The poster was created for two major student research activities at Kennesaw State University named (i) Symposium of Student Scholars and (ii) C-Day where I have introduced one of my research projects virtually.
The poster Can be found here: https://digitalcommons.kennesaw.edu/cgi/viewcontent.cgi?article=1066&context=cday
Computational Neuroscience - The Brain - Computer Science InterfaceChristopher Currin
Understanding intelligence is one of the most challenging scientific problems faced by humanity.
This talk will provide an introduction to the multi-disciplinary field of Computational Neuroscience: the questions it seeks to answer and some of the (mathematical & computational) techniques used to investigate how we fundamentally think.
Currently doing his Computational Neuroscience PhD at the University of Cape Town, Chris has a wonderfully weird background in machine learning, neuroscience, and psychology. He is fascinated by how we think and learn, sometimes to a fault, and how this works in both biological and artificial intelligence.
Computational Neuroscience - The Brain - Computer Science InterfaceChristopher Currin
Understanding intelligence is one of the most challenging scientific problems faced by humanity.
This talk will provide an introduction to the multi-disciplinary field of Computational Neuroscience: the questions it seeks to answer and some of the (mathematical & computational) techniques used to investigate how we fundamentally think.
Currently doing his Computational Neuroscience PhD at the University of Cape Town, Chris has a wonderfully weird background in machine learning, neuroscience, and psychology. He is fascinated by how we think and learn, sometimes to a fault, and how this works in both biological and artificial intelligence.
Brain computer interface based smart keyboard using neurosky mindwave headsetTELKOMNIKA JOURNAL
In the last decade, numerous researches in the field of electro-encephalo-graphy (EEG) and brain-computer-interface (BCI) have been accomplished. BCI has been developed to aid disabled/partially disabled people to efficiently communicate with the community. This paper presents a control tool using the Neurosky Mindwave headset, which detects brainwaves (voluntary blinks and attention) to form a brain-computer interface (BCI) by receiving the system signals from the frontal lobe. This paper proposed an alternative computer input device for those disabled people (who are physically challenged) rather than the conventional one. The work suggested to use two virtual keyboard designs. The conducted experiment revealed a significant result in developing user printing skills on PCs. Encouraging results (1.55-1.8 word per minute (WPM)) were obtained in this research in comparison to other studies.
Brain Computer Interfacing using Electroencephalography and Convolutional Neu...ijtsrd
A brain computer interface BCI is a communication system that interprets brain activity into commands for a computer or other devices .This technology is the emphasis of a rapidly growing research and development initiative that is greatly exciting experts, and the public in general. Today, humans can use the electrical signals from brain activity to interrelate with, influence, or change their surroundings. The evolving field of BCI technology may allow persons in capable of speaking and or use their limbs to yet again interconnect or operate assistive devices for walking and functional objects. In other words, a BCI permits users to act on their environment by using only brain activity, without using outlying nerves and muscles. In this paper we give an overview to some of the aspects of BCI research mentioned above, present a tangible example of a BCI system, and highlight recent progresses and open complications. Ms. Dhiviyaa S | Ms. Sri Priyanka J | Ms. Meghala S "Brain Computer Interfacing using Electroencephalography and Convolutional Neural Networks" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-3 , April 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30174.pdf Paper Url :https://www.ijtsrd.com/other-scientific-research-area/other/30174/brain-computer-interfacing-using-electroencephalography-and-convolutional-neural-networks/ms-dhiviyaa-s
BayCHI April 2015 - Towards Smart Emotional Neuro Search Engines: An Extensio...Nilo Sarraf
In an era when humans are creating brain-controlled airplanes, neurogaming, and robots that learn behavior by reading human emotions, we may soon enable search engines to read human emotions in order to improve search results based on the neurological feedback they receive from brain waves.
Through wearable computing devices, search engines might read brain waves and dimensions of emotions in order to improve search results. In other words, search engines can become an extension of the human brain.
As the power of modern computers grows alongside our understanding of the human brain, we move ever closer to making some pretty spectacular science fiction into reality. Imagine transmitting signals directly to someone's brain that would allow them to see, hear or feel specific sensory inputs. Consider the potential to manipulate computers or machinery with nothing more than a thought. It isn't about convenience, for severely disabled people, development of a brain-computer interface (BCI) could be the most important technological breakthrough in decades.
A Brain-computer interface, sometimes called a direct neural interface or a brain-machine interface, is a direct communication pathway between a brain and an external device. It is the ultimate in development of human-computer interfaces or HCI. BCIs being the recent development in HCI there are many realms to be explored. After experimentation three types of BCIs have been developed namely Invasive BCIs, Partially-invasive BCIs, Non-invasive BCIs.
Principle of soft computing.
Soft computing.
Goals of soft computing.
Problem solving techniques.
Hard computing v/s soft computing.
Techniques in soft computing.
Advantages of soft computing.
Applications of soft computing.
Brain computer interface based smart keyboard using neurosky mindwave headsetTELKOMNIKA JOURNAL
In the last decade, numerous researches in the field of electro-encephalo-graphy (EEG) and brain-computer-interface (BCI) have been accomplished. BCI has been developed to aid disabled/partially disabled people to efficiently communicate with the community. This paper presents a control tool using the Neurosky Mindwave headset, which detects brainwaves (voluntary blinks and attention) to form a brain-computer interface (BCI) by receiving the system signals from the frontal lobe. This paper proposed an alternative computer input device for those disabled people (who are physically challenged) rather than the conventional one. The work suggested to use two virtual keyboard designs. The conducted experiment revealed a significant result in developing user printing skills on PCs. Encouraging results (1.55-1.8 word per minute (WPM)) were obtained in this research in comparison to other studies.
Brain Computer Interfacing using Electroencephalography and Convolutional Neu...ijtsrd
A brain computer interface BCI is a communication system that interprets brain activity into commands for a computer or other devices .This technology is the emphasis of a rapidly growing research and development initiative that is greatly exciting experts, and the public in general. Today, humans can use the electrical signals from brain activity to interrelate with, influence, or change their surroundings. The evolving field of BCI technology may allow persons in capable of speaking and or use their limbs to yet again interconnect or operate assistive devices for walking and functional objects. In other words, a BCI permits users to act on their environment by using only brain activity, without using outlying nerves and muscles. In this paper we give an overview to some of the aspects of BCI research mentioned above, present a tangible example of a BCI system, and highlight recent progresses and open complications. Ms. Dhiviyaa S | Ms. Sri Priyanka J | Ms. Meghala S "Brain Computer Interfacing using Electroencephalography and Convolutional Neural Networks" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-3 , April 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30174.pdf Paper Url :https://www.ijtsrd.com/other-scientific-research-area/other/30174/brain-computer-interfacing-using-electroencephalography-and-convolutional-neural-networks/ms-dhiviyaa-s
BayCHI April 2015 - Towards Smart Emotional Neuro Search Engines: An Extensio...Nilo Sarraf
In an era when humans are creating brain-controlled airplanes, neurogaming, and robots that learn behavior by reading human emotions, we may soon enable search engines to read human emotions in order to improve search results based on the neurological feedback they receive from brain waves.
Through wearable computing devices, search engines might read brain waves and dimensions of emotions in order to improve search results. In other words, search engines can become an extension of the human brain.
As the power of modern computers grows alongside our understanding of the human brain, we move ever closer to making some pretty spectacular science fiction into reality. Imagine transmitting signals directly to someone's brain that would allow them to see, hear or feel specific sensory inputs. Consider the potential to manipulate computers or machinery with nothing more than a thought. It isn't about convenience, for severely disabled people, development of a brain-computer interface (BCI) could be the most important technological breakthrough in decades.
A Brain-computer interface, sometimes called a direct neural interface or a brain-machine interface, is a direct communication pathway between a brain and an external device. It is the ultimate in development of human-computer interfaces or HCI. BCIs being the recent development in HCI there are many realms to be explored. After experimentation three types of BCIs have been developed namely Invasive BCIs, Partially-invasive BCIs, Non-invasive BCIs.
Principle of soft computing.
Soft computing.
Goals of soft computing.
Problem solving techniques.
Hard computing v/s soft computing.
Techniques in soft computing.
Advantages of soft computing.
Applications of soft computing.
This presentation is given in (2015) . As the power of modern computers grows alongside our understanding of the human brain, we move ever closer to making some pretty spectacular science fiction into reality.
Current trends in cognitive science and brain computing research 18th june 2020Dr G R Sinha
Medical Image Processing is study of acquisition, processing and analysis of various types of medical image modalities. Biomedical Imaging is one such modalities that mainly includes EEG, EMG, fMRI, MEG signals and their analysis for numerous applications such as diagnosis of mental disorder, sleep analysis, cognitive ability, study of memory and attention. Cognitive Science Research exploits biomedical modalities related to human brain and make use of the images in decoding brain commands and understanding them. This is very important in brain computer interface (BCI) and assessment of cognitive abilities. The abilities of human brain with the help of EEG signals can be described, decoded and used in performing desired tasks in numerous applications like robotics, driverless cars etc. EEG records brain activities especially electrical activities which are actually due to psychological, physiological and other changes in human brain. This lecture highlights an overview of cognitive science and brain computing research with its challenges and opportunities.
Brain Computer Interface (BCI) aims at providing an alternate means of communication and control to people with severe cognitive or sensory-motor disabilities. These systems are based on the single trial recognition of different mental states or tasks from the brain activity. This paper discusses the major components involved in developing a Brain Computer Interface system which includes the modality to obtain brain signals and its related processing methods.
Brain Computer Interface Next Generation of Human Computer InteractionSaurabh Giratkar
In the area of HCI research the main focus is on defining new ways of human interaction with computer system. With the passes of time a number of inventions have been made in this field. In initial days we used only keyboards to access our computer system (e.g. in Unix Terminal). In Second phase, after invention of mouse and other pointing devices, we started using graphical user interface using pointing devices like mouse which make the use of computer more easy and comfortable. Nowadays we are using pressure-driven mechanism, i.e. touch screen, which is common at ATMs, Mobile phones and PDAs etc. Although it is not as common in daily works but the release of tablet PCs and its popularity shows that the day is not much far when we wouldn’t be having keyboards and mouse at all.
All of these inventions have been made for balancing the requirements of society and user. E.g. Games, Multimedia Applications etc are not possible using only-Keyboard so we need mouse driven system for such applications, similarly we cannot have large keyboard on mobile so we need a touch screen system for mobiles. In addition to these traditional HCI models, there are some more advance HCI technology too for adding more flexibility and hence making the product more useful. E.g. swap card system at office doors for attendance and ATM-swap card for shopping. Speech processing systems are also there where we can access our computer system using our speech. Fig 1 shows most popular traditional HCI system.
This word file consists of a detailed introduction to the brain computer interface technology which is still a sophisticated technology. You can find its PPT under the heading "Brain Computer Interface PPT".
Brain, Body, and Bytes CHI 2010 Workshop PresentationsLennart Nacke
Brain and Body Interfaces (BBI) were discussed in this workshop. Its goal was to provide a platform for creating synergies between two related and emerging HCI disciplines (PC and BCI). Find out more at the workshop website: http://www.eecs.tufts.edu/~agirou01/workshop/
Powerpoint presentation on Brain Computer Interface (BCI), giving a brief introduction of the technology and then giving an overview of its working and its applications.
Each slide has notes added to it to help describe what the slide is about.
NeuroWeb Roadmap: Results of Foresight & Call for ActionPavel Luksha
Next 10 to 20 years will witness the coming of NeuroWeb – the next stage of communicational technologies, Internet 4.0 that involves our bodies and minds into the totality of communication by applying brain-computer and brain-brain interfaces supported by artificial intelligence & semantic technologies. Key technologies that precede NeuroWeb will be available before or around 2020.This presentation defines elements of the future architecture and promotes an international action
Augmenting Speech-Language Rehabilitation with Brain Computer Interfaces: An ...HCI Lab
Presentation on Aug 7, 2015 in the 17th International Conference on Human-Computer Interaction #HCII2015 in Los Angeles, CA, USA. The paper was presented in the Universal Access in Human-Computer Interaction track in the "Novel technologies for speech, language, attention and child development" session which was chaired by Prof. Margherita Antona, Foundation for Research & Technology - Hellas (FORTH), Greece http://2015.hci.international/friday
In this document, we will provide a detailed introduction to the purpose of this document. We will extend by providing a comprehensive evaluation report on the Wellstar web application, introducing innovative solutions, and proposing futuristic, state-of-art technology for Electronic Health Records (EHR).
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!
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
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.
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
We all have good and bad thoughts from time to time and situation to situation. We are bombarded daily with spiraling thoughts(both negative and positive) creating all-consuming feel , making us difficult to manage with associated suffering. Good thoughts are like our Mob Signal (Positive thought) amidst noise(negative thought) in the atmosphere. Negative thoughts like noise outweigh positive thoughts. These thoughts often create unwanted confusion, trouble, stress and frustration in our mind as well as chaos in our physical world. Negative thoughts are also known as “distorted thinking”.
Chapter 3 - Islamic Banking Products and Services.pptx
Poster Presentation: An Investigation on Non-Invasive Brain-Computer Interfaces: Emotiv Epoc+ Neuroheadset and Its Effectiveness
1. An Investigation on Non-Invasive Brain-Computer Interfaces:
Emotiv Epoc+ Neuroheadset and Its Effectiveness
Md Jobair Hossain Faruk
Faculty Mentor: Professors Maria Valero and Hossain Shahriar
INTRODUCTION
▪ Neurotechnology focuses on nervous system
with goals to directly “wire up” human brains
to machines.
▪ Brain-Computer Interfaces (BCI) is one of the
forefronts of many neurotechnological
discoveries.
▪ BCI research was introduced in the 1970s and
primary attempts are to decoding human speech
from brain signals, implementing creativity by
imagination, and controlling neuro-
psychological patterns.
▪ BCI utilizes billion of neural activities that
would significantly benefit people suffering
from neurological disorders.
STUDY OBJECTIVES
▪ Study the progress of BCI research and
Illustrate scores of unveiled contemporary
approaches.
▪ Investigate the mind machine-based Epoc+
neuroheadset in identifying emotional
parameters among human subjects and
effectiveness of neurotechnological research.
MATERIALS AND METHODS
▪ Three non-KSU human subjects for Epoc+
neuroheadset experiments focus on emotional
parameters.
▪ Naïve Bayes and Linear Regression classifiers
are applied to identify, and Kappa metric
optimizes the accuracy of the performance
metrics.
▪ Comparative study between Experimental,
External, and Survey Data.
RESULTS
▪ 69% and 62% improved accuracy for the
Naïve Bayes and Linear Regression
classifiers, respectively in reading the
performance matrices of the participants.
▪ A comparative representation between the
subjects and their survey report on
performance metrics draw a parallel
implication.
CONCLUSIONS
▪ Current Essence: We envision that non-
invasive, insertable, and low-cost BCI
approaches shall be the focal point for not
only an alternative for patients with physical
paralysis but also brain understanding that
would pave us to access and control the
memories and brain somewhere very near.
▪ Future Direction: We aim to continue our
effort explicitly towards significant
accomplishments around the domain of BCIs;
following the vision 2050 when BCI could
become a magic wand for developing men
control objects with the mind.
REFERENCE CITED
[1] H. Jobair, M. Valero, H. Shahriar. “An
Investigation on Non-Invasive Brain Computer
Interfaces: Emotiv Epoc+ Neuroheadset and Its
Effectiveness”. To appear in IEEE COMPSAC
2021, Full paper.
Literature Review
August 2020
Study Timeline
Internal Experiments
November 2020
Data Classifying
December 2020
Result Presentation
February 2021
FINDINGS
DATASETS
▪ External Datasets from Emotiv,
consist of about 2,170 events
(Emotional Parameters).
▪ Experimental Datasets (from 3
different subjects) consist of
6,086 events.
▪ Datasets from the Preliminary
Survey.
DISCUSSION
▪ The BCI’s approaches, both
Neuralink and FLR revealed their
progressional promises in BCIs
research towards a technological
wonderland.
▪ Experimental findings appear a
promising research tool around
the field of neurotechnology.
Naïve Bayes
Initial
Accuracy
Improved
Accuracy
N=1,242
57% 69% Training: 70%
32% (Kappa) 41% (Kappa) Testing: 30%
Linear Regression
Initial/Improv
ed Accuracy
Standard
Error/t-Stat
N=1,242
45% 15% Training: 70%
62% 12% Testing: 30%
ACKNOWLEDGEMENT
Fig. 1: Represents the contact quality of Epoc+ Neuroheadset (left) and illustrate the probability chart of performance
metrics (right)
Fig. 2: Graphical illustration of performance metrics using EEG dataset
Fig. 3: Analogy Between Naïve Bayes And Linear Regression Using Confusion Matrix
![An Investigation on Non-Invasive Brain-Computer Interfaces:
Emotiv Epoc+ Neuroheadset and Its Effectiveness
Md Jobair Hossain Faruk
Faculty Mentor: Professors Maria Valero and Hossain Shahriar
INTRODUCTION
▪ Neurotechnology focuses on nervous system
with goals to directly “wire up” human brains
to machines.
▪ Brain-Computer Interfaces (BCI) is one of the
forefronts of many neurotechnological
discoveries.
▪ BCI research was introduced in the 1970s and
primary attempts are to decoding human speech
from brain signals, implementing creativity by
imagination, and controlling neuro-
psychological patterns.
▪ BCI utilizes billion of neural activities that
would significantly benefit people suffering
from neurological disorders.
STUDY OBJECTIVES
▪ Study the progress of BCI research and
Illustrate scores of unveiled contemporary
approaches.
▪ Investigate the mind machine-based Epoc+
neuroheadset in identifying emotional
parameters among human subjects and
effectiveness of neurotechnological research.
MATERIALS AND METHODS
▪ Three non-KSU human subjects for Epoc+
neuroheadset experiments focus on emotional
parameters.
▪ Naïve Bayes and Linear Regression classifiers
are applied to identify, and Kappa metric
optimizes the accuracy of the performance
metrics.
▪ Comparative study between Experimental,
External, and Survey Data.
RESULTS
▪ 69% and 62% improved accuracy for the
Naïve Bayes and Linear Regression
classifiers, respectively in reading the
performance matrices of the participants.
▪ A comparative representation between the
subjects and their survey report on
performance metrics draw a parallel
implication.
CONCLUSIONS
▪ Current Essence: We envision that non-
invasive, insertable, and low-cost BCI
approaches shall be the focal point for not
only an alternative for patients with physical
paralysis but also brain understanding that
would pave us to access and control the
memories and brain somewhere very near.
▪ Future Direction: We aim to continue our
effort explicitly towards significant
accomplishments around the domain of BCIs;
following the vision 2050 when BCI could
become a magic wand for developing men
control objects with the mind.
REFERENCE CITED
[1] H. Jobair, M. Valero, H. Shahriar. “An
Investigation on Non-Invasive Brain Computer
Interfaces: Emotiv Epoc+ Neuroheadset and Its
Effectiveness”. To appear in IEEE COMPSAC
2021, Full paper.
Literature Review
August 2020
Study Timeline
Internal Experiments
November 2020
Data Classifying
December 2020
Result Presentation
February 2021
FINDINGS
DATASETS
▪ External Datasets from Emotiv,
consist of about 2,170 events
(Emotional Parameters).
▪ Experimental Datasets (from 3
different subjects) consist of
6,086 events.
▪ Datasets from the Preliminary
Survey.
DISCUSSION
▪ The BCI’s approaches, both
Neuralink and FLR revealed their
progressional promises in BCIs
research towards a technological
wonderland.
▪ Experimental findings appear a
promising research tool around
the field of neurotechnology.
Naïve Bayes
Initial
Accuracy
Improved
Accuracy
N=1,242
57% 69% Training: 70%
32% (Kappa) 41% (Kappa) Testing: 30%
Linear Regression
Initial/Improv
ed Accuracy
Standard
Error/t-Stat
N=1,242
45% 15% Training: 70%
62% 12% Testing: 30%
ACKNOWLEDGEMENT
Fig. 1: Represents the contact quality of Epoc+ Neuroheadset (left) and illustrate the probability chart of performance
metrics (right)
Fig. 2: Graphical illustration of performance metrics using EEG dataset
Fig. 3: Analogy Between Naïve Bayes And Linear Regression Using Confusion Matrix](https://image.slidesharecdn.com/jobairsposterforsymposiumspring21-210502051713/85/Poster-Presentation-An-Investigation-on-Non-Invasive-Brain-Computer-Interfaces-Emotiv-Epoc-Neuroheadset-and-Its-Effectiveness-1-320.jpg)
