Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
8-2020
Abstract
For wheelchair users, social participation and physical mobility play a significant part in determining their mental health and quality of life outcomes. However, little is known about how wheelchair users move about and engage in social interactions within their life-spaces. In this project, we investigate the social participation performance of the wheelchair users based on a combination of geolocational and lifestyle survey data collected over a period of three months. This paper adopts a multi-variate approach combining geolocational travel patterns and various factors such as independence, willingness and self-perception to provide multi-faceted analysis to their lifestyles. We provide profiles of wheelchair users by combining these factors in an empirical analysis. With our users' geolocational data, we can demonstrate the influence of other factors on wheelchair users' social participation performance with regards to life-space mobility.
Keywords
Social participation, geospatial, mobility pattern, data analytics, social insights
Discipline
Computer Engineering | Databases and Information Systems
Research Areas
Data Science and Engineering
Publication
Proceedings of the 16th International Conference on International Conference on Automation Science and Engineering (CASE), Hong Kong, 2020 August 20-21
First Page
1
Last Page
6
Identifier
10.1109/CASE48305.2020.9216793
Publisher
IEEE
City or Country
Hong Kong
Citation
1
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.