal processing approach
used to detect the stress level of a subject.To check the device's performance, few experiments were done in
which 20 adults (ten women and ten men) who completed different tests requiring a certain degree of effort,
such as showing facing intense interviews in office.
Mental Strain while Driving on a Driving-Simulator: Potential Effect on Centr...CSCJournals
We recorded magnetoencephalographic (MEG), autonomic nervous system (ANS) activities and behavioral data during normal driving conditions (ND) and during driving under time constraint (TCD) while drivers had to respect traffic lights in a simulated driving task. Electrodermal activity and heart rate were the dependent variables from the ANS. Cerebral regions of interest, reaction time (RT) and rate of traffic light violations were those from MEG and behavior, respectively. Under TCD conditions, scenarios were likely to elicit high strain. In these conditions, response selection was more complex when drivers should respect traffic law, thus eliciting longer RT with increased activation in the left dorso-lateral prefrontal cortex. Heart rate decrease preceding light change perception was larger under TCD suggesting that drivers focused their attention toward potential light changes before decision-making (i.e. respecting the traffic law or the requested scenario). We finally observed a negative correlation between ANS and left-brain activities. Consequences upon safety are then discussed.
A typical Realization of the process with linear recovery of AldosteroneIJERA Editor
Hypercortisolism as a sign of hypothamamus-pituitary-adrenocortical (HPA) axis overactivity and sleep EEG
changes are frequently observed in depression. Closely related to the
HPA axis is the renin-angiotensin-aldosterone system (RAAS) as 1. adrenocorticotropic hormone (ACTH) is a
common stimulus for cortisol and aldosterone, 2. cortisol release is suppressed by mineralocorticoid receptor
(MR) agonists 3. angiotensin II (ATII) releases CRH and vasopressin from the hypothalamus. The first passage
time and the bounds of the survival functions for the application are also obtained
POWER SPECTRAL ANALYSIS OF EEG AS A POTENTIAL MARKER IN THE DIAGNOSIS OF SPAS...ijbesjournal
The detection and diagnosis of various neurological disorders are performed using different medical
devices among which electroencephalogram (EEG) is one of the most cost effective technique. Though
significant progress had been made in the analysis of EEG for diagnosis of different neurological
disorders, yet detection of cerebral palsy (CP) is not quite clear. This study was performed to analyze the
EEG power spectrum density (PSD) of spastic CP and normal children to find if any significant EEG
patterns could be used for early detection of CP. Twenty children participated in this study out of which ten
were spastic CP and other ten were normal healthy children. EEG of all the participants was recorded
from C3 C4 and F3 F4 regions following montage 10-20 system. The artifact-free EEG signals of 15
minutes duration was extracted for spectral analysis using Fast Fourier Transformation (FFT) algorithm
in MATLAB and power density spectrum (PSD) was plotted. The PSD revealed high intensity power peak
at frequency of 50Hz and smaller at 100 Hz, which was consistent for all healthy subjects. In case of
spastic CP children, high intensity peak at 100Hz were prominent and smaller peak was observed at 50Hz.
The high intensity 100Hz peak observed in the PSD of spastic CP patients demonstrated that this tool can
be used for early detection of spastic CP.
Stress detection during job interview using physiological signalIJECEIAES
A job interview can be challenging and stressful even when one has gone through it many times. Failure to handle the stress may lead to unsuccessful delivery of their best throughout the interview session. Therefore, an alternative method which is preparing a video resume and interview before the actual interview could reduce the level of stress. An intelligent stress detection is proposed to classify individuals with different stress levels by understanding the physiological signal through electrocardiogram (ECG) signals. The Augsburg biosignal toolbox (AUBT) dataset was used to obtain the state-of-art results. Only five selected features are significant to the stress level were fed into neural network multi-layer perceptron (MLP) as the optimum classifier. This stress detection achieved an accuracy of 92.93% when tested over the video interview dataset of 10 male subjects who were recording the video resume for the analysis purposes.
MEDITATION: ITS TREMENDOUS IMPACT ON HEART RATE VARIABILITYcscpconf
The heart is connected through the nervous system directly to major organs and is able to sense
their need. The heart also responds to adrenaline in the blood flowing through it. With these
inputs the heart is able to adjust its rate to accommodate the needs of the whole body. By its
heartbeat, it is able to broadcast a common signal to every cell. One measure of heart health is
Heart Rate Variability (HRV). HRV is defined in terms of how different the lengths of time
between each heart beat is. The greater the difference in times between heart beats, the
healthier is the heart thought to be. Individuals may be able to learn to increase their own HRV
and become healthier by a daily meditation practice. This paper uses Heart Variability as the
base signal for studying the impact of meditation on it. The paper brings out the difference
between pre and post meditation conditions in terms qualitative measure of Power Spectral
Density (PSD) variations using Smoothed Pseudo Wigner Ville (SPWVD) distribution method.The simulations highlight the meditation effects overtime period in PSDs
Review:Wavelet transform based electroencephalogram methodsijtsrd
In this paper, EEG signals are the signatures of neural activities. There have been many algorithms developed so far for processing EEG signals. The analysis of brain waves plays an important role in diagnosis of different brain disorders. Brain is made up of billions of brain cells called neurons, which use electricity to communicate with each other. The combination of millions of neurons sending signals at once produces an enormous amount of electrical activity in the brain, which can be detected using sensitive medical equipment such as an EEG which measures electrical levels over areas of the scalp. The electroencephalogram (EEG) recording is a useful tool for studying the functional state of the brain and for diagnosing certain disorders. The combination of electrical activity of the brain is commonly called a Brainwave pattern because of its wave-like nature. EEG signals are low voltage signals that are contaminated by various types of noises that are also called as artifacts. Statistical method for removing artifacts from EEG recordings through wavelet transform without considering SNR calculation is proposed Miss. N. R. Patil | Prof. S. N. Patil"Review:Wavelet transform based electroencephalogram methods" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018, URL: http://www.ijtsrd.com/papers/ijtsrd11542.pdf http://www.ijtsrd.com/engineering/bio-mechanicaland-biomedical-engineering/11542/reviewwavelet-transform-based-electroencephalogram-methods/miss-n-r-patil
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Emotions are an unstoppable and uncontrollable aspect of mental state of human. Some bad situations give
stress and leads to different sufferings. One can’t avoid situation but can have awareness when body feel
stress or any other emotion. It becomes easy for doctors whose patient is not in condition to speak. In that
case person’s physiological parameters are measured to decide emotional status. While experiencing
different emotion, there are also physiological changes taking place in the human body, like variations in
the heart rate (ECG/HRV), skin conductance (GSR), breathing rate(BR), blood volume pulse(BVP),brain
waves (EEG), temperature and muscle tension. These were some of the metrics to sense emotive coefficient.
This research paper objective is to design and develop a portable, cost effective and low power
embedded system that can predict different emotions by using Naïve Bayes classifiers which are based on
probability models that incorporate class conditional independence assumptions. Inputs to this system are
various physiological signals and are extracted by using different sensors. Portable microcontroller used
in this embedded system is MSP430F2013 to automatically monitor the level of stress in computer. This
paper reports on the hardware and software instrumentation development and signal processing approach
used to detect the stress level of a subject.To check the device's performance, few experiments were done in
which 20 adults (ten women and ten men) who completed different tests requiring a certain degree of effort,
such as showing facing intense interviews in office.
Mental Strain while Driving on a Driving-Simulator: Potential Effect on Centr...CSCJournals
We recorded magnetoencephalographic (MEG), autonomic nervous system (ANS) activities and behavioral data during normal driving conditions (ND) and during driving under time constraint (TCD) while drivers had to respect traffic lights in a simulated driving task. Electrodermal activity and heart rate were the dependent variables from the ANS. Cerebral regions of interest, reaction time (RT) and rate of traffic light violations were those from MEG and behavior, respectively. Under TCD conditions, scenarios were likely to elicit high strain. In these conditions, response selection was more complex when drivers should respect traffic law, thus eliciting longer RT with increased activation in the left dorso-lateral prefrontal cortex. Heart rate decrease preceding light change perception was larger under TCD suggesting that drivers focused their attention toward potential light changes before decision-making (i.e. respecting the traffic law or the requested scenario). We finally observed a negative correlation between ANS and left-brain activities. Consequences upon safety are then discussed.
A typical Realization of the process with linear recovery of AldosteroneIJERA Editor
Hypercortisolism as a sign of hypothamamus-pituitary-adrenocortical (HPA) axis overactivity and sleep EEG
changes are frequently observed in depression. Closely related to the
HPA axis is the renin-angiotensin-aldosterone system (RAAS) as 1. adrenocorticotropic hormone (ACTH) is a
common stimulus for cortisol and aldosterone, 2. cortisol release is suppressed by mineralocorticoid receptor
(MR) agonists 3. angiotensin II (ATII) releases CRH and vasopressin from the hypothalamus. The first passage
time and the bounds of the survival functions for the application are also obtained
POWER SPECTRAL ANALYSIS OF EEG AS A POTENTIAL MARKER IN THE DIAGNOSIS OF SPAS...ijbesjournal
The detection and diagnosis of various neurological disorders are performed using different medical
devices among which electroencephalogram (EEG) is one of the most cost effective technique. Though
significant progress had been made in the analysis of EEG for diagnosis of different neurological
disorders, yet detection of cerebral palsy (CP) is not quite clear. This study was performed to analyze the
EEG power spectrum density (PSD) of spastic CP and normal children to find if any significant EEG
patterns could be used for early detection of CP. Twenty children participated in this study out of which ten
were spastic CP and other ten were normal healthy children. EEG of all the participants was recorded
from C3 C4 and F3 F4 regions following montage 10-20 system. The artifact-free EEG signals of 15
minutes duration was extracted for spectral analysis using Fast Fourier Transformation (FFT) algorithm
in MATLAB and power density spectrum (PSD) was plotted. The PSD revealed high intensity power peak
at frequency of 50Hz and smaller at 100 Hz, which was consistent for all healthy subjects. In case of
spastic CP children, high intensity peak at 100Hz were prominent and smaller peak was observed at 50Hz.
The high intensity 100Hz peak observed in the PSD of spastic CP patients demonstrated that this tool can
be used for early detection of spastic CP.
Stress detection during job interview using physiological signalIJECEIAES
A job interview can be challenging and stressful even when one has gone through it many times. Failure to handle the stress may lead to unsuccessful delivery of their best throughout the interview session. Therefore, an alternative method which is preparing a video resume and interview before the actual interview could reduce the level of stress. An intelligent stress detection is proposed to classify individuals with different stress levels by understanding the physiological signal through electrocardiogram (ECG) signals. The Augsburg biosignal toolbox (AUBT) dataset was used to obtain the state-of-art results. Only five selected features are significant to the stress level were fed into neural network multi-layer perceptron (MLP) as the optimum classifier. This stress detection achieved an accuracy of 92.93% when tested over the video interview dataset of 10 male subjects who were recording the video resume for the analysis purposes.
MEDITATION: ITS TREMENDOUS IMPACT ON HEART RATE VARIABILITYcscpconf
The heart is connected through the nervous system directly to major organs and is able to sense
their need. The heart also responds to adrenaline in the blood flowing through it. With these
inputs the heart is able to adjust its rate to accommodate the needs of the whole body. By its
heartbeat, it is able to broadcast a common signal to every cell. One measure of heart health is
Heart Rate Variability (HRV). HRV is defined in terms of how different the lengths of time
between each heart beat is. The greater the difference in times between heart beats, the
healthier is the heart thought to be. Individuals may be able to learn to increase their own HRV
and become healthier by a daily meditation practice. This paper uses Heart Variability as the
base signal for studying the impact of meditation on it. The paper brings out the difference
between pre and post meditation conditions in terms qualitative measure of Power Spectral
Density (PSD) variations using Smoothed Pseudo Wigner Ville (SPWVD) distribution method.The simulations highlight the meditation effects overtime period in PSDs
Review:Wavelet transform based electroencephalogram methodsijtsrd
In this paper, EEG signals are the signatures of neural activities. There have been many algorithms developed so far for processing EEG signals. The analysis of brain waves plays an important role in diagnosis of different brain disorders. Brain is made up of billions of brain cells called neurons, which use electricity to communicate with each other. The combination of millions of neurons sending signals at once produces an enormous amount of electrical activity in the brain, which can be detected using sensitive medical equipment such as an EEG which measures electrical levels over areas of the scalp. The electroencephalogram (EEG) recording is a useful tool for studying the functional state of the brain and for diagnosing certain disorders. The combination of electrical activity of the brain is commonly called a Brainwave pattern because of its wave-like nature. EEG signals are low voltage signals that are contaminated by various types of noises that are also called as artifacts. Statistical method for removing artifacts from EEG recordings through wavelet transform without considering SNR calculation is proposed Miss. N. R. Patil | Prof. S. N. Patil"Review:Wavelet transform based electroencephalogram methods" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018, URL: http://www.ijtsrd.com/papers/ijtsrd11542.pdf http://www.ijtsrd.com/engineering/bio-mechanicaland-biomedical-engineering/11542/reviewwavelet-transform-based-electroencephalogram-methods/miss-n-r-patil
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
How to Create Map Views in the Odoo 17 ERPCeline George
The map views are useful for providing a geographical representation of data. They allow users to visualize and analyze the data in a more intuitive manner.
How to Split Bills in the Odoo 17 POS ModuleCeline George
Bills have a main role in point of sale procedure. It will help to track sales, handling payments and giving receipts to customers. Bill splitting also has an important role in POS. For example, If some friends come together for dinner and if they want to divide the bill then it is possible by POS bill splitting. This slide will show how to split bills in odoo 17 POS.
The Indian economy is classified into different sectors to simplify the analysis and understanding of economic activities. For Class 10, it's essential to grasp the sectors of the Indian economy, understand their characteristics, and recognize their importance. This guide will provide detailed notes on the Sectors of the Indian Economy Class 10, using specific long-tail keywords to enhance comprehension.
For more information, visit-www.vavaclasses.com
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
3. A wide range of stress
Physical stress, mental stress, Job stress …
If we can evaluate stress precisely, we prevent
human errors.
4. EOG, EEG, ECG, GSR, RR… these are used to
evaluate stress in other laboratory.
EOG : electro oculogram
GSR : galvanic skin reflex
RR : respiration rate
5. Atsuo Murata, Hiroshima City University,
evaluate mental work load using wavelet
transform of EEG. [1]
The effect of mental stress on heart rate
variability and blood pressure during
computer work [2]
6. 12 single capital letters (A-L)
randomly selected at eight points on the
display
the identity of the letter and its position
varied randomly from trial to trail
Three levels of task
Low: compare one trial ago
Moderate: compare two trials ago
High: compare three trials ago
7.
8. [1] Atsuo Murata
“An Attempt to Evaluate Mental Workload Using
Wavelet Transform of EEG”, Human Factors, Fall 2005
[2] Nis Hjortskov, Dag Rissen, Anne Katrine Blangsted,
Nils Fallentin, Ulf Lundberg, Karen Sogaard
“The effect of mental stress on heart rate variability
and blood pressure during computer work”, Eur J
Appl Physiol (2004)
[3]Kenichi Takano, Kenji Yoshino, Akihiko Nagasaka
“Basic research on measurement of mental work load
utilizing physiological information”, Japanese journal
of industrial health 32(2) pp.105-117 19900320
