1. Neurobotix LTD.
Bishestha Adhikari
Arthur Assamoi
Morgan Auzenne
Nicholas Helmstetter
BIEN 400
Louisiana Tech University

2.  Education and educational progress monitoring hindered by the lack
of integration with biometrics technologies
 Glaringly evident in the education of children with cognitive
disabilities
 1 of 88 children has been identified with an autism disorder (CDC,
2012)
 Intention is to increase the efficiency of educational progress
monitoring in early childhood education
 Incorporation of several biometrics technologies with Hatch/
SMART educational board

3.  Intended to use for the progress monitoring in early childhood education
including child under special care
 In current Scenario, the monitoring based on observation is in practice
 Special need child uses Puppet or Wikkistix as a source of communication
or learning
 In order to develop an education progression tracking system for cognitive
children, we envision a two year time frame
 First year – underlying concept and generating preliminary data
 Second Year – continue design process and refine the system and prepare for
market testing

4.  We Plan to implement EEG and Eye/Head tracking together
with a Smart Board
 The EEG will feed into a system for monitoring the active
areas in the child’s brain to track the engagement and
development of these areas
 The eye/head tracking will track the attentiveness of the child
to implement a quick educational material switch to try to
constantly keep the child engaged

5. Product Description Design Specification
Detect active areas of the brain EEG headset will be used to determine the active centers of the
waves brain. This will be used to track the engagement and development
of areas.
Detecting Head/ Eye movement Gyroscope on the EEG headset will be used to detect the head
tracking whereas the Eye tracking glasses will be used to detect the
eye movement.
Ease of Use The Headset is made adjustable to fit most of the head size. The
eye tracker can be designed is such a way that its comfortable for
all kinds of child.
Reliability As its used by child, it is made using almost no or very less wire
connections and try to make it easy and comfortable so that it can
be used for long time.

6. Biometrics Technology Pros Cons
EEG Capable of detecting the EEG signals Intensive programming required to
from the wearer and quantifying as create algorithms to analyze the data.
progress related data Sensitivity issues during setup.
GSR Capable of detecting excitement as a Cannot quantify engagement towards
response of skin secretions. a stimulus. Only useful in quantifying
the wearer’s level of excitement.
Hall Effect Sensor Capable of detecting the wearer’s Could possibly interfere with the
head oriented to the board. function of the SMART board and
Can detect the direction the wearer is other measurement equipment.
facing relative to the front of the
board.
Gaze/ Eye Tracking Capable of determining where the Only tracks the eyes, not the
eyes of the wearer are focused. orientation of the head.
Pupil Dilation Can measure excitement towards Does not include engagement or
external stimuli. disinterest in the stimuli.
EKG Can measure excitement towards Does not include engagement or
external stimuli. disinterest in the stimuli.

7.  EEG
 Record and analyze the wearer’s brain signals to determine their
excitement and engagement towards an external stimulus
 Hall Effect Sensors and Eye/Gaze Tracking
 Coupled together to determine where the wearer is looking and focusing
relative to Hatch/SMART Board
 Feedback to Hatch system to control material output
 Hatch/SMART Board
 Provides educational software and interface for wearer

8.  Emotiv EPOC EEG headset tested for potential to measure
brain activity when varied through different types of activities
 Headset fitted to subject who was instructed to perform
different activities to test cognitive data collection of device
 EMOTIV user interface includes three waveforms on two
graphs
 Waveforms included : Engagement/Disinterest;
Excitement/Calm; Meditation
 Graphs included: a current feed with a time span of 30
seconds and a long term feed with a span of 5 minutes

9.  Subject instructed to be calm and meditate
 Significant rise in blue meditation curve

10.  Subject instructed to stare at white wall
 Increase in calmness

11.  Subject instructed to construct a Word document
 Increase in engagement
 Excitement increases then levels off to calm

12.  The EEG is capable of
reading and analyzing
the subject’s brain
waves
 Capturing raw data is
the next step
 The Emotiv algorithm
for analysis may be
reworked to better fit
the overall device

13. 1. Test various technologies for integration into device
1. Test Emotiv EPOC EEG
2. Test Gyroscope
3. Test Gaze/Eye Tracking Technologies
4. Test Hall Effect Sensor
2. Integrate feasible technologies into educational systems
1. Output Data for Progress Monitoring
2. Integration Into Hatch Software
3. Develop prototype
1. The prototype should be developed with the main users,
children, in mind
4. Field Testing
1. The device will be field tested on the developers and children
without serious cognitive or physical impairments

14.  Goal is to detect the engagement and
attentiveness of children utilizing an
educational software
 Better quantify student progress during
education
 Progress monitoring utilizing Emotiv EPOC
EEG headset
 Attentiveness monitored by head and gaze
tracking technologies

15. PROGRESS MONITORING HEAD AND GAZE TRACKING
 Emotiv EPOC EEG is method  Gaze/ eye tracking glasses
of gathering EEG signals from and/or Hall Effect sensors
the student
 Built in algorithms used to an
will actively determine
extent to determine the where the student is looking
emotional state of the child  This information is fed back
 Plan to develop secondary to the Hatch software
software to collect and
analyze raw EEG data
 Headset also includes a
gyroscope for potential head
tracking abilities

16.  Educational board
provided by a SMART
board
 Educational software
provided by Hatch
 Include a method for
collecting feedback
from the various
biometrics sensors.
 EEG data output as its
own feed

18. EQUIPMENT TESTING FIELD TESTING
 Individual technologies  Tested by project team
tested for inclusion in members and students
overall device
 Durability
 As each individual
technology is approved we  Reliability
will include it in the overall
headset design  Efficacy

19. Final
Presentation
Field Testing:
Real World
Durability,
Reliability and
Efficacy
Testing
Development
of Prototype
and Initial
Testing
Design of
Prototype
Headset
Individual
Biometrics
Testing: EEG
and Eye
Tracking
Research and
Initial Testing
September October November December January February March April May

20. TWO TEAMS OF TWO ONE TEAM OF FOUR
 Progress Monitoring  Incorporate technologies
Biometrics Team into one device
 Focus on EEG
 Design program to generate an
analysis of wearer’s brain signal  Incorporate device into
data Hatch/SMART system
 Feedback Biometrics Team
 Focus on Eye Tracking and Hall
Effect  Testing for durability and
 Design system to track the reliability
wearer’s head and eyes relative
to Hatch/SMART board
 Field testing with children

21. Price Per
Number Total Our
Component
Required
Component
($)
Price ($) Cost ($)  Prototype to be developed
for $1400.00
Emotive EPOC EEG
1 299.99 299.99 Donated
Headset  Includes donated
SMART/ Hatch
board and software
1 8,126.91 Donated components
 Overall cost of product
Computer 1 500-1500 1000 Donated
not to exceed $11000.00
Eye Tracking
Hardware Allotment
500 500 depending on software
Outsourcing of
purchased
Programming
Allotment
500 500  No direct competitors to
Various circuit and our design
programming 150 150
components  Several competitors to
Travel 250 Hatch/SMART system
Total Price 10576.9 1400