Social participation performance of wheelchair users using clustering and geolocational sensor's data

• Main Authors: YIN, Yukun, TAN, Kar Way
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Social participation; geospatial; mobility pattern; data analytics; social insights; Computer Engineering; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/5499; https://ink.library.smu.edu.sg/context/sis_research/article/6502/viewcontent/CASE20_0264_FI.pdf
• Institution: Singapore Management University

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.