16-11-2010, 04:32 PM
SYSTEM FOR ASSISTED MOBILITY USING EYE MOVEMENTS BASED ON ELECTROOCULOGRAPHY
PRESENTED BY:
SANITHA.K
S7 AEI
College Of Engineering, Trivandrum
2007-11 Batch
PRESENTED BY:
SANITHA.K
S7 AEI
College Of Engineering, Trivandrum
2007-11 Batch
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CONTENTS
INTRODUCTION
ELECTROOCULOGRAPHY
EYE MODEL BASED ON EOG
GUIDANCE OF A WHEELCHAIR
VARIOUS GUIDANCE STRATEGIES
GUIDANCE CHARACTERISTICS
EOG Vs EEG
CONCLUSION
INTRODUCTION
EOG is a method of sensing eye movement
Based on recording the standing corneal-retinal potential
The potential can be considered as a steady electric dipole
With a negative pole at fundus and positive pole at the cornea
The EOG value varies from 50 to 3500 microvolt
Factors Effecting EOG
EOG
The EOG is captured by by five electrodes placed around the eye
D-E electrodes are used to detect the horizontal movement
B-C electrodes are used to detect vertical movement
A is the reference electrode placed
on the forehead
EYE MODEL BASED ON EOG
Separate saccadic and smooth eye movements and calculate the eye position in the socket
Filter eliminates the effects due to other biopotentials
Security detects when the eyes are closed,whereupon the output is disabled
Detectors detect whether it is saccadic or smooth eye movement
If a saccadic movement is detected position control is used to calculate the position
CONTD…………
The final position is calculated as the sum of the saccadic and smooth movements
The model parameters are adjusted in according with the angle detected,to adapt itself to the possible variations of acquisition conditions
WHEELCHAIR GUIDANCE SCHEME
GUIDANCE OF WHEELCHAIR USING EOG
The EOG signal is recorded by means of Ag-Agcl electrodes
This data is sent to an onboard computer in which they are processed to calculate the eye gaze direction
This serves as the basis for drawing up the control strategy
Controller implements the high level control and generates the linear and angular speed commands of the wheel chair
CONTD…………
The wheelchair kinematics model then transforms these speeds into angular speed for each wheel
These are sent to a low-level control where two close loop speed controls are implemented
GUIDANCE STRATEGIES
The wheelchair can be controlled by various guidance strategies
Direct access guidance
Scanning guidance
Guidance by eye commands
DIRECT ACCESS INTERFACE
INTERFACE OF SCANNING GUIDANCE
GUIDANCE BY EYE COMMANDS
MOVEMENT COMMANDS
UP :The wheelchair moves forward
DOWN:The wheelchair moves backward
RIGHT:The wheelchair moves to the right
LEFT :The wheelchair moves to the left
GUIDANCE CHARACTERISTICS
Guidance strategy
Self confidence of the user
Interface comfort
Comfort for generating the trajectory
Degree of concentration
EOG Vs EEG
EOG signal measurements are much easier than EEG
Higher amplitude than EEG signals
EOG based systems are less expensive,efficient and practical compared with EOG
CONCLUSIONS
An eye model based on EOG is proposed and a study is made of its ability to determine the eye position within socket
It is also possible to codify ocular actions as commands and apply them to mobility
Presented a control system that allows the handicapped ,especially those with only eye motor coordination to control a wheelchair
Different strategies of electrooculographic guidance has been commented
REFERENCES
D. G. Evans, R. Drew, and P. Blenkhorn, “Controlling mouse pointerposition using a infrared head-operated joystick,” IEEE Trans. Rehab.Eng., vol. 8, Mar. 2008
Research group of the SIAMO Project, “The SIAMO project: IntegralSystem for Assisted Mobility,” IEEE Robot. Automat. Special Issue inRes. Autonomous Robotic Wheelchair in Europe, 2009
F. Cincotti, D. Mattia, F. Aloise, S. Bufalari, G. Schalk, G. Oriolo,A. Cherubini, M. G. Marciani, and F. Babiloni, “Non-invasivebrain-computer interface system: Towards its application as assistivetechnology,” Brain Res. Bull., vol. 75, no. 6, pp. 796–803, Apr. 15, 2008.
[15] S. P. Levine, J. E. Huggins, S. L. BeMent, R. K. Kushwaha, L. A. Schuh,M. M. Rohde, E. A. Passaro, D. A. Ross, K. V. Elisevich, and B. J. Smith,“A direct brain interface based on event-related potentials,” IEEE Trans.Rehabil. Eng., vol. 8, no. 2, pp. 180–185, Jun. 2000.
[16] S. Venkataramanan, P. Prabhat, S. R. Choudhury, H. B. Nemade, andJ. S. Sahambi, “Biomedical instrumentation based on EOG signal processingand application to a hospital alarm system,” in Proc. IEEE ICISIP,Chennai, India, 2005, pp. 535–540
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