Non-Invasive BCI.

Slides:



Advertisements
Similar presentations
Introduction to Neural Networks
Advertisements

Thought Translation Device
Nick Gomes BRAIN CONTROL INTERFACE (BCI) Richard Canton first discovers electrical signals on the surface of animal brains 1940s - Wilder Penfield.
IntroductionMethods Participants  7 adults with severe motor impairment.  9 adults with no motor impairment.  Each participant was asked to utilize.
Brain-computer interfaces: classifying imaginary movements and effects of tDCS Iulia Comşa MRes Computational Neuroscience and Cognitive Robotics Supervisors:
Brain-Computer Interfaces for Communication in Paralysis: A Clinical Experimental Approach By Adil Mehmood Khan.
GROUP 7 THOMAS BLASCHAK JOSHUA DAVIS ANTHONY HOMCHENKO CHARLES HUPP NANABAYIN WILSON SMART WHEELCHAIR.
The Scientific Method  What parts of the reflex experiment make up the scientific method?
Billy Vermillion. EEG  Electroencephalography A test to measure the electrical activity of the brain. ○ Brain cells communicate by producing tiny electrical.
Lunch Talk on Brain-Computer Interfacing Artificial Intelligence, University of Groningen Pieter Laurens Baljon December 14, :30-13:00.
Brain Computer Interface Presenter : Jaideo Chaudhari.
Brain-Computer Interface - BrainGate Chip Hillary Grimes III Homework 6 COMP 4640.
Biofeedback in Virtual Reality applications and Gaming Bonie Rosario, Jr. Sebastian Osorio Tom Iancovici University of Massachusetts Lowell Intro to Biosensors.
Brain-Computer Natural-Language Interface ● What is it? An interface between the brain and a computer that enables natural language communication within.
BCI Systems Brendan Allison, Ph.D. Institute for Automation University of Bremen 6 November, 2008.
COMSATS Institute of Information Technology,Sahiwal.
Brain Computer Interfaces
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.
NeuroPhone : Brain-Mobile Phone Interface using a wireless EEG Headset Ilho nam.
Engineering the Brain KAIST 바이오및뇌공학과 정재승. Ardipithecus.
Brain-Computer Interfaces for Communication in Paralysis: A Clinical Experimental Approach By Adil Mehmood Khan.
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.
Brain-Computer-Interface for Stress Detection Hassan Farooq, Ilona Wong Supervisor: Steve Mann Administrator: Cristiana Amza Section 8 Collecting Brainwave.
BRAINGATE NEURAL- INTERFACE SYSTEM BY
By Brett Kotowski BME Section 2 Presentation 1.  Neurotechnology  Neurotechnology is the use of engineering applications to scan, alter or enhance the.
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.
Meet Patel and Auriana Semans AP Biology
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.
What is Neural Engineering Tae-Seong Kim, Ph.D.. Neural Engineering Neural engineering also known as Ne uroengineering is a discipline that uses engineering.
Valerie Fortin BME 181 Spring 2013 Controlling Prosthetic Devices.
Gary O’ Donoghue Electronic & Computer Engineering, National University of Ireland, Galway Final Year Project A small number of consumer electronics.
1 EEG-based Online Brain- Computer Interface System Chi-Ying Chen,Chang-Yu Tsai,Ya-Chun Tang Advisor:Yong-Sheng Chen.
EEG-Based Communication and Control: Short-Term Role Feedback Present by: Yu Yuan-Chu Dennis J. Mcfarland, Lynn M. McCane, and J. R. Wolpaw.
Electromyography (EMG)
作者:Ali Bulent Usakli and Serkan Gurkan
 Carry impulses from the Central Nervous System to perform muscle movement  Motor Neurons are known as the control muscle  They directly or indirectly.
PSYCHOLOGY - MR. DUEZ Unit 2 - Biological Bases of Behavior Neuroscience: Neural Communication.
Group D: Malkesh Agheda and Belinda Stiles
Brain/Computer Interfacing James Wilson COMP /28/07.
Six seconds of data, recorded 5 minutes apart. Electroencephalography First recording of electrical fields of animals, Caton (1875); humans, Berger.
BrainGate Hardware Summer Bird Kacie Johnson Gitau Muchane Jonathan Wright Washington Farver.
BRAIN COMPUTER INTERFACE FOR TREATMENT OF NEUROLOGICAL DISORDERS Introduction to Neurological Disorders Treatment of ADHD Using BCI Ethical Complications.
Good Morning! Today We Will be Discussing Fantastic Information!
Presentation by A.Sudheer kumar Dept of Information Technology 08501A1201.
Adaptive Technology Thought-Controlled Wheelchairs By: Mary Nell Patterson.
Roberto Sironi | Paolo Perego | Riccardo Lavezzari | Giuseppe Andreoni Study of integrated neuro-motor rehabilitation system based on User Centered Design.
BRAIN GATE TECHNOLOGY.. Brain gate is a brain implant system developed by the bio-tech company Cyberkinetics in 2003 in conjunction with the Department.
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)
1 Psychology 304: Brain and Behaviour Lecture 4. 2 Research Methods and The Structure of the Nervous System 2. What are the primary divisions of the nervous.
B rain- C omputer I Luigi Bianchi Università di Roma “Tor Vergata” Luigi Bianchi Università di Roma “Tor Vergata”
Brain-Computer Interfaces
The State of the Art in Biofeedback and Neurofeedback: Where do we stand? Thomas F. Collura, Ph.D. October 16, 2010 Michigan Society for Behavioral Medicine.
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.
12. General Clinical Issues Relevant to Brain-Computer Interfaces YOON, HEENAM.
SEMINAR on ‘BRAIN COMPUTER INTERFACE’ Submitted by: JYOTI DOSAYA
Brain Computer Interface. Outlines What is BCI? How does it work? Brain Wave Control Simple introduction of the brain Data Acquisition Apps Drawbacks.
SIE 515 Brain-Computer Interfaces (BCI) and Sensory Substitution
Brain operated wheelchair
The Thought Translation device
Jakub Berčík – Jana Rybanská
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.
Brain Computer Interface
The Berlin Brain-Computer Interface: Machine Learning-Based Detection of User Specific Brain States Umar Farooq.
Brain-Computer Interfaces
Presentation transcript:

Non-Invasive BCI

1929 Hans Berger – Discovered the EEG Electroencephalograph – Signal Reflecting the electrical field produced by trillions of individual synaptic connections in the cortex and subcortical structures of the brain If you were to cut the brain in half  top and bottom

EEG

EEG

EEG Niels Birbaumer – Trained severely paralyzed people to self-regulate the slow cortical potentials in their EEG in such a way that these signals could be used as a binary signal to control a computer cursor (1990s) Tests included writing characters with the cursor System users require training just as any person is trained to use a keyboard or a computer

Those who depend

ALS Amyotrophic Lateral sclerosis – Muscle weakness and atrophy throughout the body caused by the degeneration of upper and lower motor neurons. Individuals may ultimately lose ability to initiate and control all voluntary movement For the most part, cognitive function is preserved Sensory nerves and the autonomic nervous system are generally unaffected

ALS BCI systems have the ability to allow a paralyzed, “locked-in” patient to communicate words, letters and simple commands to a computer interface that recognizes different outputs of EEG signals and translates them through use of assigned algorithms into a specific function or computing output that the user has the ability to control. A complex mechanical BCI system would allow a user to control an external system possibly an artificial limb by creating an output of specific EEG frequency

P300 Speller User observes 6x6 matrix where each cell contains a character or symbol User receives stimuli that coordinate with a specific output User learns to recognize certain stimuli that exist in relation to a specific output System created successful feedback when tested among the ALS population

EEG Rhythms For analyzing EEG signals, studies suggest that frequencies of 8-12 Hz (mu) and 13-28 Hz (Beta) are most sensible for human control The form or magnitude of a voltage change evoked by a stereotyped stimulus is known as an evoked potential and can serve as a command ie. The amplitude of the EEG in a particular frequency band, can be used to control movement of a cursor on a computer screen

Non-Invasive BCI Forefront of human experimentation Cost effective No implantation Susceptible to noise Cranial barrier dampens signal

What about right now Today, BCIs are already being incorporated into modern technologically dependent society As they were once thought to be strictly a bridge between a neurologically disconnected brain to an outside mechanism of replacing neuromuscular function, the commercial exploitations have already begun as devices can now be purchased that allow users to control an exterior system and navigate and control a graphical Interface using only EEG output signals

NeuroSky Developers at NeuroSky created the Brainwave, a comprehensive non-invasive BCI that connects the user to iOS and Android platforms, and transfers all signal information through Bluetooth as opposed to radio. The EEG outputs for this setup are controlled primarily by variations in brain-state. In order to achieve a specific level of EEG the user may be prompted to relax or improve focus, thus altering the specific output of brain energy and ultimately changing the level of expressed EEG signals

Emotiv Devolped a BCI called the EPOC 16 sensors capture EEGs to the extent of which the system can return feedback to let the user know whether or not they blinked, or sneezed, or smiled The device allows a user to connect to a computer, and perform all basic functions that they otherwise would control using a keyboard, but with the mind. That includes control of gaming platforms as well

Future For the future, BCI technology seems very applicable in a wide variety of areas whether it be medically or commercially The possibilities of how far the systems can go is virtually limitless Control of subvocalization and more advanced EEG processing could lead to telepathic communication and active learning mechanisms This all would bring up an unfeasible amount of ethical discomfort and confrontation

Bibliography Curran , E., & Stokes , M. (2002). Learning to control brain activity: A review of the production and control of eeg components for driving brain-computer interface systems . Academic Press , Retrieved from http://hossein69.persiangig.com/.uZ900jjmWN/sdarticle.pdf Wikipedia: Biomedical Engineering <en.wikipedia.org/wiki/ Biomedical_engineering>. "Disruptions: Brain Computer Interfaces Inch Closer to Mainstream." Bits Disruptions Brain Computer Interfaces Inch Closer to Mainstream Comments. N.p., n.d. Web. 23 Sept. 2013."Brain–computer Interface." Wikipedia. Wikimedia Foundation, 21 Sept. 2013. Web. 23 Sept. 2013. Sellers , E. (2013 ). New horizons in brain computer interface research . U.S national library of medicine, Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3658460/ Naci , L., Cusack, R., Jia , V., & Owen, A. (2013). The brain's silent messenger: Using selective attention to decode human thought for brain-based communication . The Journal of Neuroscience , Retrieved from http://www.cusacklab.org/downloads/nacietal_jon2013.pdf Wolpaw , J., McFarland , D., & Vaughan, T. (2000). Brain-computer interface research at the wadsworth center . IEEE Transaction on Rehabilitation Engineering , 8(2), 222-226. Retrieved from http://www.cs.hmc.edu/~keller/eeg/Wolpaw.pdf Schalk, S., McFarland , D., Hinterberger, T., Birbaumer, N., & Wolpaw , J. (2004 ). Bci2000: A general-purpose brain-computer interface (bci) system . IEEE Transactions on Biomedical Engineering , 51(6), 1034-1043. Retrieved from http://bpv-tese.googlecode.com/hg- history/095dce5394352001ef2ddaefe6f10678ca6413d5/src/referencias/10.1.1.115.7600.pdf Heetderks , W., McFarland , D., Hinterberger, T., Birbaumer, N., Wolpaw , J., Peckham, P., Donchin, E., & Quatrano, L. (2000). Brain- computer interface technology: A review of the first international meeting . IEEE Transactions on Rehabilitation Engineering , 8(2), 164- 173. Retrieved from http://www.ocf.berkeley.edu/~anandk/neuro/BCI Overview.pdf