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Brain gate
1. BRAINGATE:A Neural interface system to bridge
the gap between Brain and Limbs
Presented By
Sachin Jha
11530014
C0-6
2. Contents
1. Introduction
2. Brain-Computer Interface(BCI)
3. BCI research on Animals
4. BCI research on Humans
5. Principle Behind BCI
6. How BCI works?
7. How BCI implements?
8. Application
9. Limitations and Future Implementation.
10. Conclusion
11. References
3. Introduction
• It is a mind-to-movement system that allows a quadriplegic man to
control a computer using his thoughts.
• It monitors brain activity in the patient and converts the intention of
the user into computer commands.
• It implements the technology named Brain-Computer Interface(BCI)
4. Brain-Computer Interface(BCI)
• BCI acts as a direct communication pathway between a brain or
brain cell culture and a device i.e. Computer.
• BCI can be of two types:
1. One way BCI
• Information passes from brain to computer or Computer to
brain.
2. Two way BCI
• Information is exchanged between brain and computer.
5. BCI RESEARCH ON ANIMALS
• At first, rats were implanted with BCI.
• Signals recorded from the cerebral cortex of rat operate BCI to carry
out the movement.
• Researchers at the University of Pittsburgh had demonstrated on a
monkey that can feed itself with a robotic arm simply by using signals
from its brain.
6. BCI research on Humans
• Since there were no complications in trials with monkeys.
Next Step: Humans!
• In December 7, 2004, brain-computer interface had been clinically
tested on a human by an American company Cyberkinetics.
• The Nature report describes the first participant in these trials, a 25-
year-old man who had sustained a spinal cord injury leading to
paralysis in all four limbs three years prior to the study.
7. PRINCIPLE BEHIND BCI
• This technology is based on to sense, transmit, analyze the language of
neurons and translate it in to computer commands .
• It consist of a sensor that is implanted in the motor cortex of the brain and a
device that analyses brain signals. The signals generated by brain are
interpreted and translated into computer commands.
• It consists of a silicon array about the size of an Aspirin tablet that contains
about 100 electrodes each thinner than a human hair.
9. How BCI implements?
• A more difficult task is interpreting the brain signals for movement in someone
who can't physically move his own arm. With a task like that, the subject must
"train" to use the device.
• With an implant in place, the subject would visualize closing his or her disabled
hand. After many trials, the software can learn to recognize the signals associated
with the thought of hand-closing.
• Software connected to a robotic hand is programmed to receive the "close hand"
signal and interpret it to mean that the robotic hand should close. At that point,
when the subject thinks about closing the hand, the signals are sent and the
robotic hand closes.
11. Applications
• Provide disabled people with communication, environment , control,
and movement restoration.
• Provide enhanced control of devices such as wheelchairs ,vehicles , or
assistance robots for people with disabilities.
• This technology provides the ability to control a video game by
thought , ability to change TV channels with your mind etc.
• Control robots that function in dangerous or inhospitable situations.
12. Limitations
• At present the biggest obstacle of BCI technology is the lack of sensor
mode that provides safe, accurate, and strong access to brain signals.
• It is very expensive. Processing and Information transformation of
data is very time taking.
• Difficulty in adaptation and learning.
14. Conclusions
• BCI can help paralyzed people to move by controlling their own
electric wheelchairs, to communicate by using e-mail and Internet-
based phone systems, and to be independent by controlling items
such as televisions and electrical appliances.
• Conclusively, BCI has proved to be a boon for paralyzed patients and
all human being in future.
15. References
• Wang, Yijun; Wang, Ruiping; Gao, Xiaorong; Hong, Bo; Gao, Shangkai (June 2006). "A practical
VEP-based brain-computer interface". IEEE Transactions on Neural Systems and Rehabilitation
Engineering. 14 (2): 234–239.
• Levine, SP; Huggins, JE; Bement, SL; Kushwaha, RK; Schuh, LA; Rohde, MM; Passaro, EA; Ross,
DA et al. (2000). "A direct brain interface based on event-related potentials". IEEE transactions on
rehabilitation engineering: a publication of the IEEE Engineering in Medicine and Biology Society.
• Huang, D. Kai Qian ; Oxenham, S. ; Ding-Yu Fei ; Ou Bai “Event-related desynchronization/
synchronization-based brain-computer interface towards volitional cursor control in a 2D center-
out paradigm” Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB), 2011
IEEE Symposium 11-15 April 2011.
• https://spectrum.ieee.org/the-human-os/biomedical/devices/paralyzed-individuals-operate-
tablet-with-brain-implant
