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NON VERBAL & BRAIN COMPUTER INTERFACE Submitted by :- Sourabh Jain(IIT2010038) Nikhil Karnwal(IIT2010012) Aman Kumar(IIT2010043) Ishant(IIT2010024) Kush Meena(IIT2010096) Guided By:- Dr. Anupam Agarwal (IIIT-ALLAHABAD)
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Non verbal & brain computer interface

Nov 07, 2014

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Nikhil Karnwal

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Page 1: Non verbal & brain computer interface

NON VERBAL & BRAIN COMPUTER INTERFACE

Submitted by :-

Sourabh Jain(IIT2010038)

Nikhil Karnwal(IIT2010012)

Aman Kumar(IIT2010043)

Ishant(IIT2010024)

Kush Meena(IIT2010096)

Guided By:-Dr. Anupam Agarwal(IIIT-ALLAHABAD)

Page 2: Non verbal & brain computer interface

CONTENTS

Introduction What Inspired Us ! Working Architecture Inventions Present work and developments Difficulties Future scope Video Content’s Conclusion References

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INTRODUCTION

Brain-computer interface (BCI) is a collaboration between a brain and a device that enables signals from the brain to direct some external activity, such as control of a cursor  or a prosthetic limb . 

Brain Computer Interface(BCI) is a direct communication pathway between the brain and an external device .

A brain–computer interface (BCI), often called a mind-machine interface (MMI), or sometimes called a direct neural interface or a brain–machine interface (BMI) .

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CONTD..

 In BCI brain does not use nerves to give orders to body or to the world outside .

In one BCIs, computer either accept signals from the brain or send signals to it but not both.

In the case of cursor control, for example, the signal is transmitted directly from the brain to the mechanism directing the cursor, rather than taking the normal route through the body's neuromuscular system from the brain to the finger on a mouse.

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WHAT INSPIRED US

The Computer-Human Interface has a new contender technology. Though we’d like to think we’ve come a long way with computers, the keyboard and mouse remain the predominant way we interface with them. We’ve had the unfulfilled promise of handwriting and voice recognition and hope that something better will come along sooner or later. Perhaps this is it - brain computer interface technology so we start our project with BCI.

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Schematic diagram of a BCI system

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WORKING ARCHITECTURE

Types of BCI: - Invasive BCI Non Invasive BCI Partially Invasive BCI

These types are decided on the basis of the technique used for the interface. Each of these techniques has some advantages as well as some disadvantages .

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INVASIVE BCI

Invasive BCI are neuroprosthetics(a series of devices) whose electrode array heads are buried within the brain itself, and left there on a permanent basis.

Invasive BCI are directly implanted into the grey matter of the brain during neurosurgery .

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EARLIER USED

An Invasive BCI containing 68 electrodes was firstly implanted onto jerry’s visual cortex and succeed in producing a sensation of seeing light.

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MERIT AND DE-MERITS

As they rest on grey matter, produce the highest quality signals of BCI devices.

These BCIs are prone to building up of scar-tissue which causes the signal to become weaker and even lost as body reacts to a foreign object in the brain.

Require complex surgery to implant, and usually require a permanent hole in the skull.

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PARTIALLY INVASIVE BCI

Partially invasive BCI, are neuroprosthetics that are implanted on a permanent basis within the skull itself, but only onto the surface of the brain. 

They spread out electrode arrays over the surface rather than burrowing inside.

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EARLIER USED

Electrocorticography (ECoG) measures the electrical activity of the brain taken from beneath the skull.

 The researchers,  Eric Leuthardt and Daniel Moran, enabled a

teenage boy to play  space invaders  using his ECoG implant.

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MERITS AND DE-MERITS

They produce better resolution signals than non-invasive BCIs.

But , not as high as Invasive BCIs system.

 Lower risk of forming scar-tissue in the brain than fully invasive BCIs.

This approach typically results in a permanent hole in the skull.

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NON-INVASIVE BCI

Non-invasive BCI is the version of interface used when only a temporary connection to the brain is required.

It is the least accurate of the neuroprosthetic methods, dealing with general brainwaves that are dampened by passing through the skull.

Electroencephalography (EEG) is the most studied potential non-invasive interface, mainly due to its fine temporal resolution, ease of use, portability and low set-up cost.

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MERITS AND DE-MERITS

 It is sensitive enough to perform general tasks, and gather non-specific information.

 It typically takes considerable conscious effort to drive brainwaves as it is dampened by the skull.

It produce poor signal resolution.

It is more difficult to determine the area of the brain that created these brainwaves.

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INVENTIONS

First scientists to come up with a working brain interface to restore sight as private researcher, William Dobelle.

(Wolpaw and McFarland 2004) allowed a user to move a cursor around a 2 dimensional screen.

(Millán, et al. 2004) allowed a user to move a robot around the room.

1987 - Lusted and Knapp demonstrated an EEG controlling a music synthesizer in real time.

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PRESENT WORK AND DEVELOPMENTS

Although significant progress has been made in researching brain–computer interface technologies in recent years, the applications controlled by these interfaces have largely been designed for trainingor demonstration purposes. Communication

Methods of assistive communication:- Simple binary (yes/no) capabilities. Iconic selection applications such as TalkAssist. Virtual keyboards that support spelling.

Donchin et al. have developed a method which allows theuser to select a letter by flashing rows and columns of a

two-dimensional (2-D) alphabet grid to determine the desired letter.

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CONTD.o Neural Prosthetics

Another key application for BCI technology is Restoring movement for people with motor disabilities.

Cortical signals have been used to control a hand orthosis essentially restoring the connection from the brain to a paralyzed arm.

o Aware ’Chair—Communication and Environmental Control

The Aware ’Chair is a context-aware intelligent power wheelchair which integrates environmental control, communication, and multilevel prediction based on context and user history.

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CONTD.

Neural Screen Navigation—New User Interface Control Paradigms

To identify possibilities for alternate paradigms of navigating a computer screen using brain signals, in addition to traditional 2-D spatial navigation (such as cursor movement controlled by a mouse).

One option for increasing accuracy and reducing errors is logical control, which is movement between targets triggered by a discrete control signal.

They implemented logical control with signals from a neurotrophic-electrode that had been implanted in the cortex of a patient .

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CONTD. Neural Internet

Access to the internet opens a myriad of opportunities for those with severe disabilities, including shopping, entertainment, education, and possibly even employment.

Neural control users cannot control a cursor with a great

degree of precision, so, therefore, the challenge of adapting a web browser for neural control is in making links—which are spatially organized—accessible.

The University of Tuebingen developed a web browser controller to be used with their thought translation device , but it requires the user to select from an alphabetized list of links.

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FUTURE SCOPE

Direct control over the activities of all individual neurons by means of nanorobots.

 Arbitrary read/write access to the whole brain.

The line between the mind and the computer is blurred. Partial or full uploading is possible and inevitable.

More direct links into the brain with the ability to read certain thoughts and copy a wide range of data and information into various parts of the brain.

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LINK :- HTTP://YOUTU.BE/TXDFCJRASQM

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DIFFICULTIES There are many challenges inherent in employing BCI

control for real-world tasks. These challenges can be generalized into several categories.

1) Information transfer rate (“bandwidth”)—Even the best average information transfer rates for experienced subjects and well-tuned BCI systems are relatively low.

This is too slow for natural interactive conversation, so we are researching ways of optimizing selection techniques and incorporating prediction mechanisms to speed communication.

2) High error rate—A significant complicating factor in the slow information transfer rate of BCI users is the high probability of errors. Brain signals are highly variable,

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CONCLUSION

Brain-Computer Interface (BCI) is a method of communication based on voluntary neural activity generated by the brain and independent of its normal output pathways of peripheral nerves and muscles.

We can say as detection techniques and experimental designs improve, the BCI will improve as well and would provide wealth alternatives for individuals to interact with their environment.

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REFERENCES http://www.cs.man.ac.uk/aig/staff/toby/research/bci/

richard.seabrook.brain.computer.interface.txt http://www.icad.org/websiteV2.0/Conferences/ICAD2004/

concert_call.htm http://faculty.washington.edu/chudler/1020.html http://www.biocontrol.com/eeg.html http://www.asel.udel.edu/speech/Spch_proc/eeg.html http://en.wikipedia.org/wiki/Brain%E2%80%93comput

er_interface.

http://ieeexplore.ieee.org/ielx5/10/28897/01300799.pdf http://ieeexplore.ieee.org/ielx5/10/22228/01035968.pdf http://ieeexplore.ieee.org/ielx5/7333/27323/01214694.pd

f

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THANK YOU