A Survey of Technologies Facilitating Home and Community-Based Stroke Rehabilitation

Abstract

Stroke is a cardiovascular and cerebrovascular disease that affects the aged population at a high rate. Patients’ functional disabilities can be reduced with effective rehabilitation training. However, due to a lack of hospital resources and a social yearning for family contact, patients frequently discontinue rehabilitation training sessions and return home to their local community. Such a shift emphasizes the value of home and community-based rehabilitation, where patients can perform daily training with remote support from therapists. In this survey, the technologies that assist stroke rehabilitation will be discussed in following aspects: (1) technologies for home-based stroke rehabilitation; (2) technologies for community-based stroke rehabilitation; (3) technologies for therapist’s engagement in remote rehabilitation. A comprehensive overview of technologies that support home and community-based stroke rehabilitation was presented, as well as insights into future research themes.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research was supported by the Shanghai Municipal Science and Technology Major Project [2021SHZDZX0100] and the Fundamental Research Funds for the Central Universities. We extend our gratitude to the anonymous peer reviewers for their helpful comments on an earlier version of the paper.

Notes on contributors

Xiaohua Sun

Xiaohua Sun is a professor at the College of Design and Innovation, Tongji University, China. She received her PhD degree in Design and Computation from Massachusetts Institute of Technology in 2007. Her research interests include human-robot interaction (HRI), smart healthcare and rehabilitation, and extended reality (XR), etc.

Jiayan Ding

Jiayan Ding is a master’s student at the College of Design and Innovation, Tongji University. Her main research interest is interaction design for smart healthcare, rehabilitation and elderly nursing.

Yixuan Dong

Yixuan Dong is a graduate student at the College of Design and Innovation, Tongji University. Her main research interest lies in the interaction design of stroke rehabilitation in the home setting.

Xinda Ma

Xinda Ma is a graduate student in Information Science at Cornell University. She is currently working at Center for Digital Innovation, Tongji University. Her research interest is in human computer interaction, inclusive design, etc. She received her BA from New York University majoring in Interactive Media Arts and Computer Science.

Ran Wang

Ran Wang is a master’s student for Interaction Design at the College of Design and Innovation, Tongji University. Her research interests include smart healthcare and post-stroke remote rehabilitation. She received her BM degree in Clinical Medicine from Tongji University in 2020.

Kailun Jin

Kailun Jin is a master’s student majoring in AI and Data Design at the College of Design and Innovation, Tongji University. His research fields include deep learning supported speech therapy, human-computer interaction (HCI), data visualization and pre-trained language modeling.

Hexin Zhang

Hexin Zhang is a graduate student at the College of Design and Innovation, Tongji University. His research interests lie in human-computer interaction and information visualization, especially their clinical application.

Yiwen Zhang

Yiwen Zhang is a PhD Candidate at the College of Design and Innovation, Tongji University. His research is in the field of human-intelligent system collaboration and interaction design in automated systems. He received his MEng degree in industrial design engineering from Shandong University.