Literature DB >> 10609632

The NavChair Assistive Wheelchair Navigation System.

S P Levine1, D A Bell, L A Jaros, R C Simpson, Y Koren, J Borenstein.   

Abstract

The NavChair Assistive Wheelchair Navigation System [19] is being developed to reduce the cognitive and physical requirements of operating a power wheelchair for people with wide ranging impairments that limit their access to powered mobility. The NavChair is based on a commercial wheelchair system with the addition of a DOS-based computer system, ultrasonic sensors, and an interface module interposed between the joystick and power module of the wheelchair. The obstacle avoidance routines used by the NavChair in conjunction with the ultrasonic sensors are modifications of methods originally used in mobile robotics research. The NavChair currently employs three operating modes: general obstacle avoidance, door passage, and automatic wall following. Results from performance testing of these three operating modes demonstrate their functionality. In additional to advancing the technology of smart wheelchairs, the NavChair has application to the development and testing of "shared control" systems where a human and machine share control of a system and the machine can automatically adapt to human behaviors.

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Mesh:

Year:  1999        PMID: 10609632     DOI: 10.1109/86.808948

Source DB:  PubMed          Journal:  IEEE Trans Rehabil Eng        ISSN: 1063-6528


  10 in total

1.  Upper Body-Based Power Wheelchair Control Interface for Individuals With Tetraplegia.

Authors:  Elias B Thorp; Farnaz Abdollahi; David Chen; Ali Farshchiansadegh; Mei-Hua Lee; Jessica P Pedersen; Camilla Pierella; Elliot J Roth; Ismael Seanez Gonzalez; Ferdinando A Mussa-Ivaldi
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2015-06-01       Impact factor: 3.802

2.  Vision based interface system for hands free control of an Intelligent Wheelchair.

Authors:  Jin Sun Ju; Yunhee Shin; Eun Yi Kim
Journal:  J Neuroeng Rehabil       Date:  2009-08-06       Impact factor: 4.262

3.  3-D Object Recognition of a Robotic Navigation Aid for the Visually Impaired.

Authors:  Cang Ye; Xiangfei Qian
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2017-09-01       Impact factor: 3.802

4.  Combining Brain-Computer Interfaces and Assistive Technologies: State-of-the-Art and Challenges.

Authors:  J D R Millán; R Rupp; G R Müller-Putz; R Murray-Smith; C Giugliemma; M Tangermann; C Vidaurre; F Cincotti; A Kübler; R Leeb; C Neuper; K-R Müller; D Mattia
Journal:  Front Neurosci       Date:  2010-09-07       Impact factor: 4.677

5.  Wheelchair Navigation System for Disabled and Elderly People.

Authors:  Eun Yi Kim
Journal:  Sensors (Basel)       Date:  2016-10-28       Impact factor: 3.576

6.  Hazardous Object Detection by Using Kinect Sensor in a Handle-Type Electric Wheelchair.

Authors:  Jeyeon Kim; Takaaki Hasegawa; Yuta Sakamoto
Journal:  Sensors (Basel)       Date:  2017-12-18       Impact factor: 3.576

7.  SWADAPT1: assessment of an electric wheelchair-driving robotic module in standardized circuits: a prospective, controlled repeated measure design pilot study.

Authors:  Emilie Leblong; Bastien Fraudet; Louise Devigne; Marie Babel; François Pasteau; Benoit Nicolas; Philippe Gallien
Journal:  J Neuroeng Rehabil       Date:  2021-09-16       Impact factor: 4.262

8.  Design and validation of an intelligent wheelchair towards a clinically-functional outcome.

Authors:  Patrice Boucher; Amin Atrash; Sousso Kelouwani; Wormser Honoré; Hai Nguyen; Julien Villemure; François Routhier; Paul Cohen; Louise Demers; Robert Forget; Joelle Pineau
Journal:  J Neuroeng Rehabil       Date:  2013-06-17       Impact factor: 4.262

9.  A Driving Behaviour Model of Electrical Wheelchair Users.

Authors:  S O Onyango; Y Hamam; K Djouani; B Daachi; N Steyn
Journal:  Comput Intell Neurosci       Date:  2016-04-11

10.  Development of a New Intelligent Joystick for People with Reduced Mobility.

Authors:  Makrem Mrabet; Yassine Rabhi; Farhat Fnaiech
Journal:  Appl Bionics Biomech       Date:  2018-03-22       Impact factor: 1.781

  10 in total

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