Intelligent system to analyze data about powered wheelchair drivers

Malik Haddad; David Sanders; Martin Langner; Mohamad Thabet; Peter Osagie Omoarebun; Alexander Gegov; Nils Bausch; Khaled Giasin

doi:10.1007/978-3-030-55190-2_43

Intelligent system to analyze data about powered wheelchair drivers

Malik Haddad, David Sanders, Martin Langner, Mohamad Thabet, Peter Osagie Omoarebun, Alexander Gegov, Nils Bausch, Khaled Giasin

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

166 Downloads (Pure)

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 language	English
Title of host publication	Intelligent Systems and Applications
Subtitle of host publication	Proceedings of the 2020 Intelligent Systems Conference (IntelliSys) Volume 3
Editors	Kohei Arai, Supriya Kapoor, Rahul Bhatia
Publisher	Springer
Pages	584-593
ISBN (Electronic)	978-3-030-55190-2
ISBN (Print)	978-3-030-55189-6
DOIs	https://doi.org/10.1007/978-3-030-55190-2_43
Publication status	Published - 25 Aug 2020
Event	Intelligent Systems Conference - London, United Kingdom Duration: 3 Sept 2020 → 4 Sept 2020

Publication series

Name	Advances in Intelligent Systems and Computing
Publisher	Springer
Volume	1252
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	Intelligent Systems Conference
Abbreviated title	IntelliSys 2020
Country/Territory	United Kingdom
City	London
Period	3/09/20 → 4/09/20

Keywords

RCUK
EPSRC
EP/S005927/1

Access to Document

10.1007/978-3-030-55190-2_43

Intelligent System to Analyze Data about Powered Wheelchair Drivers
This is a post-peer-review, pre-copyedit version of an article published in Advances in Intelligent Systems and Computing. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-030-55190-2_43.
Accepted author manuscript (Post-print), 853 KB

Project Data EPSRC EP/S005927/1 Case study 1 Session 4
Haddad, M. (Creator) & Sanders, D. (Creator), University of Portsmouth, 13 Feb 2020
DOI: 10.17029/b96cc3d2-3f9a-4cc3-98fa-3099b269feb5
Dataset

File
Project Data EPSRC EP/S005927/1 Case study 1 Session 3
Haddad, M. (Creator) & Sanders, D. (Creator), University of Portsmouth, 13 Feb 2020
DOI: 10.17029/17cabd02-eff4-4722-ac7c-7f60f10a0d19
Dataset

File
Project Data EPSRC EP/S005927/1 Case study 1 Session 1
Haddad, M. (Creator) & Sanders, D. (Creator), University of Portsmouth, 13 Feb 2020
DOI: 10.17029/4b73f2b5-e725-4dda-8325-352093aca84b
Dataset

File
Project Data EPSRC EP/S005927/1 Case study 1 Session 2
Haddad, M. (Creator) & Sanders, D. (Creator), University of Portsmouth, 13 Feb 2020
DOI: 10.17029/4969d7f5-f721-4fbb-a738-7048f087e3e9
Dataset

File

Using artificial intelligence to share control of a powered-wheelchair between a wheelchair user and an intelligent sensor system
Sanders, D., Gegov, A. & Haddad, M.
Engineering and Physical Sciences Research Council
1/11/18 → 1/11/22
Project: Research

File

Cite this

Haddad, M., Sanders, D., Langner, M., Thabet, M., Omoarebun, P. O., Gegov, A., Bausch, N., & Giasin, K. (2020). Intelligent system to analyze data about powered wheelchair drivers. In K. Arai, S. Kapoor, & R. Bhatia (Eds.), Intelligent Systems and Applications: Proceedings of the 2020 Intelligent Systems Conference (IntelliSys) Volume 3 (pp. 584-593). (Advances in Intelligent Systems and Computing; Vol. 1252). Springer. https://doi.org/10.1007/978-3-030-55190-2_43

Haddad, Malik ; Sanders, David ; Langner, Martin et al. / Intelligent system to analyze data about powered wheelchair drivers. Intelligent Systems and Applications: Proceedings of the 2020 Intelligent Systems Conference (IntelliSys) Volume 3. editor / Kohei Arai ; Supriya Kapoor ; Rahul Bhatia. Springer, 2020. pp. 584-593 (Advances in Intelligent Systems and Computing).

@inproceedings{6c0f27a57f674741b27561a76c430781,

title = "Intelligent system to analyze data about powered wheelchair drivers",

abstract = "The research presented in this paper creates an intelligent system that collects powered wheelchair users{\textquoteright} 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{\textquoteright} 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.",

keywords = "RCUK, EPSRC, EP/S005927/1",

author = "Malik Haddad and David Sanders and Martin Langner and Mohamad Thabet and Omoarebun, {Peter Osagie} and Alexander Gegov and Nils Bausch and Khaled Giasin",

year = "2020",

month = aug,

day = "25",

doi = "10.1007/978-3-030-55190-2_43",

language = "English",

isbn = "978-3-030-55189-6",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer",

pages = "584--593",

editor = "Kohei Arai and Supriya Kapoor and Rahul Bhatia",

booktitle = "Intelligent Systems and Applications",

note = "Intelligent Systems Conference, IntelliSys 2020 ; Conference date: 03-09-2020 Through 04-09-2020",

}

Haddad, M, Sanders, D, Langner, M, Thabet, M, Omoarebun, PO, Gegov, A, Bausch, N & Giasin, K 2020, Intelligent system to analyze data about powered wheelchair drivers. in K Arai, S Kapoor & R Bhatia (eds), Intelligent Systems and Applications: Proceedings of the 2020 Intelligent Systems Conference (IntelliSys) Volume 3. Advances in Intelligent Systems and Computing, vol. 1252, Springer, pp. 584-593, Intelligent Systems Conference, London, United Kingdom, 3/09/20. https://doi.org/10.1007/978-3-030-55190-2_43

Intelligent system to analyze data about powered wheelchair drivers. / Haddad, Malik; Sanders, David; Langner, Martin et al.
Intelligent Systems and Applications: Proceedings of the 2020 Intelligent Systems Conference (IntelliSys) Volume 3. ed. / Kohei Arai; Supriya Kapoor; Rahul Bhatia. Springer, 2020. p. 584-593 (Advances in Intelligent Systems and Computing; Vol. 1252).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Intelligent system to analyze data about powered wheelchair drivers

AU - Haddad, Malik

AU - Sanders, David

AU - Langner, Martin

AU - Thabet, Mohamad

AU - Omoarebun, Peter Osagie

AU - Gegov, Alexander

AU - Bausch, Nils

AU - Giasin, Khaled

PY - 2020/8/25

Y1 - 2020/8/25

N2 - 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.

AB - 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.

KW - RCUK

KW - EPSRC

KW - EP/S005927/1

U2 - 10.1007/978-3-030-55190-2_43

DO - 10.1007/978-3-030-55190-2_43

M3 - Conference contribution

SN - 978-3-030-55189-6

T3 - Advances in Intelligent Systems and Computing

SP - 584

EP - 593

BT - Intelligent Systems and Applications

A2 - Arai, Kohei

A2 - Kapoor, Supriya

A2 - Bhatia, Rahul

PB - Springer

T2 - Intelligent Systems Conference

Y2 - 3 September 2020 through 4 September 2020

ER -

Haddad M, Sanders D, Langner M, Thabet M, Omoarebun PO, Gegov A et al. Intelligent system to analyze data about powered wheelchair drivers. In Arai K, Kapoor S, Bhatia R, editors, Intelligent Systems and Applications: Proceedings of the 2020 Intelligent Systems Conference (IntelliSys) Volume 3. Springer. 2020. p. 584-593. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-030-55190-2_43

Intelligent system to analyze data about powered wheelchair drivers

Abstract

Publication series

Conference

Keywords

Access to Document

Fingerprint

Datasets

Project Data EPSRC EP/S005927/1 Case study 1 Session 4

Project Data EPSRC EP/S005927/1 Case study 1 Session 3

Project Data EPSRC EP/S005927/1 Case study 1 Session 1

Project Data EPSRC EP/S005927/1 Case study 1 Session 2

Projects

Using artificial intelligence to share control of a powered-wheelchair between a wheelchair user and an intelligent sensor system

Cite this