This document presents a brain-computer interface (BCI) based system for automatically adjusting smart home environments based on the user's cognitive state, as detected through a single-channel EEG acquisition module. The system architecture consists of 3 modules: 1) a wireless EEG acquisition module using Bluetooth, 2) an embedded signal processing module to detect cognitive states from alpha and theta brain waves, and 3) a host system that controls smart home devices via signals from the processing module. The system aims to adapt environments like lighting based on detected alert vs. drowsy cognitive states over a 10 minute period, providing a low-cost, portable alternative to existing BCI systems.

1. BRAIN COMPUTER INTERFACE:
BASED SMART LIVING ENVIROMENTAL AUTO-ADJUSTMENT
CONTROL IN UNIVERSAL PLUG AND
PLAY HOME NETWORKING
PRESENTED BY
ANU .N.RAJ
S7 IT
ROLL :1 3
GUIDE: IERIN BABU

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3. INDRODUCTION
• Biological computer
• Analogues to cpu of a computer
• Neurons :- eclectically excitable cells in brain
• Electroencheplaogram -:detect brain voltage
EEG electrodes NEURON 3

4. • A brain–computer interface (BCI) -
is a communication system that translates
brain-activity into commands for a computer
or other devices
• Based on the advantages of –
BCI technique ,this system has integrated it
with the environmental control systems in a
smart house
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5. EXISTING SYSTEM
• P300 based BCI system
• Result of decision making
• Used in real time BCI games Eg:-Mind Balance
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6. EXISTING SYSTEM …..
• Motor imagery BCI
• EEG of motor movements Eg:-Graz BCI
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7. DRAWBACKS
• Need active metal command.
• Do not adapt to cognitive state.
• Bulky and expensive.
• High power conception.
• Limit flexibility , portability and practicability.
• Messy cables are used.
• lot’s of electrode’s are used.
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8. PROPOSED SYSTEM
• A brain computer interface –based smart living
environment auto adjustment control system
(BSLEACS)
• Cost effective, extendable.
• Based on cognitive state.
• Single EEG channel
• Portable signal aqustisition module
• Bluetooth is used.
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9. WORKING
• The system architecture of BSLEACS consists of
3modules:
1)Wireless physiological signal acquisition module
2)Embedded signal processing module
3)Host system
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11. WORKING contin……..
1)Wireless physiological signal acquisition module
• It consist of:-
Front –end amplifier
Microprocessor
Wireless transmission unit
• Amplifier unit:- preamplifier , band pass filter , ADC.
• ADC input stored in microprocessor.
• Power line interference is removed .
• Bluetooth is used in wireless module.
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12. • Li-ion battery is used .
• Work for 33 hours
EEG amplifier&
acqutisition
Microprocessor
unit
Wireless
transmission
Blue tooth
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13. 2)EMBEDDED SIGNAL PROCESSING UNIT
• Real time processing of raw EEG
• Perform the real time cognitive state detection
algorithm
• Black fin processor is used.
• UART interface is used.
RAW EEG 13

14. • Ethernet is used to transfer the command to host
system.
Signal processing module Back fin processor
Wireless unit
UART
Signal
processing
RF module
/Ethernet
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15. How to decode the EEG signal?
• Theta wave(4-7Hz) and alpha wave( 8-11Hz) are used.
• Reflect the cognitive state.
• EEG of occipital midline is used.
• Discriminating power and high correlation with cognitive
state.
• State of alert to drowsy is detected by increase in alpha
and theta rhythm
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16. • User’s instantaneous cognitive state is not used.
• Cause discomfort to user.
• Trend of user’s cognitive state is used.
• Average of estimated cognitive state ,previous 10
min .
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17. Low
pass
filter
Extract
alpha and
theta
Build alert
model of
alpha
Build alert
model for
theta
Calcula
te MDA
Calcula
te MDT
RAW EEG
Calculate
MDA
Build alert model
Calculate deviation from alert
model
output
How Algorithm works'?
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18. Flow chart explanation
• High frequency noise removed by filter.
• FFT is used to extract alpha and theta rhythm.
• Alert state is modeled.
• Mahalanobis distance from alert model.
• Drowsy subjects mahalanobis distance increases.
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19. 3)Host system and environment controller
• Processing unit sent command via Ethernet.
• PLC is used for controlling device .
• Ethernet hand over data packet to PLC.
• Control the environment control systems.
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21. Application in environment control system
• During exercise and working ,alert state
• Alert state ,day lamp is on
• Relaxing and sleeping ,drowsy state
• Drowsy state, day lamp is off
Alert state Drowsy state 21

22. Advantages
BCI system Mind balance Graz BCI BSLEACS
EEG signal P300 wave Motor imagery Alpha and theta
Channels 2 3 1
Transmission Cable Cable Bluetooth
Power supply power line power line Li-ion battery
Back end signal
processing unit
Personal computer Personal computer Embedded signal
processing unit
Control mode Active mental
command
Active mental
command
Adaptation
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23. Limitation
• Ethical issue prevent its development
• EEG signal is prone to inference.
• There are many chemical process ,can’t be
captured.
• Too costly to set up .
• Cannot be used for brain disease people.
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24. Future scope
• Bionic eye
• Transfer the hearing impulse to brain.
• Robotic assistance to old and disables
• Real time gaming
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25. Conclusion
• BCI is a high potential idea with high impact on the
society .
• Future developments enable ,complex performance .
• Researchers hope that every thing will be mind
controlled in future.
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26. References
• www.howstuffswork.com
• www.ieeexplore.com
• www.wekipedia.com
• Brain-Computer Interfaces Using Electrocorticographic Signals
Gerwin Schalk, Member, IEEE, and Eric C. Leuthardt,2011
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28. THANK YOU !
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