Initial results from using an intelligent system to analyse powered wheelchair users’ data

Haddad, Malik, Sanders, David, Langner, Martin, Omoarebun, Peter, Thabet, Mohamad and Gegov, Alexandar (2020) Initial results from using an intelligent system to analyse powered wheelchair users’ data. In: 2020 IEEE 10th International Conference on Intelligent Systems (IS).

Abstract

Research in this paper presents a technique to collect powered wheelchair users' data using an intelligent system. Python programming language is used to create a program that will collect data for future analysis. The collected data considers driving session details, medication administered that can affect driving ability, and the type of input devices used to control 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 and in an attached file. Data will be used for future analysis and will be considered as a training data set to train an intelligent system to predict future route patterns for different wheelchair users. In addition, data will be used to analyze the ability of a user to operate their wheelchair, and monitor users' progress from one session to another, compare the progress of different users with the same type of disability and identify the most suitable input device for each user and route.

Item Type:	Conference or Workshop Item (Paper)
Disciplines:	Computing, Maths, Engineering and Natural Sciences > Computer Science Computing, Maths, Engineering and Natural Sciences > Data Science & AI
Depositing User:	Malik Haddad
Date Deposited:	21 Dec 2023 11:34
Last Modified:	21 Dec 2023 11:34
URI:	https://nul.repository.guildhe.ac.uk/id/eprint/1402

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