@inproceedings{3c6f7be69d7e4fe889b6dab7c4654246,
title = "ARMove: A smartphone augmented reality exergaming system for upper and lower extremities stroke rehabilitation: Demo abstract",
abstract = "Effective at-home rehabilitation of both upper and lower extremities is important for regaining proficiency in activities of daily living (ADLs) post-stroke. We introduce ARMove, a smartphone augmented reality (AR) exergaming system for upper and lower extremities stroke rehabilitation. The AR technology facilitates exergaming that utilizes full range of motion in real-world spatial environments, while creating interesting graphics to engage users in gamified environments. ARMove's novelty comes from its multifaceted rehabilitation of both upper and lower extremities. Furthermore, ARMove provides simultaneous training of fine and gross movements; it also considers bilateral training, preparing users for ADLs such as using computers or playing sports. Additionally, our utilization of smartphone embedded vision sensors and mobile computing give our system scalability, with potential for ubiquitous deployment.",
keywords = "Augmented reality, Embedded sensor system, Exergame, Mobile computing, Rehabilitation, Smart health, Stroke",
author = "Gabriel Guo and Joshua Segal and Hanbin Zhang and Wenyao Xu",
note = "Publisher Copyright: {\textcopyright} 2019 Authors.; 17th ACM Conference on Embedded Networked Sensor Systems, SenSys 2019 ; Conference date: 10-11-2019 Through 13-11-2019",
year = "2019",
month = nov,
day = "10",
doi = "10.1145/3356250.3361951",
language = "English",
series = "SenSys 2019 - Proceedings of the 17th Conference on Embedded Networked Sensor Systems",
publisher = "Association for Computing Machinery",
pages = "384--385",
editor = "Mi Zhang",
booktitle = "SenSys 2019 - Proceedings of the 17th Conference on Embedded Networked Sensor Systems",
address = "United States",
}