Low cost and High Efficient Model for Multi Control Wheelchair Based on an Embedded System
|International Journal of Electronics and Communication Engineering|
|© 2019 by SSRG - IJECE Journal|
|Volume 6 Issue 5|
|Year of Publication : 2019|
|Authors : Nashaat M. Hussain Hassan|
How to Cite?
Nashaat M. Hussain Hassan, "Low cost and High Efficient Model for Multi Control Wheelchair Based on an Embedded System," SSRG International Journal of Electronics and Communication Engineering, vol. 6, no. 5, pp. 22-34, 2019. Crossref, https://doi.org/10.14445/23488549/IJECE-V6I5P105
Multi Control wheelchair device revolves around one main idea is helping people with special needs to have a better independent life. A hardware implementation to a modification of a self-propelled wheelchair is presented in this paper. That modification is to move it electronically and with multi control. That to help people with special needs in different situations rely on themselves only to move from one place to another through the use of three different ways to control the chair. Each control is accordance to the situation of those with special needs. The first control is aimed to those who suffering of the paralysis those cannot move their feet. That control allows them to control the movement of the chair by their hands using the joystick easily. The second control is aimed at those who suffering from paralysis of the quadrilateral and cannot move any of the limbs. That control allows them to control the movement of the chair using voice commands. The third control is aimed at those who suffering from the inability to move any of the limbs and also cannot speak like those suffering from Amyotrophic lateral sclerosis ―ALS‖. That control allows them to control the chair by moving the eyelids "blinks". The chair also has a fourth control, but is not aimed to those with special needs, but it aimed to those responsible for them. While the occurrence of whatever prevents who with special needs from the controlling by himself in the chair. This control allows the responsible to control the chair through the smart phone. The chair also has a high safety system so that the chair will automatically stop in case of any hurdle of about fifty centimeters by using ultrasonic waves. Our smart system is designed and developed to save cost, time, accuracy, energy and dependence on the others. Our system is based on using an embedded system as part of the complete device including electrical hardware component and mechanical parts. Several test results of the multi control systems have been monitored to verify the efficiency of the proposed device.
wheelchair; electric wheelchair; joystick control; sound control; blinks control.
 Thomas R, Christian M, and Tim L. Controlling an Automated Wheelchair via Joystick/Head-Joystick Supported by Smart Driving Assistance. 2009 IEEE 11th International Conference on Rehabilitation Robotics Kyoto International Conference Center, Japan, pp. 743-748, June 23-26, 2009.
 Alonso A. Alonso, Ramón de la Rosa, Albano C. A Control System for Robots and Wheelchairs: Its Application for People with Severe Motor Disability. Mobile Robots – Current Trends, pp. 105-127, 26, October, 2011
 Yassine R , Makrem M, and Farhat F. Intelligent Control Wheelchair Using a New Visual Joystick. Hindawi, Journal of Healthcare Engineering, pp. 1-21, February 2018
 Azam, G., and M. T. Islam. Design and Fabrication of a Voice Controlled Wheelchair for Physically Disabled People‖ International Conference on Physics Sustainable Development & Technology, pp 80-90, 2015 .
Andrej Š, Anton Z. Speech-controlled cloud-based wheelchair platform for disabled persons. Journal of Microprocessors &Microsystems, Elsevier Science Publishers B. V. Amsterdam, Volume 39 Issue 8, November 2015, Pages 819-828.
 Klabi I., Masmoudi M.S., Masmoudi M., Advanced user interfaces for intelligent wheelchair system, 1st IEEE Conference on Advanced
Technologies for Signal and Image Processing, Tunisia, pp.130-136,2014.
 Deepak K. Lodhi, Prakshi V, Addala. V, and Prashant S. Smart Electronic Wheelchair Using Arduino and Bluetooth Module. International
Journal of Computer Science and Mobile Computing, Vol. 5, Issue. 5, May 2016, pg.433 – 438.
 Ritika P, Narender K.. Android Mobile Phone Controlled Bluetooth Robot Using 8051 Microcontroller. International Journal of Scientific
Engineering and Research, Volume 2, pp. 14-17, July 2014.
 Nikhil R. Folane , R. M. Autee,―EEG Based Brain Controlled Wheelchair for Physically Challenged People‖,International Journal of
Innovative Research in Computer and Communication Engineering , pp. 134-137, January 2016.
 Arjon T. Member, Demi S, Mardi T, Endra J. EEG-based brain-controlled wheelchair with four different stimuli frequencies. Internetworking
Indonesia Journal, pp. 64-69, 21 March 2017.
 A. Turnip & M. Siahaan. Adaptive Principal Component Analysis based Recursive Least Squares for Artifact Removal of EEG Signals. Advanced
Science Letters, pp. 2034-2037, October 2014.
 A. Turnip & K. S. Hong. Classifying mental activities from EEGP300 signals using adaptive neural network. Int. J. Innov. Comp. Inf. Control,
 M. Kh. Hazrati and A. Erfanian. An online EEGbased brain-computer interface for controlling hand grasp using an adaptive probabilistic neural network. Medical Engineering & Physics, pp. 730-739, 2010 .
 Zisu Ding. Motor Comparison & Selection For Electric Jet Ski. School of Electrical and Electronic Engineering, University of Western Australia, pp.16-22, October 26th 2015.
 Hibbeler, R. C, ―Engineering Mechanics‖, Pearson, Prentice Hall, p.393.
 Battery Technology for Data Centers and Network Rooms: U.S. Fire Safety Codes Related to Lead Acid Batteries, Schneider Electric – Data
Center Science Center, P31, 2012.
 Cytron Technologies ―MDD10A Dual Channel 10A DC Motor Driver.pdf‖, User's Manual, pp.1-11, June 2017.
 Elegoo,―THE MOST COMPLETE STARTER KIT TUTORIAL FOR MEGA2560‖, Article available at www.elegoo.com , pp.32-42, 2017.
 Ali A. Abed ―Design of Voice Controlled Smart Wheelchair‖, International Journal of Computer Applications, Volume 131 – No.1, pp. 32-38,
 Sim Kok Swee, Kho Desmond Teck Kiang and Lim Zheng You ―EEG Controlled Wheelchair‖, MATEC Web of Conferences, Malaysia, published
by EDP Sciences, pp. 1-9, 2016
 Deepak K. Lodhi , Prakshi V, Addala V , Prashant S , Ritakshi G , Manoj K.. Pandey & Rajat B. Smart Electronic Wheelchair Using Arduino and
Bluetooth Module. International Journal of Computer Science and Mobile Computing, Vol.5 Issue.5, pg. 433-438, May- 2016.
 M. Jain, S. Puri, S. Unishree. Eyeball Motion Controlled Wheelchair Using IR Sensors. International Journal of Computer, Electrical, Automation, Control and Information Engineering Vol:9, No:4, pp. 1012-1015, 2015.