Automating Stroke Rehabilitation for Home-Based Therapy
Conference Paper, Proceedings of AAAI '14 Fall Symposium on Artificial Intelligence for Human-Robot Interaction (AI - HRI '14), pp. 134 - 136, November, 2014
Abstract
In this work we present a conceptual design to automatically evaluate a subject’s performance for a home-based stroke rehabilitation system. We propose to model a reaching task as a trajectory in the state space of hand part features and then use reward learning to automatically generate new ratings for subjects to track performance over time.
BibTeX
@conference{Saran-2014-109817,author = {Akanksha Saran and Kris M. Kitani and Thannasis Rikakis},
title = {Automating Stroke Rehabilitation for Home-Based Therapy},
booktitle = {Proceedings of AAAI '14 Fall Symposium on Artificial Intelligence for Human-Robot Interaction (AI - HRI '14)},
year = {2014},
month = {November},
pages = {134 - 136},
}
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