vision

Vision-based hand wheel-chair control

Several studies have shown that people with disabilities benefit substantially from access to a means…

Several studies have shown that people with disabilities benefit substantially from access to a means of independent mobility and assistive technology. Researchers are using technology originally developed for mobile robots to create easier to use wheelchairs. With this kind of technology people with disabilities can gain a degree of independence in performing daily life activities. In this work a computer vision system is presented, able to drive a wheelchair with a minimum number of finger commands. The user hand is detected and segmented with the use of a kinect camera, and fingertips are extracted from depth information, and used as wheelchair commands.

Introduction

Several studies have shown that people with disabilities benefit substantially from access to a means of independent mobility and assistive technology [1], being independent mobility an important aspect of selfesteem [2]. Assistive devices such as powered wheelchairs improve one’s quality of life. While the needs of many individuals with disabilities can be satisfied with traditional manual wheelchairs, some find it difficult to use. To accommodate this population and even other segments, several researchers have used technologies originally developed for mobile robots to create user friendly easier to use wheelchairs and “smart wheelchairs”. Smart wheelchairs typically consist of either a standard power wheelchair to which a computer and a collection of sensors have been added or a mobile robot base to which a seat has been attached [2]. This work presents a simple and effective HCI (human computer interface) giving the user the ability to easily control a robotic wheelchair with a minimum number of finger commands. The main goal consists of giving the user the capability to control it without touching any physical device. For that purpose, a computer vision interface was developed, able to detect fingertips and able to use that information for driving the wheelchair.

To extract the hand and fingertip localization a kinect [3] camera is mounted on the back of the wheelchair pointing down to the user’s hand. Machine vision is a promising sensor technology. With nowadays cameras, smaller than a lot of other sensors, they can be mounted in multiple locations, giving larger sensor coverage. Also, the cost of machine vision hardware has fallen significantly, and the solutions based on computer vision continue to improve.

Paulo Trigueiros
Departamento de Informática Instituto Politécnico do Porto, Portugal

Fernando Ribeiro

Departamento de Electrónica Industrial Universidade do Minho, Guimarães, Portugal

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