International Journal of Engineering Trends and Technology (IJETT) – Volume 34 Number 7- April 2016
Using Brain Computer Interface for Home
Automation
Harish Verlekar #1, Hrishikesh Gupta*2, Kashyap Joshi#3
#1*2
#3
Student, Department of Electronics and telecommunication, MPSTME NMIMS University, Mumbai, INDIA
Assistant Professor, Department of Electronics and telecommunication, MPSTME NMIMS University, Mumbai,
INDIA
Abstract- Brain computer interface (BCI) is a communication
pathway between the brain and the external peripheral devices
like computers. We propose to use this technology for Home
automation. Home automation can be totally revolutionized
using BCI. Brain produces various types of waves like alpha
(9-13Hz), beta (14-30Hz), theta (4- 8Hz), delta (1-3Hz).Using
these waves we can control various home appliances. The
entire concept consists of 4 main stages detection,
amplification, processing, output. First detecting the brain
signals using an EEG cap or electrodes. These brain signals
are very weak hence in second stage we need to amplify these
brain signals to a usable amount and filter these to remove
noise. Then thirdly, we will have to convert these signals into
digital by using A to D converter and into a type a computer
software or a microcontroller can understand. Fourth, taking
this decoded signal and sending these signals wirelessly, by
using an RF circuit to a distant switch circuit, which will
turn on or off the appliance in vicinity. Using this
technology the life of people would be further simplified,
physical efforts would be considerably reduced and it
would also prove as a boon for physically disabled people.
technology i s breathtaking and has the potential to
completely revolutionize and change our lives[4].
As an application of BCI we have proposed to
interface it with home appliances and automate our
homes.
II. System Design
Figure 1.
System Design
Keywords: BCI(Brain Computer Interface), EEG, Automation
I. INTRODUCTION
Brain Computer Interface (BCI) is a process by which
Humans can control the external devices using their brain
waves.[1] These interfaces are made using sensors which
can record brain data either by invasive plantation or noninvasive plantation. Our Human Brain is highly complex
and is made up of 100 billion neurons[1]. There are many
types of neurons in our brain such as motor neurons,
sensory neurons. These neurons get fired up while
generating a response for a particular stimuli and generate
an electrical signal which is detected by the electrodes and
can be used to control a number of devices.
Home Automation is an area where BCI can be used
and our entire house can be controlled simply by our
brain[2]. This technology would prove as a great boon
for almost all people on the planet. Less energy would
be wasted for performing menial tasks such as switching
on the lights, ac’s and other electrical appliances[3]. This
ISSN: 2231-5381
The System Design consists of two main stages the
transmitter stage and the receiver stage. The transmitter
circuit consists of the following stages:
A. Electrodes
We will be using dry non-invasive scalp sensors to
measure the electrical activity of our brain.[5]
Specific electrodes would be placed at the motor
cortex area and the rest would be placed in many
specific areas of the brain to measure brain activity.
B. Amplitude and filter circuit
These signals along the scalp are very weak i.e, in
micro volts and contain noise[6]. Thus, we need to
amplify and filter out the frequencies not useful to us , We
can use an instrumentation amplifier to amplify the
signals we get from electrodes.
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International Journal of Engineering Trends and Technology (IJETT) – Volume 34 Number 7- April 2016
One such instrumentation amplifier is AD620, in which
we can vary the gain by varying the value or resistor. A
High pass filter is designed having cut off frequency 7
Hz and a low pass filter is designed which will have a
cut-off frequency at 31 Hz[7]. Hence it will allow only
frequencies from 8-31 Hz to pass. The basic noise in
all the systems is at 60HZ which is due to power line
interference. For, suppression or attenuation of this
frequency we can design a notch filter, that will severe
reduce gain of this frequency[8]. Also an Analog to
Digital converter will be required to feed the data to
microcontroller.
F. Wireless-Transmitter
The wireless transmitter will transmit the signal
which will be received by the receiver end. A Zig-bee
Wireless transmitter is used to transmit the signals.
The Receiver circuit consists of the following parts
Wireless Receiver
The Receiver will receive the signals and feed it to
the O/P Devices. The output devices can be anything
lights, TV, fan etc.
III. Working
Figure 2. Motor cortex area of human brain
D. Micro-controller
After the amplification and the filtering process the
microcontroller will process the signals and give the
output according to the specific algorithm. The microcontroller will do the following operations:
1. Will take the digital signal data from the ADC and
process it according to the working specified.
2. The microcontroller will be directly connected to
the user interface which will display the data
selected, and details such as concentration level.
3. The microcontroller will send the processed data
to the wireless transmitter which will transmit it
wirelessly.
The electrical signals that helps to communicate 2
neurons and that which forms the basis of whatever we do is
never fully transferred from one neuron to another ,but
some part of it escapes and reaches the scalp.[9] This
electrical neural signal can be observed and captured
using right equipment’s such as EEG electrodes. The
electrodes will then send the signals to the amplifier and
filter circuit wherein the signal is amplified and unwanted
noise and signals are filtered out .The analog signals are
then converted into digital signals using an ADC
converter. The microcontroller process the signals based
on the following logic.
1. When the user imagines his right hand the left
part of the motor cortex in the brain gets and the
signals
are
detected[10].Over
the motor
cortex beta waves are associated with the muscle
contractions that happen in isotonic movements
and are suppressed prior to and during movement
changes[1].So now the cursor will move in the
right hand side of the user interface. The same can be
done with the left hand, but the only difference will
be is that when the user imagines his left hand
the cursor will move to the left hand side.
E. User-Interface
The user interface will act as an interface which
would let the user know which device is selected. It will
basically let the user choose which device it wants to use.
Apart from this the user interface will also be having
many other details such as concentration level. The user
interface will be completely customizable by the user. The
user can add and name the devices which he wants to
control. The user interface can be designed as a mobile
application to make it more user friendly.
Figure 4. Movement of the cursor according to brain signal
Figure 3. User Interface
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International Journal of Engineering Trends and Technology (IJETT) – Volume 34 Number 7- April 2016
Kotchoubey, A. Kübler, J. Perelmouter, E. Taub, and H. JOURNAL OF
COMPUTERS, VOL. 9, NO. 9, SEPTEMBER 2014 2165 © 2014
ACADEMY PUBLISHER Flor, “A spelling device for the paralysed,” Nature,
vol. 398, pp. 297- 298, 1999.
Figure 5. Brain Signals According to right and left hand
Imagination.
2.
Now if the user wants to select a particular device
he will have to concentrate his mind. When a user
concentrates his mind Beta waves (16-31Hz) are
generated, the brain emits more than 18 Hz
frequency and the frequency will get locked and
that particular device will get selected. It must be
noted that when the user moves the cursor to the
left or to the right there will be a particular delay
after every move by the cursor which the user can
set. When a person relaxes alpha (8 – 15 Hz)
waves are emitted.
The above logic can also be implemented using
machine learning, which will greatly reduce the error of
the system.
IV. Conclusion
So by using our brain our homes can be
automated using Brain computer interface. A three
application based graphical user interface was
developed. By interfacing the system with brain using
EEG system, we are able to implement home automation
system using BCI technology. This will help people with
serious illness as they need not depend on others for
doing their day to day activities.
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