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Transportation Mode Detection Technology to Predict Wheelchair Users' Life Satisfaction in Seoul, South Korea

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Kwanguk KimAuthors Info & Claims

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Volume 8, Issue 1

Article No.: 9, Pages 1 - 20

https://doi.org/10.1145/3643506

Published: 06 March 2024 Publication History

Abstract

Transportation mode detection (TMD) has been proposed as a computational technology to obtain mobility information. However, previous TMD studies mainly focused on improving detection performance and have not investigated the social implications of mobility information. This is the first study to use TMD to predict the life satisfaction of wheelchair users. Our goal is to develop TMD for wheelchair users (wTMD) utilizing smartphone location data and apply it to determine how transportation behaviors affect the life satisfaction of wheelchair users. First, we propose a wTMD technology by collecting a new dataset from wheelchair and non-wheelchair users. Second, we conduct regression analyses on existing in-the-wild dataset of wheelchair users. The result shows that the portion of subways in an individual's travel time is directly connected to wheelchair users' life satisfaction in Seoul, South Korea. We hope our findings are a good example for future social science studies and ultimately help to design wheelchair-friendly urban planning and accessibility.

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Cited By

Hwang SLeng ZOh SKim KPl�tz TKostakos VKay JHoang T(2024)More Data for People with Disabilities! Comparing Data Collection Efforts for Wheelchair Transportation Mode DetectionProceedings of the 2024 ACM International Symposium on Wearable Computers10.1145/3675095.3676617(82-88)Online publication date: 5-Oct-2024
https://dl.acm.org/doi/10.1145/3675095.3676617
Leng ZJung MHwang SOh SZhang LPl�tz TKim KKostakos VKay JHoang T(2024)Emotion Recognition on the Go: Utilizing Wearable IMUs for Personalized Emotion RecognitionCompanion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing10.1145/3675094.3678452(537-544)Online publication date: 5-Oct-2024
https://dl.acm.org/doi/10.1145/3675094.3678452

Index Terms

Transportation Mode Detection Technology to Predict Wheelchair Users' Life Satisfaction in Seoul, South Korea

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cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Volume 8, Issue 1

March 2024

1182 pages

EISSN:2474-9567

DOI:10.1145/3651875

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Published: 06 March 2024

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This work was supported by the National Research Foundation of Korea (NRF) Grant funded by the Korea government [Ministry of Science and ICT(MSIT)

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Hwang SLeng ZOh SKim KPl�tz TKostakos VKay JHoang T(2024)More Data for People with Disabilities! Comparing Data Collection Efforts for Wheelchair Transportation Mode DetectionProceedings of the 2024 ACM International Symposium on Wearable Computers10.1145/3675095.3676617(82-88)Online publication date: 5-Oct-2024
https://dl.acm.org/doi/10.1145/3675095.3676617
Leng ZJung MHwang SOh SZhang LPl�tz TKim KKostakos VKay JHoang T(2024)Emotion Recognition on the Go: Utilizing Wearable IMUs for Personalized Emotion RecognitionCompanion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing10.1145/3675094.3678452(537-544)Online publication date: 5-Oct-2024
https://dl.acm.org/doi/10.1145/3675094.3678452

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