The document outlines a brain frequency-based wheelchair project aimed at assisting disabled individuals who require enhanced mobility solutions. It describes the technology behind the brain-computer interface (BCI) that allows users to control the wheelchair using EEG signals, addressing mobility challenges faced by disabled persons in India and around the world. Additionally, it includes implementation strategies, statistics on disability, and potential collaborations to optimize the device's effectiveness and accessibility.

1. Brain Frequency Based
Handicap Wheelchair

2. Team Details
Mentor:
K DHANUARAVINTH
– 18bee080@mcet.in - +91 6379156972
R VISHNU RAJ
– 18bee087@mcet.in - +91 8220396913
DR K UMAMAHESWARI
– umamaheswari@drmcet.ac.in - +91 8825843655

3. Sustainable Development Goal
Good Health
& Well being

4. Problem Statement
❑ People who are using wheelchair require secondary
assistance to carry out their basic and daily activities, this
greatly reduces their esteem and will power.
❑ The main problem of the wheelchair is that cannot be
used by disabled person, so the type of artificial aid
needed by a disabled person in order to move about
depends, to a large extent, on the level of his incapacity.
According to our output algorithm
the control of our wheelchair is achieved
According to our output algorithm
the control of our wheelchair is achieved

5. Statistics of Disabled People by MOSPI
sector graph
1.98
1.92
2.2
2.01
2.37
2.18
2.68
2.41
2.18
2.05
2.45
2.21
0 0.5 1 1.5 2 2.5 3
Other than SC/ ST
ST
SC
Total
Persons Males Females
5 Brain Frequency Based Handicap Wheelchair
Need for System:

6. Distribution of disabled persons (%)
in India – Census 2011
6 Brain Frequency Based Handicap Wheelchair
Among the disabled persons, most of them are in the category of Movement disability

7. Disabled population in various age
groups
Brain Frequency Based Handicap
Wheelchair
7
Among the disabled persons, most of them areYoungsters (Active persons)

8. Statistics in India
❑ According to the statistics of the
Ministry of Statistics and Programme
Implementation in 2016, In India out of
the 121 Crore population, 2.68 Crore
persons are 'disabled' which is 2.21% of
the total population which is more than
the entire population of Australia.

9. Statistics in World
❑ According to the statistics of the World
Health Organization in 2011, About
15% of the world's population lives with
some form of disability, of whom 2-4%
experience significant difficulties in
functioning.

10. Solution of the Problem
❑ EEG Based Wheelchair
Recording the Brain wave by scalp
electrodes and classify the signals,
at last fed into the electric motor for
imagined movements.

11. Brain Computer Interface
Direct communication
pathway between an
enhanced or
wired brain and
an external device

13. Introduction
Brain Computer Interface is a fastest growing
emerging technology, in which researchers
aim to build a direct channel between the
human brain and the computer

14. Principle Behind BCI
This technology is based on to sense,
transmit, analyze, and apply the
language of neuron

15. BCI TYPES

16. Non Invasive
The sensors are placed
on the scalp to
measure the electrical
potentials produced by
the brain (EEG) or the
magnetic field (MEG)

17. Used Method – Non Invasive
EEG
Electroencephalography

18. EEG Electroencephalography
Definition
EEG provides the
recording of electrical
activity of the brain from
the surface of the scalp

19. How does it work ?
Electrodes are placed on
the scalp to pickup the
electrical current generated
by the brain
Neuron

20. Brain Response Motor Cortex

21. When groups of neurons fire together,
they provide enough
signal for us to measure from the
scalp
How does it work ?

23. Process of EEG Wheelchair

24. “
Flow Diagram
• Signal Acquisition
First thing we need is some raw EEG
data to process. This data is usually not
clean so some preprocessing steps are
needed
• Signal Preprocessing
The application of filters are applied,
such as a high-pass filter and low pass filter

25. Preprocessing Tool
Brain Frequency Based Handicap Wheelchair
25
• EEGLAB provides an interactive graphic
user interface (GUI) allowing users to
flexibly and interactively process their high-
density EEG and other dynamic brain data
using independent component analysis (ICA)
and/or time/frequency analysis (TFA), as
well as standard averaging methods.

26. “
Flow Diagram
• Feature Extraction
We can apply complex automatic
processing algorithms that allow us to
extract ‘hidden’ information from EEG
signals.
• Signals Classification
For instance, all brain-computer
interface systems follow this common
scheme, in which the classification step
is performed in order to decide what the
user is thinking.

27. “
Flow Diagram
• Control Actions
According to our output algorithm
the control of our wheelchair is achieved
• Output(Wheelchair Motor)
Finally the EEG taught for directions
of wheelchair is precisely controlled
with sensor braking system

28. Software – EEGLAB Matlab

29. Technology Used
❑ Internet of Things

30. The Internet of Things refers to the
billions of physical devices around the
world that are now connected to the
internet, all collecting and sharing data.
What is the Internet of Things?

31. Analysis of Recorded Signals

36. ❑ By collaborating with medical institutes, we can provided our
Brain Interface wheelchairs to person in recrupation.
❑ We can increase the accuracy and efficiency of the device by
collaborating with more detailed neuroscience medical research
team and their works.
❑ We can collaborate with defense and research organization, to
make the wheelchairs free for injured war soldiers to enhance
their quality of life.
Implementation Plan

37. Current Scenario

38. Army Injuries

39. Congenital
Malformation

40. Accidents

41. What it is ?

42. Invasive
The micro-electrodes
are placed directly into
the cortex, measuring
the activity of a single
neuron

43. Partial Invasive
The electrodes are
placed on the
exposed surface of
the brain(ECoG)

46. The letters F, T, C, P, and O stand for Frontal, Temporal, Central, Parietal and Occipital. Even numbers (2, 4, 6, 8) refer to
the right hemisphere and odd numbers (1, 3, 5, 7) refer to the left hemisphere. The z refers to an electrode placed on the
midline.

54. TRANSFER BLOCKS

55. Famous Projects
Elon Musk

56. Comparison with Other Methods
EEG has low spatial but high temporal resolution. Currently,
fMRI and MEG rely on expensive, bulky equipment; PET
requires the injection of a radioactive substance into the
bloodstream. Thus, methods relying on NIRS and, in
particular, EEG, are most commonly used

57. DATA TRANSFER
Electrodes

58. Electrodes
EEG Acquisition System
Microcontroller System

59. Microcontroller System
Motor Circuit

60. Comparison of
EEG Bands

61. Band Frequency
(Hz)
Location Normally Pathologically
Delta < 4 Frontally in
adults,
Posteriorly
in children;
high -
amplitude
waves
Adult slow-
wave sleep
in babies has
been found
during some
continuous-
attention tasks
Subcortical
lesions
diffuse lesions
metabolic
encephalopathy
hydrocephalus
deep midline
lesions

62. Band Frequency
(Hz)
Location Normally Pathologically
Theta 4 - 7 Found in
locations
not
related to
task at
hand
Higher in young
children drowsiness
in adults and teens
Idling Associated
with inhibition of
elicited responses
(has been found to
spike in situations
where a person is
actively trying to
repress a response
or action)
Focal subcortical
lesions metabolic
encephalopathy
deep midline
disorders some
instances of
hydrocephalus

63. Band Frequency
(Hz)
Location Normally Pathologically
Alpha 8 - 15
Posterior
regions of
head, both
sides, higher
in amplitude
on dominant
side. Central
sites (c3-c4) at
rest
Relaxed/reflecting
closing the eyes Also
associated with
inhibition control,
seemingly with the
purpose of timing
inhibitory activity in
different locations
across the brain
Coma

64. Band Frequency
(Hz)
Location Normally Pathologically
Beta 16 - 31
Both sides,
symmetrical
distribution,
most evident
frontally; low-
amplitude
waves
Range span:
active calm →
intense →
stressed →
mild obsessive
active
thinking,
focus, high
alert, anxious
Benzodiazepines
Dup15q syndro
me

65. Band Frequency
(Hz)
Location Normally Pathologically
Gamma
> 32 Somatosensory
cortex
Displays during cross-
modal sensory
processing (perception
that combines two
different senses, such
as sound and sight)
Also is shown during
short-term memory
matching of
recognized objects,
sounds, or tactile
sensations
A decrease in gamma-
band activity may be
associated with
cognitive decline,
especially when
related to the theta
band; however, this
has not been proven
for use as a clinical
diagnostic
measurement

66. Band Frequency
(Hz)
Location Normally Pathologically
Mu 8 - 12 Sensorimotor
cortex
Shows
rest-state
motor
neurons
Mu suppression
could indicate that
motor mirror
neurons are
working. Deficits in
Mu suppression,
and thus in mirror
neurons, might play
a role in autism

67. When and Where
it is use ?

68. • Brain tumor
• Brain damage from head injury
• Brain dysfunction that can have a variety of causes
(encephalopathy)
• Inflammation of the brain (encephalitis)
• Stroke
• Head Injury
• Sleep disorders and more…
Medical Use

69. • Teleoperation of an Industrial Manipulator
through a TCP/IP Channel
• Special machines Controls and More…
Engineering Uses

70. Research Area
• Neuroscience
• Cognitive Science
• Cognitive Psychology
• Neurolinguistics
• Psychophysiological Research

71. Existing Solutions

72. USD 1,000<ABOVE
INR 95,000<ABOVE

73. ❑NeuroScan
❑Brain Products
❑Bio Semi
❑EGI
❑Emotiv
Top 10 EEG Companies
❑ NeuroSky
❑ Advanced Brain Monitoring
❑ g tec
❑ ANT Neuro
❑ Neuroelectrics

74. ❑ Neurosky Brainwave – INR 15,500 Rs
❑ Niscomed Electroencephalogram
(EEG) Machine – INR 98,280 Rs

75. Market Values

76. Area to be Exploited:
❑ Towards commercialization
❑ New Innovations
❑ Research
The Global Electric Wheelchair Market was valued at
US$ 2,911.5 Million in 2018, and is expected to witness a
Compound Annual Growth Rate (CAGR) of 17.1% during the
forecast period (2018 – 2026).

77. USD 1,000<ABOVE
INR 95,000<ABOVE

78. TARGET
❑ Low Cost
❑ High Features
❑ More Safety
❑ Available for Children and Both genders
❑ Tracking System
❑ Long Lasting Battery

79. Limitations

80. ❑ Lack of sensor modality that provides safe,
accurate, and robust, access to brain Signals
❑ Very Expensive
❑ Information transformation rate is limited
❑ Difficult to adaptation and learning

81. Hardware Description
• Neurosky Mind wave mobile Headset or OpenBCI headset electrodes
• Nodemcu esp8266 Wi-Fi module
• Bldc wheel motors
• Hybrid Wheelchair
• Ultrasonic sensors
• Gsm module
• Heavy duty battery’s
• OpensourceBCI tool or EEGLAB
embedded tool

82. Other EEG
Applications

83. NeuroEntertainment
❑ Neurogaming
❑ Virtual Reality
❑ Neuro Toys
❑ Art

84. Security
❑ Brain based authentication

85. Biofeedback Therapy
❑ Anxiety
❑ Sleep Improvement
❑ ADHD and PTSD

86. Cognitive Training
❑ Performance Optimization
❑ Brain Ageing
❑ Early Development
❑ Mindfulness
❑ Accelerated Learning
❑ Enhanced Creativity

87. Implementation Plan Timeline
Q1. 1 Month
Related Literature survey
Q2. 3 Months
Finalization of
architecture and system
design
Q3. 1 Month
Testing
Q4. 12 Months
Next to Outreach plan
87 Brain Frequency Based Handicap
Wheelchair

88. Outreach Plan Timeline
Q1. 1-2 Months
Business Pattern
Q2. 3-4 Months
Approval, Authorization and
Installation of Business
Q3. 5-6 Months
Advertising – Digital
Marketing ,Village
campaigns, primary health
centers
Q4. 5-6 Months
Retail and wholesale – Retail
using Digital platforms and
Whole sales using traditional
marketing
88 Brain Frequency Based Handicap Wheelchair

89. “
• By collaborating with medical institutes, we can
provided our Brain Interface wheelchairs to
person in recreation
• Collaborating with Insurance companies and
offering this wheelchair at the time of accidents
and health risks
• We can collaborate with defense and research
organization, to make the wheelchairs free for
injured war soldiers to enhance their quality of
life
Implementation and outreach plan

90. Business & Employee Goals
Business priorities
▪ Increase customer satisfaction
▪ Maintain growth
▪ Diversify investment
▪ Initiative partnership with 3rd party organizations
Employee opportunities
▪ Multi-disciplinary employment
▪ Worker can Improve their skillsets
90 Brain Frequency Based Handicap Wheelchair

91. Summary
Our business is good
High level Profit
We’re getting our work done
We finished the consolidation project
Our customers relationship
We increased customer retention
91 Brain Frequency Based Handicap
Wheelchair

92. Projects
❑ BrainGate
❑ BCI2000
❑ Australian Bionic Eye
❑ Honda Asimo Control
❑ Kevin Warwick-
The first human Cyborg

94. References
1) Fast fourier analysis and EEG classification brainwave controlled wheelchair – DOI -
10.1109/CCSSE.2016.7784344
2) An Internet of Things (IoT) application to control a wheelchair through EEG signal processing – DOI -
10.1109/WEROB.2017.8383877
3) Design of a Brain Controlled Wheelchair – DOI - 10.1109/CCSSE.2018.8724794
4) Design of an EEG-Based Brain Controlled Wheelchair for Quadriplegic Patients – DOI -
10.1109/I2CT.2018.8529751
5) EEG Wheelchair for People of Determination – DOI - 10.1109/ASET48392.2020.9118340
6) Wheelchair Neuro Fuzzy Control Using Brain Computer Interface – DOI - 10.1109/DeSE.2019.00120

95. Thank You