Publication:
Free Text: Vision based interface system for hands free control of an Intelligent Wheelchair.


abstract

BACKGROUND:

Due to the shift of the age structure in today's populations, the necessities for developing the devices or technologies to support them have been increasing. Traditionally, the Wheelchair, including powered and manual ones, is the most popular and important rehabilitation/assistive device for the disabled and the elderly. However, it is still highly restricted especially for severely disabled. As a solution to this, the Intelligent Wheelchairs (IWs) have received considerable attention as mobility aids. The purpose of this work is to develop the IW interface for providing more convenient and efficient interface to the people the disability in their limbs.

METHODS:

This paper proposes an intelligent wheelchair (IW) control system for the people with various disabilities. To facilitate a wide variety of user abilities, the proposed system involves the use of face-inclination and mouth-shape information, where the direction of an IW is determined by the inclination of the user's face, while proceeding and stopping are determined by the shapes of the user's mouth. Our system is composed of electric powered wheelchair, data acquisition board, ultrasonic/infra-red sensors, a PC camera, and Vision system. Then the vision system to analyze user's gestures is performed by three stages: detector, recognizer, and converter. In the detector, the facial region of the intended user is first obtained using Adaboost, thereafter the mouth region is detected based on edge information. The extracted features are sent to the recognizer, which recognizes the face inclination and mouth shape using statistical analysis and K-means clustering, respectively. These recognition results are then delivered to the converter to control the wheelchair.

RESULT & CONCLUSION:

The advantages of the proposed system include 1) accurate recognition of user's intention with minimal user motion and 2) robustness to a cluttered background and the time-varying illumination. To prove these advantages, the proposed system was tested with 34 users in indoor and outdoor environments and the results were compared with those of other systems, then the results showed that the proposed system has superior performance to other systems in terms of speed and accuracy. Therefore, it is proved that proposed system provided a friendly and convenient interface to the severely disabled people.

Related Articles
Shared control strategies for obstacle avoidance tasks in an intelligent wheelchair.
Conf Proc IEEE Eng Med Biol So...
Shared control strategies for obstacle avoidance tasks in an intelligent wheelchair.
Trieu HT, Nguyen HT, Willey K. Conf Proc IEEE Eng Med Biol Soc. 2008; 2008:4254-7.
Towards an intelligent wheelchair system for users with cerebral palsy.
IEEE Trans Neural Syst Rehabil...
Towards an intelligent wheelchair system for users with cerebral palsy.
Montesano L, Díaz M, Bhaskar S, Minguez J. IEEE Trans Neural Syst Rehabil Eng. 2010 Apr; 18(2):193-202. Epub 2010 Jan 12.
Semi-autonomous wheelchair system using stereoscopic cameras.
Conf Proc IEEE Eng Med Biol So...
Semi-autonomous wheelchair system using stereoscopic cameras.
Nguyen JS, Nguyen TH, Nguyen HT. Conf Proc IEEE Eng Med Biol Soc. 2009; 2009:5068-71.
Review Mobility of wheelchair users: a proposed performance assessment framework.
Disabil Rehabil. 2003
Review Mobility of wheelchair users: a proposed performance assessment framework.
Routhier F, Vincent C, Desrosiers J, Nadeau S. Disabil Rehabil. 2003 Jan 7; 25(1):19-34.
Review How many people would benefit from a smart wheelchair?
J Rehabil Res Dev. 2008
Review How many people would benefit from a smart wheelchair?
Simpson RC, LoPresti EF, Cooper RA. J Rehabil Res Dev. 2008; 45(1):53-71.
Neuroengineering tools/applications for bidirectional interfaces, brain-computer interfaces, and neuroprosthetic implants - a review of recent progress.
Front Neuroeng. 2010
Neuroengineering tools/applications for bidirectional interfaces, brain-computer interfaces, and neuroprosthetic implants - a review of recent progress.
Rothschild RM. Front Neuroeng. 2010 Oct 15; 3:112. Epub 2010 Oct 15.