GDMS Sr Engineer Mike DeMichele
Design of Hands-Free System for
Device Manipulation
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
Current System:
Future System:
Motion Joystick
Requires physical
manipulation of
input device
No physical
user input
PROJECT OVERVIEW
Goal: Create and demonstrate a system to relocate assets at a user’s
command without physical input from the user.
Technological Readiness Level : 2-3
Based on DOD TRL Definitions
“Active R&D is initiated. This includes analytical studies and
laboratory studies to physically validate the analytical predictions
of separate elements of the technology. Examples include
components that are not yet integrated or representative.”
[0] DOD TRL Definitions
2
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
2
AGENDA
•
•
•
•
•
•
•
3
Motivation
Problem Statement
EEG Context
Stakeholders and Gap Analysis
CONOPS
CONOPS Validation
Project Management
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
3
PHYSICALLY DISABLED STATISTICS
Approximately 1.9% of the U.S. population, or 5,596,000 people, reported some form of paralysis
[1] 2012 study performed by the Christopher and Donna Reeve Foundation
4
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
4
HUMAN-MACHINE INTERACTION
• Process driven by input from human user
• Relies on interface to continue data exchange
Challenges
• Systems requiring a huge amount
of user input
• Time sensitive systems
• Systems requiring user accuracy
• Systems requiring frequent
operator turnover
[3] Robot FRIEND, Institute of Automation (IAT)
of University of Bremen
[2] FDA Device Regulations- Human Factors
5
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
5
AGENDA
•
•
•
•
•
•
•
6
Motivation
Problem Statement
EEG Context
Stakeholders and Gap Analysis
CONOPS
CONOPS Validation
Project Management
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
6
PROBLEM STATEMENT
Hands-free
• Paralyzed people are unable to use any device which requires a physical
interaction.
Multi-functional
• The control system can be applied to the operation of a wheelchair, robot or
computer in an effort to substantially increase the safety, quality of life and
independence of a paralyzed person
7
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
7
SCOPE
Before a new control interface can be selected for the robotic aid, we must examine the
maneuvers which the robot will need to perform.
This project will perform a simulation to collect and analyze the data crucial to
creating a hands-free control interface.
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
8
TRADE SPACE
ALTERNATIVES
Methods to Perform Hands-Free
Control
• Eye Tracking Software
• Head Movement
(Gyroscope)
• Voice Control
• Muscle Contraction
Detection
• Brain-Computer Interface
-EEG
[4]RoboNurse, Computers Making Decisions- Standford
[5] Accompany Care-O-Bot, Fraunhofer Institute
9
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
9
BRAIN-COMPUTER INTERFACE (BCI)
Direct communication pathway between the brain and a computing device
BCI Type
Signal
Quality
Sensor Location Cost
Other
Commitmen
t
1. Invasive
Best
In Brain Matter
High
2. PartiallyInvasive
Medium
Under skull
High
3. Non-invasive
Poor
On Scalp
Low
Risk of scar tissue
EEG is the most studied non-invasive BCI method due to its low cost and ease of use. The data
quality is improving quickly.
10
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
10
AGENDA
•
•
•
•
•
•
•
11
Motivation
Problem Statement
EEG Context
Stakeholders and Gap Analysis
CONOPS
CONOPS Validation
Project Management
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
11
STAKEHOLDER ANALYSIS
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
12
STAKEHOLDER INTERACTIONS
13
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
13
GAP ANALYSIS
• The necessity of physical movement of the control interface is a highly limiting factor
is the system usability and user workload.
• For the 2,909,920 severely paralyzed persons in America, the necessity of physical
motion to operate a device renders the system unusable.
Win-Win - Create a hands-free control system which can match the quality
and cost of a traditional control system
14
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
14
AGENDA
•
•
•
•
•
•
•
15
Motivation
Problem Statement
EEG Context
Stakeholders and Gap Analysis
CONOPS
CONOPS Validation
Project Management
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
15
CONOPS
A paralyzed person cannot perform basic motor tasks without
assistance. A robot, controlled by the person, can cross the room and
retrieve an item (prepackaged meal, medicine, cell phone).
User with HFCS
16
YouBot by Kuka
[9] Youbot, Vertically-Integrated Projects, GT
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
16
COMMANDS FOR CONOPS
Loop 1: Correct direct
1. Stop motion
2. Pivot to correct direction
3. Resume forward motion
Assumption 1:
Hand contacting object will result in grasp.
(No slipping, etc)
17
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
17
USE CASE
18
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
18
MISSION REQUIREMENTS
R.0 The HFCS shall be operable without physical user input.
R.1 The HFCS shall direct the motion of a simulated robot in 3 dimensions.
R.2 The robot shall perform motion directed by HFCS.
R.3 The HFCS shall direct the movement of the simulated robot arm.
R.4 The robot arm shall perform movement directed by HFCS
R.5 The HFCS shall not harm the user in any way.
R.6 The HFCS shall provide flexibility for use for a variety of functions.
R.7 The HFCS system shall operate in real-time.
19
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
19
FUNCTIONAL DIAGRAM
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
20
AGENDA
•
•
•
•
•
•
•
21
Motivation
Problem Statement
EEG Context
Stakeholders and Gap Analysis
CONOPS
CONOPS Validation
Project Management
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
21
VIRTUAL ROBOTIC SIMULATOR
• V-REP as a virtual robot simulator
• Physics based collisions
• Large number of ready made models
• Free for educational use
• YouBot will pick up an object and
move it to another location
• Limited preprogrammed movement
YouBot, a popular multi-function robot
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
22
YouBot VIRTUAL ROBOT[9]
• Platform
• Omnidirectional wheels
• Zero turn radius pivoting
• Surface for placing multiple objects
• Arm
• 5 joints for 6DoF movement (Arm is not capable
of full pitch motion)
• Each joint has a limited range of movement
• Gripper
• Open and close
• To simplify the YouBot movement, we programmed a function to move all the joints
according to the x-y-z position of the gripper in order to reduce user complexity
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
23
SIMULATION OVERVIEW
Fetch item - an item the virtual robot is instructed to pick up
Fetch point - the location of the fetch item
Task - a randomly generated trip from a start point, to the fetch point, picking up the fetch item and carrying it to an assigned finish point
Start location - initial (x,y) coordinates of the center of the robot’s platform
Finish location - final location of the center of the robot’s platform
Start Points (Green), End Point (Red)
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
Fetch Points (Blue)
24
SIMULATION STATISTICS
Statistics to Record per Task
1. Start location
2. Fetch item location
3. End location
4. Total time on task
5. Time spent on Path 1
6. Time spent on Path 2
7. Time spent picking up object (frame
between Path 1 and Path 2)
8. Total distance traveled
9. # of platform rotations
10. degrees rotated for each rotation
11. # lateral arm movements
12. Arm displacement per movement (cm)
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
25
AGENDA
•
•
•
•
•
•
•
26
Motivation
Problem Statement
EEG Context
Stakeholders and Gap Analysis
CONOPS
CONOPS Validation
Project Management
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
26
FUTURE WORK
Spring Semester:
Create simulation
Run and collect statistics
Further Work:
Identify the best interface design, given statistics from simulation
27
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
27
PROJECT BUDGET
• Labor cost - $40/ hr
• Hourly rate - $85.40
• GMU Overhead rate 2.13
• Planned hours - 1,576
• Planned Equipment cost - $400
• Planned Budget = $134,990.00
28
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
28
WORK BREAKDOWN STRUCTURE
29
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
29
CRITICAL PATH TASKS
Current Critical Path Analysis, performed in MS Project, returns the follow tasks as
critical path tasks:
2.3 Problem Statement
3.1 Requirements
4.4 Physical Architecture
5.3 Perform Test Activities
8.2 Final Presentation
8.3 Final Report
30
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
30
Performance Metrics Week 1 through Week 12
31
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
31
PROJECT RISKS
32
Risk #
Foreseeable Risk
Mitigation Strategies
1
Delivery of Equipment
1a. Order equipment asap
2
Data Collection - quality of
equipment, data quality
2a. Careful review of equipment reviews before
ordering
2b. Research data collection techniques
3
Access to raw data
3a. Contact equipment company
3b. Find contacts within Mason community
4
Data analysis timeline driven
by data collection/
equipment
4a. Develop test plan in line with system
architecture
4b. Closely monitor progress towards project
completion.
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
32
QUESTIONS?
Current System:
Future System:
Motion Joystick
Requires Physical
Manipulation of
input device
33
No Physical
User Input
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
33
BACKUP SLIDES
34
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
34
References
[1] "Prevalence of Paralysis." Christopher & Dana Reeve Foundation. The Reeve Foundation Paralysis Resource Center, n.d. Web. 19
Nov. 2015.
[2] "Human Factors and Medical Devices." U.S. Food and Drug Administration. U.S. Food and Drug Administration, n.d. Web. 19 Nov.
2015.
[3] "Care-Providing Robot FRIEND." Institute of Automation. University of Bremen, n.d. Web. 19 Nov. 2015.
[4] "Computers and Robots: Decision-Makers in an Automated World." Computers and Robots DecisionMakers in an Automated World.
University of Stanford, n.d. Web. 19 Nov. 2015.
[5] "Care-O-bot 3." Fraunhofer Institute for Manufacturing Engineering and Automation. Fraunhofer Institute, n.d. Web. 19 Nov. 2015.
[6] "Brain Cells Chat, Even Without a Synapse." Science Magazine. AAAS, n.d. Web. 19 Nov. 2015.
[7]"Parts of Central Nervous System." , Control and Coordination, Science Help. Tutorvista, n.d. Web. 19 Nov. 2015.
[8] "A Closer Look at EEG." Epilepsy Society. Epilepsy Society, n.d. Web. 19 Nov. 2015.
[9] "YouBot." YouBot Store. Kuka, n.d. Web. 19 Nov. 2015.
[10] "Emotiv EPOC / EPOC+." Emotiv Epoc. Emotiv, n.d. Web. 19 Nov. 2015.
[11] "Quantitative EEG and Event-Related Potentials." Neuronetrix. COGNISION , n.d. Web. 19 Nov. 2015.
[12] T. Pierce, T. Watson, J. King, S. Kelly and K. Pribram, 'Age Differences in Factor Analysis of EEG', Brain Topography, vol. 16, no.
1, pp. 19-27, 2003.
35
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
35
AGENDA
•
•
•
•
•
•
•
36
Motivation
Problem Statement
EEG Context
Stakeholders and Gap Analysis
CONOPS
CONOPS Validation
Project Management
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
36
EEG TERMINOLOGY
Signals - The electrical activity that travels through a user’s
brain
Synapses - Spaces between neurons that conduct the electrical
activity in the brain
Noise - General term for unwanted and, in general, unknown
modifications that a signal may suffer during capture,
storage, transmission, processing, or conversion
[6] AAAS, Brain and Behavior
Event-Related Potential - electrophysiological response to a
stimulus
User command - The instruction a user gives to perform an action (user signal to EEG)
Input Command - A collection of steps the end-device will perform in order to execute a
single user command (digital signals to end-device)
37
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
37
PHYSIOLOGY OF THE BRAIN
Human Brain
- Comprised of
100,000,000,000 neurons
- Neurons connect via
synapses
- When thought occurs,
neurons generate spikes
of electrical activity
[7] Canadian Institutes of Health Research, Institutes of Neurological, Mental Health and Addiction
38
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
38
ELECTROENCEPHALOGRAHY (EEG)
• Offers a non-invasive method to detect electrical activity by using electrodes to
measure the electrical pulses along the scalp to ultimately graph these impulses
• Predominantly used in medical field for sleeping/brain abnormalities and
detection, stress evaluation, and prosthetics
• Event related potentials (ERP)
• Correspond to a brain response related to a sensory, cognitive or motor event
• The key to using EEG as a control method is to detect the desired ERP from
other ERPs (noise) and map it to a command
• EEG is not widely used as a control method due to poor signal quality from being
outside of the skull. Technological advances are improving quality.
39
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
39
How the EEG Hands-Free System Works
1) When a user thinks, electrical pulses fire within synapses in lobes of the brain specific to
that “thought” - user command
2) The EEG headset reads these signals as voltage and generates a graph indicating the
intensity and pattern of the electrical signals (The same stimuli or thought should produce
roughly the same EEG patterns when repeated)
3) These graphs will then be analyzed and chosen patterns will be stored in the database with
it’s corresponding thought or stimulus
4) These selected patterns will then be mapped to varying device actions through a system
that
this project will create - input command
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
40
EEG receives
signals and captures
them in the form of
graphs
14
Sensors
Raw signals are
stored in database and
inputted into the
system
EEG raw data stream
[8] A Closer Look at EEG, Epilepsy Society
System filters out
noise and converts
signals to digital
format
System sends digital
signals to library to be
matched to a command
System outputs
corresponding
command to
simulator
User concentrates
on a trained user
command
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
41
PATTERN LIBRARY BLOCK DIAGRAM
42
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
42
OPERATIONAL BLOCK DIAGRAM
43
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
43
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
44
EEG SIGNAL PROCESSING
• The EEG signal will be composed of 14 continuous and numerical data streams, one
from each of the EEG.
• General steps to preprocess the signal:
1. High pass filter to remove low frequency noise
2. Use a window function to group a variable length interval of data such as the Hann or
Hamming window function and eliminate edge artifacts
3. Fast Fourier Transform
4. Convert the imaginary part of any complex numbers into amplitude values
• Use a machine learning approach such as neural networks to build a learning model,
then continuously test in real time to measure accuracy
45
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
45
OPTIMIZING EEG Event-Related Potentials
Goal: Determine largest limiting factor in EEG Control System reliability
• Use simulation to examining the effects of different variables on
detection rate and reliability of ERPs such as:
• Optimal training procedures or increasing training time
• Use of different machine learning approaches to improve detection
• Tentative input commands to be detected:
• 6 directional commands for positive and negative displacement along each
of the x, y, z axes
• 1 toggle command for switching platform control vs arm control
• May need to simplify the number of different commands to reduce user
complexity
46
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
46
SIMULATION REQUIREMENTS
S.0.1 Virtual Robot shall accept input from HFCS.
S.0.1.1 Virtual Robot model shall contain a robot with 2D movement capability
S.0.1.2 Virtual Robot model shall contain a robot capable of grasping and
relocating
S.0.1.3 Virtual Robot model shall contain an object to be relocated
S.0.2 Simulation shall accept EEG ERPs from an input device
S.0.2.1 Simulation shall respond to a detected ERP in time < 2 seconds
S.0.2.2 Simulation shall map ERPs to input commands and interface with VREP
S.0.2.3 Simulation should detect and respond to 2+ simultaneous ERP
S.0.3 Virtual robot shall employ automated collision avoidance.
47
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
47
EPOC Cognitive Suite
1) Create user account
2) Train neurological signal to a basic motion
3) Repeat thought to perform signal
4) Map signal to another vehicle motion
48
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad
Sungkar
Source:
Emotiv
EPOC
48
EEG Headset Alternatives
Standard EPOC
• 14 EEG channels and two references for accurate spatial resolution
• High performance wireless device
• iOS and Android compatible
EPOC+
• 9 axis-inertial motion sensors, Bluetooth capabilities, additional applications are
enabled
Raw Data Add-on
• Includes EEG firmware that allows the raw EEG data stream and marker
events in TestBench software
49
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
49
PROJECT PLANNING, detailed
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
50
Statement of Work
Objectives:
●
●
●
●
●
Subset of brain signals mapped to the specific thought which generated the signal
Documented process to identify and map new brain signals
Increase value of a hands-free application
Quality deliverables and products produced
Improved realization of hands-free control systems
Scope
●
●
●
●
●
●
●
●
51
Project Management
Documentation
Data Collection & Analysis Process
Test Plan & Criteria
Delivery of a Prototype
Test Results
Utility Analysis
Plan for future expansion
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
51
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
52
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
53
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
54
54
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
55
55
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
56
Brainwaves
Neural oscillations are rhythmic or repetitive neural activities in the central nervous system. Neural tissue generate oscillations through
neuron interactions.
A large number of neurons activating for a particular neural computation is called a neural ensemble.
Neural oscillations can be categorized into 5 main frequencies
• Beta (14-40Hz) - Waking consciousness
• Alpha (7.5-14Hz) - Conscious relaxation
• Theta (4-7.5Hz) - Sleeping and light meditation
• Delta (0.5-4Hz) – Deep sleep
• Gamma (above 40Hz) – Insight
• Only recently discovered
57
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
57
http://neuronetrix.com/technology-i-36.html
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
58
58
Age
• A study conducted by Thomas W. Pierce et. al suggested that
age has an effect on EEG
• Results showed that electrode groupings were higher in older
adults than younger adults
• Older adults had more electrode locations that did not load
than the younger adults
59
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
59
[1]T. Pierce, T. Watson, J. King, S. Kelly and K. Pribram, 'Age Differences in Factor
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Analysis of EEG', Brain Topography, vol. 16, no. 1, pp. 19-27, 2003.
60
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
60
Gender
• A study by Corsi-Cabrera et. al suggested differences in the
brain waves between male and female
• Men showed higher beta power, women showed higher alpha
power
• The alpha waves of men decreased during analytic,spatial,
and mixed processing, while women decreased significantly
only in analytic and mixed processing
61
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
61
Interface Diagram
DESIGN OF A HANDS FREE CONTROL SYSTEM FOR DEVICE MANIPULATION
Kassidy Kenney, Angelo Huan, Kimberly Harrington, Muhammad Sungkar
62