Intelligent system to analyze data about powered wheelchair drivers

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The research presented in this paper creates an intelligent system that collects powered wheelchair users’ driving session data. The intelligent system is based on a Python programming platform. A program is created that will collect data for future analysis. The collected data considers driving session details, the ability of a driver to operate a wheelchair, and the type of input devices used to operate a powered wheelchair. Data is collected on a Raspberry Pi microcomputer and is sent after each session via email. Data is placed in the body of the emails, in an attached file and saved on microcomputer memory. Modifications to the system is made to meet confidentiality and privacy concerns of potential users. Data will be used for future analysis and will be considered as a training data set to teach an intelligent system to predict future path patterns for different wheelchair users. In addition, data will be used to analyze the ability of a user to drive a wheelchair, and monitor users’ development from one session to another, compare the progress of various users with similar disabilities and identify the most appropriate input device for each user and path.
Original languageEnglish
Title of host publicationIntelligent Systems and Applications
Subtitle of host publicationProceedings of the 2020 Intelligent Systems Conference (IntelliSys) Volume 3
EditorsKohei Arai, Supriya Kapoor, Rahul Bhatia
PublisherSpringer
Pages584-593
ISBN (Electronic)978-3-030-55190-2
ISBN (Print)978-3-030-55189-6
DOIs
Publication statusPublished - 25 Aug 2020
EventIntelligent Systems Conference - London, United Kingdom
Duration: 3 Sep 20204 Sep 2020

Publication series

NameAdvances in Intelligent Systems and Computing
PublisherSpringer
Volume1252
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

ConferenceIntelligent Systems Conference
Abbreviated titleIntelliSys 2020
CountryUnited Kingdom
CityLondon
Period3/09/204/09/20

Keywords

  • RCUK
  • EPSRC
  • EP/S005927/1

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