Authors:
Malik Haddad
1
;
David Sanders
2
;
Giles Tewkesbury
2
;
Martin langner
3
;
Sanar Muhyaddin
4
and
Mohammed Ibrahim
5
Affiliations:
1
Northeastern University – London, St. Katharine’s Way, London, UK
;
2
Faculty of Technology, University of Portsmouth, Anglesea Road, Portsmouth, UK
;
3
Chailey Heritage Foundation, North Chailey, Lewes, UK
;
4
North Wales Business School, Wrexham Glyndwr University, Wrexham, UK
;
5
Ministry of Communications, Abo Nawas Street, Bagdad, Iraq
Keyword(s):
Computer Vision, Powered Wheelchair, Assistive Technology.
Abstract:
This paper presents a novel approach to driving smart wheelchairs using Computer Vision algorithms. When a user makes a movement, the new approach identifies that movement and utilises it to control a smart wheelchair. An electronic circuit is created to connect a camera, a set of relays and a microcomputer. A programme was created using Python programming language. The program detects the movement of the user. Three algorithms for Computer-Vision algorithms are used: Background Subtraction, Python Imaging Library and Open Source Computer Vision (OpenCV) algorithm. The camera was pointed towards the user a body part used for operating the smart wheelchair. The new approach will detect and identify the movement, the programme will analyse the movement and control the smart wheelchair accordingly. Two User Interfaces were built: a simple User Interface to control the architecture and a technical interface to adjust sensitivity, movement detection settings and operation mode. Testing re
vealed that OpenCV produced the highest sensitivity and accuracy compared to the other algorithms considered in this paper. The new approach effectively identified voluntary movements and interpreted movements to commands used to drive a smart wheelchair. Future clinical tests will be performed at Chailey Heritage Foundation.
(More)