Usability Studies of an Egocentric Vision-Based Robotic Wheelchair

Author:

Kutbi Mohammed1,Du Xiaoxue2,Chang Yizhe3,Sun Bo4,Agadakos Nikolaos5,Li Haoxiang6,Hua Gang6,Mordohai Philippos4

Affiliation:

1. Saudi Electronic University, Saudi Arabia

2. Teachers College, Columbia University, New York, NY, USA

3. California State Polytechnic University, Pomona, California, USA

4. Stevens Institute of Technology, Castle Point on Hudson, Hoboken, NJ, USA

5. University of Illinois at Chicago, IL, USA

6. Wormpex AI Research, Bellevue, WA, USA

Abstract

Motivated by the need to improve the quality of life for the elderly and disabled individuals who rely on wheelchairs for mobility, and who may have limited or no hand functionality at all, we propose an egocentric computer vision based co-robot wheelchair to enhance their mobility without hand usage. The robot is built using a commercially available powered wheelchair modified to be controlled by head motion. Head motion is measured by tracking an egocentric camera mounted on the user’s head and faces outward. Compared with previous approaches to hands-free mobility, our system provides a more natural human robot interface because it enables the user to control the speed and direction of motion in a continuous fashion, as opposed to providing a small number of discrete commands. This article presents three usability studies, which were conducted on 37 subjects. The first two usability studies focus on comparing the proposed control method with existing solutions while the third study was conducted to assess the effectiveness of training subjects to operate the wheelchair over several sessions. A limitation of our studies is that they have been conducted with healthy participants. Our findings, however, pave the way for further studies with subjects with disabilities.

Funder

National Institute of Nursing Research of the National Institutes of Health

National Science Foundation

Publisher

Association for Computing Machinery (ACM)

Subject

Artificial Intelligence,Human-Computer Interaction

Cited by 18 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3