BRAIN-COMPUTER INTERFACE (BCI)

Slides:



Advertisements
Similar presentations
Presented By Qingwei Zhang Mu Li  To understand the definition and classification of brain-computer interaction  To explorer various non-invasive brain-
Advertisements

RESEARCHERS ARE DEVELOPING NEW METHODS OF TESTING THE OPERABILITY OF PROSTHETICS VIA THE BRAIN. Controlling a Computer With Thought.
Brain-computer interfaces: classifying imaginary movements and effects of tDCS Iulia Comşa MRes Computational Neuroscience and Cognitive Robotics Supervisors:
Controlling Assistive Machines in Paralysis Using Brain Waves and Other Biosignals HCC 741- Dr. Amy Hurst Wajanat Rayes.
Brain Computer Interface Presenter : Jaideo Chaudhari.
Brain Machine Interaction. Non-invasive BCIs Electroencephalography(EEG) - the neurophysiologic measurement of the electrical activity of the brain by.
Brain-Computer Interface - BrainGate Chip Hillary Grimes III Homework 6 COMP 4640.
The Brain is Embodied and the Body is Embedded in the Environment Jeff Krichmar Department of Cognitive Sciences University of California, Irvine.
A commonly used feature to discriminate between hand and foot movements is the variance of the EEG signal at certain electrodes. To this end, one calculates.
CSE 490i: Design in Neurobotics Yoky Matsuoka (instructor) Lecture: TTH 10:30-11:20 EEB 003 Labs: TTH 11:30-1:20 CSE 003E.
BRAIN-COMPUTER INTERFACES (BCI)
BCI Systems Brendan Allison, Ph.D. Institute for Automation University of Bremen 6 November, 2008.
Brain Chips Presented by Sumayya.S MCA B7.
Medical Informatics Basics
James Brooks BME 281 Presentation 1. What are BCI? Brain-computer interfaces are direct pathways of communication between the brain and some external.
By Omar Nada & Sina Firouzi. Introduction What is it A communication channel between brain and electronic device Computer to brain/Brain to computer Why.
Neural Decoding: Model and Algorithm for Evidence Accumulator Inference Thomas Desautels University College London Gatsby Computational Neuroscience Group.
Papavasileiou-1 CSE 5810 Brain Computer Interface in BMI Ioannis Papavasileiou Computer Science & Engineering Department The University of Connecticut.
Ch.1 Introduction to Brain-Computer Interfacing. Overview Fairytales: translating thoughts into actions without acting physically. Recent BCI technologies.
A Virtual Keyboard with Multi Modal Access for people with disabilities Vijit Prabhu 1, Girijesh Prasad 2 1 Computer Science & Engineering, Indian School.
August 19 th, 2006 Computational Neuroscience Group, LCE Helsinki University of Technology Computational neuroscience group Laboratory of computational.
Introduction to Computer and Programming CS-101 Lecture 6 By : Lecturer : Omer Salih Dawood Department of Computer Science College of Arts and Science.
Neuro-Prosthetic Project (Humanities) Norman, Mathew, Armando, Chris.
Brain-Computer Interface for VR control Christoph Guger.
Presenter : Jung-Ting Jin Adviser : Dr. Shih-Chung Chen Chairman : Dr. Hung-Chi Yang Date : December 31, 2014 BCI2000 : A General- Purpose Brain-Computer.
Human Brain the most complex living structure on the universe وَ فِیۡۤ اَنۡفُسِكُمْ اَفَلَا تُبْصِرُوۡنَ -- سُوۡرَۃُ الذّٰرِیٰتِ Dr. Abdel Ilah Alshbatat.
Shaun McGorry Executive Briefing July 16, Introduction: Robotics  Robots are becoming increasingly present in our daily lives  Robot: a virtual.
Improving People’s Lives.  Technology – is the use of science to solve problems and make people’s lives easier  Engineer – person who designs, constructs,
Beyond Gazing, Pointing, and Reaching A Survey of Developmental Robotics Authors: Max Lungarella, Giorgio Metta.
BRAINGATE NEURAL- INTERFACE SYSTEM BY
Shyamanta M. Hazarika, Adity Saikia, Simanta Bordoloi, Ujjal Sharma And Nayantara Kotoky Department Of Computer Sc. & Engineering, Tezpur University Tezpur,
Graz-Brain-Computer Interface: State of Research By Hyun Sang Suh.
Directeur : Mr S. PERREY (PR). Improving Usability in Human Computer Interfaces: an investigation into cognitive fatigue and its influence on the performance.
Virtual Reality in Brain- Computer Interface Research F. Lee 1, R. Scherer 2, H. Bischof 1, G. Pfurtscheller 2 1) Institute for Computer Graphics and Vision.
 A direct communication pathway between the brain and an external device.  Directed at assisting, augmenting, or repairing human cognitive or sensory-motor.
1 EEG-based Online Brain- Computer Interface System Chi-Ying Chen,Chang-Yu Tsai,Ya-Chun Tang Advisor:Yong-Sheng Chen.
The human brain: During the last decades a lot of research has been conducted, and many theories have been developed trying to unveil some of the secrets.
作者:Ali Bulent Usakli and Serkan Gurkan
Workshop on direct brain/computer interface & control Febo Cincotti Fondazione Santa Lucia IRCCS Brussels, August 2, 2006.
Brain Chips.
BrainGate Hardware Summer Bird Kacie Johnson Gitau Muchane Jonathan Wright Washington Farver.
Presentation by A.Sudheer kumar Dept of Information Technology 08501A1201.
Intelligent Systems Research Centre University of Ulster, Magee Campus BCI Research at the ISRC, University of Ulster N. Ireland, UK By Dr. Girijesh Prasad.
Adaptive Technology Thought-Controlled Wheelchairs By: Mary Nell Patterson.
ICT-enabled assistive systems based on non-invasive BCI Joseph Bremer European Commission, DG Information Society and Media E-Inclusion Unit (H3) BRAIN-COMPUTERINTERACTIONBRAIN-COMPUTERINTERACTION.
Brain Computer Interfaces...
BRAIN GATE TECHNOLOGY.. Brain gate is a brain implant system developed by the bio-tech company Cyberkinetics in 2003 in conjunction with the Department.
REU 2009 Computer Science and Engineering Department The University of Texas at Arlington Research Experiences for Undergraduates in Information Processing.
MIND CONTROLLED ROBOT BY ADITHYA KUMAR EIGHTH GRADE.
Presentation on BRAIN GATE Sree Vidyanikethan Engineering College A.Rangampeta, Tirupati. By P.Bhaskar (II MCA) M.Jayaprakash (II MCA)
B rain- C omputer I Luigi Bianchi Università di Roma “Tor Vergata” Luigi Bianchi Università di Roma “Tor Vergata”
Brain Chip Technology | Presented to- Dr. Jia Uddin, BRAC University 2 Dung Beetle, Can lift upto 1141 times of it’s own body weight..
introduction Brain driven car which would be of great help to the physically disabled people. These cars will rely only on what the individual is thinking.
Nformatics APPLICATION OF Q-EEG IN PEDIATRIC RESEARCH AND PRACTICE Gjoneska B.¹, Pop-Jordanova N.² and Markovska-Simoska S.¹ ¹ Macedonian Academy of Sciences.
SEMINAR on ‘BRAIN COMPUTER INTERFACE’ Submitted by: JYOTI DOSAYA
MANOJ KUMAR MEHER BME, 8 TH SEMESTER  INTRODUCTION  SCHEMATIC OF THE IRIS SYSTEM  PRINCIPLE & PRACTICE  LOCATION SPECIFICATION  SYSTEM.
NCP training day ICT 23- Interfaces for accessibility Juan Pelegrin "Youth, Skills and Inclusion" DG CONNECT European Commission Luxembourg.
Dr. Ervin Sejdić, Ph.D. Assistant Professor
Brain operated wheelchair
Sinhgad College of Engineering Department of Information Technology
Howell Istance Ambient Assisted Living Group
BRAINGATE SYSTEMS --Converts Thoughts into Actions
Figure 1 General framework of brain–computer interface (BCI) systems
Introduction Brain driven car which would be of great help to the physically disabled people. These cars will rely only on what the individual is thinking.
The Berlin Brain-Computer Interface: Machine Learning-Based Detection of User Specific Brain States Umar Farooq.
PSNA College of Engineering and Technology, Dindigul.
BCI Research at the ISRC, University of Ulster N. Ireland, UK
Brain-Computer Interfaces
BCI Review paper Sections 8 & 9
Overview of Computer system
Presentation transcript:

BRAIN-COMPUTER INTERFACE (BCI) Presentation by Raghuvarma Basavaraju 12/20/08 DCS860A

Agenda What is BCI? BCI Disciplines Why BCI? BCI paradigms Applications of BCI Current trends and Future directions References

What is a BCI? BCIs read electrical signals or other manifestations of brain activity and translate them into a digital form that computers can understand, process, and convert into actions of some kind, such as moving a cursor or turning on a TV. BCI can help people with inabilities to control computers, wheelchairs, televisions, or other devices with brain activity.

The 3 major components of BCIs [4] Ways of measuring neural signals from the human brain Methods and algorithms for decoding brain states/intentions from these signals and Methodology and algorithms for mapping the decoded brain activity to intended behavior or action.

Invasive versus Non-invasive BCI Invasive techniques, which implant electrodes directly onto a patient’s brain; Noninvasive techniques, in which medical scanning devices or sensors mounted on caps or headbands read brain signals.

BCI Disciplines [1] Nanotechnology Biotechnology Information technology Cognitive science Computer science Biomedical engineering Neuroscience Applied mathematics

Why BCI? [2] BCI is a new neuroscience paradigm that might help us better understand how the human brain works in terms of reorganization, learning, memory, attention, thinking, social interaction, motivation, interconnectivity, and much more. BCI research allows us to develop a new class of bioengineering control devices and robots to provide daily life assistance to handicapped and elderly people. Several potential applications of BCI hold promise for rehabilitation and improving performance, such as treating emotional disorders (for example, depression or anxiety), easing chronic pain, and overcoming movement disabilities due to stroke. BCI can expand possibilities for advanced human computer interfaces (HCIs), making them more natural, flexible, efficient, secure, and user-friendly by enhancing the interaction between the brain, the eyes, the body, and a robot or a computer.

BCI Paradigms [2] Passive endogenous: specific mental imagination activity— for example, motor imagery or mental arithmetic; active endogenous: active neurofeedback and unrestricted mental imagination using the operant-conditioning principle—a “no specifics” cognitive, “just do it” principle; passive exogenous: responses to externally driven stimuli to evoke specific brain responses called event-related potentials (ERPs); and active exogenous: consciously modified responses to external stimuli, often combined with neurofeedback.

Carleton University’s proposed BCI-based biometric system [1] Subjects use specific thoughts as passwords (called pass-thoughts).When someone tries to access a protected computer system or building, they think of their pass- thought.A headpiece with electrodes records the brain signals.The system extracts the signal’s features for computer processing,which includes identification of the feature subset that best and most consistently represents the pass-thought.The biometric system then compares the subset to those recorded for authorized users.

Current and future trends in noninvasive BCI [2] Unimodal to multimodal - that is, simultaneous monitoring of brain activity using several devices and combining BCI with multimodal HCIs; Simple signal-processing tools to more advanced machine learning and multidimensional data mining; Synchronous binary decision to multidegree control and asynchronous self-paced control; Open-loop to closed-loop control - neurofeedback combined with multimodal HCI; and Laboratory tests to practical trials in the noisy real world environment.

References Sixto Ortiz Jr., "Brain-Computer Interfaces: Where Human and Machine Meet," Computer, vol. 40, no. 1, pp. 17-21, Jan., 2007 Andrzej Cichocki, Yoshikazu Washizawa, Tomasz Rutkowski, Hovagim Bakardjian, Anh-Huy Phan, Seungjin Choi, Hyekyoung Lee, Qibin Zhao, Liqing Zhang, Yuanqing Li, "Noninvasive BCIs: Multiway Signal-Processing Array Decompositions," Computer, vol. 41, no. 10, pp. 34-42, Oct., 2008 Anton Nijholt, Desney Tan, Gert Pfurtscheller, Clemens Brunner, Jos del R. Mill, Brendan Allison, Bernhard Graimann, Florin Popescu, Benjamin Blankertz, Klaus-R. M?, "Brain-Computer Interfacing for Intelligent Systems," IEEE Intelligent Systems, vol. 23, no. 3, pp. 72-79, May/Jun, 2008 1. F. Babiloni, A. Cichocki, and S. Gao, eds., special issue, “Brain-Computer Interfaces: Towards Practical Implementations and Potential Applications,” ComputationalIntelligence and Neuroscience, 2007; P. Sajda, K-R. Mueller, and K.V. Shenoy, eds., special issue, “Brain Computer Interfaces,” IEEE Signal Processing Magazine,Jan. 2008.