This document discusses two main applications of EEG waves: diagnosis of sleep disorders and brain-computer interfaces (BCIs). For sleep disorder diagnosis, EEG signals are analyzed to stage sleep and identify abnormalities. Statistical methods classify sleep stages over time. BCIs translate brain signals into commands, using visual evoked potentials from stimuli flickering at different frequencies to identify intended commands. Key issues discussed include reducing electrode numbers and optimizing frequency feature extraction from EEG signals to improve BCI accuracy and usability.
An electrogastrogram (EGG) is a graphic produced by an electrogastrograph, which records the electrical signals that travel through the stomach muscles and control the muscles' contractions. An electrogastroenterogram (or gastroenterogram) is a similar procedure, which writes down electric signals not only from the stomach, but also from intestines.
An electrogastrogram (EGG) is a graphic produced by an electrogastrograph, which records the electrical signals that travel through the stomach muscles and control the muscles' contractions. An electrogastroenterogram (or gastroenterogram) is a similar procedure, which writes down electric signals not only from the stomach, but also from intestines.
This slide has been prepared in detaied manner and will help you.
The topics covered are:-
1- introduction
2.circuit diagram and its explaination
3.working
4. features
5.advantages / disadvantages
6. the top vendors
This ppt describes the various features, signal processing methods that are commonly applied like wavelet, HHT, FT etc. Hope it helps someone understand better. EEG During mental arithmetic task dataset is used.
Electroencephalography (eeg),electrical activity recorded via electrodes on the scalp,Neurophysiological Basis of EEG,Scalp EEG Recordings,Wearable EEG Devices,Recording EEG Signals,EEG Rhythms,
This lecture is all about the recognition of an abnormal EEG, its characteristics, its appearance and all about how to differentiate the abnormal activity with normal EEG background.
This slide has been prepared in detaied manner and will help you.
The topics covered are:-
1- introduction
2.circuit diagram and its explaination
3.working
4. features
5.advantages / disadvantages
6. the top vendors
This ppt describes the various features, signal processing methods that are commonly applied like wavelet, HHT, FT etc. Hope it helps someone understand better. EEG During mental arithmetic task dataset is used.
Electroencephalography (eeg),electrical activity recorded via electrodes on the scalp,Neurophysiological Basis of EEG,Scalp EEG Recordings,Wearable EEG Devices,Recording EEG Signals,EEG Rhythms,
This lecture is all about the recognition of an abnormal EEG, its characteristics, its appearance and all about how to differentiate the abnormal activity with normal EEG background.
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.
Amyotrophic Lateral Sclerosis (ALS) is the most common progressive neurodegenerative disorder reflecting
the degeneration of upper and lower motor neurons. Motor neurons controls the communication between nervous
system and muscles of the body. ALS results in the loss of voluntary control over muscular activities along with the
inability to breathe and the maximum life expectancy of affected individual will be 3-5 years from the onset of
symptoms. But the lifetime of affected people can be extended by early detection of disease. The usual methods for
diagnosis are Electromyography (EMG), Nerve Conduction Study (NCS), Magnetic Resonance Imaging (MRI) and
Magneto-encephalography (MEG). But some of these methods may erroneously result in neuropathy or myopathy
instead of ALS and some do not provide any biomarker. EEG is comparatively least expensive method and it
provides biomarker for ALS detection. ALS is always associated with fronto-temporal dementia (FTD). The spectral
analysis of EEG will reveal the structural and functional connectivity alterations of the underlying neural network
that occurs due to FTD and it can generate potential biomarkers for the early detection of ALS. A novel algorithm
has been developed by exploiting the Dual Tree Complex Wavelet Transform (DTCWT) technique and it can
overcome the short comes of existing methods for the analysis and feature extraction of EEG. Deterministic
biomarkers were obtained from spectral analysis of EEG and the proposed algorithm provided 100% accuracy for all
the test datasets.
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Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Vaccine management system project report documentation..pdfKamal Acharya
The Division of Vaccine and Immunization is facing increasing difficulty monitoring vaccines and other commodities distribution once they have been distributed from the national stores. With the introduction of new vaccines, more challenges have been anticipated with this additions posing serious threat to the already over strained vaccine supply chain system in Kenya.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Forklift Classes Overview by Intella PartsIntella Parts
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Courier management system project report.pdfKamal Acharya
It is now-a-days very important for the people to send or receive articles like imported furniture, electronic items, gifts, business goods and the like. People depend vastly on different transport systems which mostly use the manual way of receiving and delivering the articles. There is no way to track the articles till they are received and there is no way to let the customer know what happened in transit, once he booked some articles. In such a situation, we need a system which completely computerizes the cargo activities including time to time tracking of the articles sent. This need is fulfilled by Courier Management System software which is online software for the cargo management people that enables them to receive the goods from a source and send them to a required destination and track their status from time to time.
Democratizing Fuzzing at Scale by Abhishek Aryaabh.arya
Presented at NUS: Fuzzing and Software Security Summer School 2024
This keynote talks about the democratization of fuzzing at scale, highlighting the collaboration between open source communities, academia, and industry to advance the field of fuzzing. It delves into the history of fuzzing, the development of scalable fuzzing platforms, and the empowerment of community-driven research. The talk will further discuss recent advancements leveraging AI/ML and offer insights into the future evolution of the fuzzing landscape.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Event Management System Vb Net Project Report.pdfKamal Acharya
In present era, the scopes of information technology growing with a very fast .We do not see any are untouched from this industry. The scope of information technology has become wider includes: Business and industry. Household Business, Communication, Education, Entertainment, Science, Medicine, Engineering, Distance Learning, Weather Forecasting. Carrier Searching and so on.
My project named “Event Management System” is software that store and maintained all events coordinated in college. It also helpful to print related reports. My project will help to record the events coordinated by faculties with their Name, Event subject, date & details in an efficient & effective ways.
In my system we have to make a system by which a user can record all events coordinated by a particular faculty. In our proposed system some more featured are added which differs it from the existing system such as security.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
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An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
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Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
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3. INTRODUCTION
Electroencephalogram (EEG) is the recording of
electrical activity through electrode sensors placed on
the scalp. The electricity is recorded as waves that can
be classified as normal or abnormal.
Different types of normal waves can indicate various
states or activity levels. Abnormal waves can indicate
medical problems.
4. CLASSIFICATION OF APPLICATION
Two important applications of EEG wave :-
(1) Diagnosis of sleep disorders.
(2) Brain–Computer Interfaces.
5. DIAGNOSIS OF SLEEP DISORDERS
A typical sleep recording has multiple channels of
EEG waves coming from the electrodes placed on the
subject’s head. Sample sleep recordings are shown in
Figure 1. In the left panel, the waves from a healthy
subject are stable at about zero and show relatively
high variability and low correlation. In the right panel,
the waves from a person with sleep difficulty show
less variability and higher correlation.
6. EEG signals from a healthy person and a person
with sleep difficulty
7. Sleep staging:- Sleep staging is the pattern recognition
task of classifying the recordings into sleep stages
continuously over time; the task is performed by a sleep
stager. The stages include rapid-eye movement (REM)
sleep, four levels of non-REM sleep, and being awake.
Sleep staging is crucial for the diagnosis and treatment of
sleep disorders.
Statistical Analysis of Sleep EEG Data:- statistical
methods for performing sleep staging are auto regression,
Kullback-Leibler divergence-based nearest-neighbor
classification, and statistical modeling using a hidden
Markov model (HMM).
8. Logarithmic power spectral density of EEG
signals from a healthy person and a person with
sleep difficulty
10. BRAIN COMPUTER INTERFACES
BCIs translate human intentions into control signals to
establish a direct communication channel between the
human brain and output devices.
Visual Evoked Potentials VEPs reflect the visual
information-processing mechanism in the brain.
VEPs corresponding to low stimulus rates are
categorized as transient VEP (TVEP), and those
corresponding to rapidly repetitive stimulations are
categorized as steady-state VEP (SSVEP)
11. A TVEP is a true transient response to a stimulus when
the relevant brain mechanisms are in resting states. It
does not depend on any previous trial. If the visual
stimulation is repeated with intervals shorter than the
duration of a TVEP, the responses evoked by each
stimulus will overlap each other, and an SSVEP is
generated.
Analysis of the TVEP is based on temporal methods
such as template matching, whereas SSVEP detection
is usually performed by frequency analysis, e.g., power
spectral density (PSD) estimation.
12. SSVEP System Based on Frequency Feature
Frequency coding and PSD analysis is the method
employed by most SSVEP-based BCI systems.
Figure 1 shows its basic diagram. Facing a number
of visual spots flickering at different frequencies,
the subject gazes at one of them, generating an
SSVEP with specific frequency components.
Figure 1(c) is the amplitude spectrum of the
SSVEP evoked by the visual spot flickering at 7
Hz. Spectrum peaks appear at 7 Hz, 14 Hz (second
harmonic), and 21 Hz (third harmonic). When the
peaks are detected, the flickering spot the subject is
watching can be identified, and the corresponding
command can then be executed.
13.
14. The SSVEP BCI based on frequency coding seems
to be rather simple in principle, but a number of
problems (such as selection of electrodes and
stimulating frequencies, algorithm of feature
extraction, and threshold setting) have to be solved
during its implementation. Among them, lead
position selection and frequency feature extraction
are the most important
15. Lead Position :-To get SSVEPs with a high SNR
using the least number of electrodes is the goal of lead
selection. Only one bipolar lead is chosen as the input
in our system. From physiological knowledge, VEP
can be recorded with maximum amplitude at the
occipital region. So, the electrode giving the strongest
SSVEP, which is generally located in the occipital
region, is selected as the signal channel.
16. The location of the reference channel is searched under
the following considerations: the amplitude of the
SSVEP in it should be lower, and its position should
lie in the vicinity of the signal channel so that the noise
component in it is similar to that in the signal channel.
A high SNR can then be gained when the potentials of
the two electrodes are subtracted
• Frequency Feature:- Because of the nonlinearity
during information transfer in visual system, strong
harmonics may often be found in the SSVEPs.
17. CRITICAL ISSUES
Reducing the number of electrodes in BCI systems is a
critical issue for the successful development of
clinical applications of BCI technology.
Size of epoch (a time window of fixed length of the
raw EEG data)
18. REFERENCES
Medical Applications of EEG Wave Classification By
Wanli Min and Gang Luo.
Brain Computer Interfaces Based on Visual Evoked
Potentials By Yijun Wang, xiaorong Gao, bo Hong,
Chuan Jia and Shangkai Gao.