NDLI: Adaptation of task difficulty in rehabilitation exercises based on the user's motor performance and physiological responses

Content Provider	IEEE Xplore Digital Library
Author	Shirzad, N. Van der Loos, H.F.M.
Copyright Year	2013
Description	Author affiliation: Dept. of Mech. Eng., Univ. of British Columbia, Vancouver, BC, Canada (Shirzad, N.; Van der Loos, H.F.M.)
Abstract	Although robot-assisted rehabilitation regimens are as effective, functionally, as conventional therapies, they still lack features to increase patients' engagement in the regimen. Providing rehabilitation tasks at a “desirable difficulty” is one of the ways to address this issue and increase the motivation of a patient to continue with the therapy program. Then the problem is to design a system that is capable of estimating the user's desirable difficulty, and ultimately, modifying the task based on this prediction. In this paper we compared the performance of three machine learning algorithms in predicting a user's desirable difficulty during a typical reaching motion rehabilitation task. Different levels of error amplification were used as different levels of task difficulty. We explored the usefulness of using participants' motor performance and physiological signals during the reaching task in prediction of their desirable difficulties. Results showed that a Neural Network approach gives higher prediction accuracy in comparison with models based on k-Nearest Neighbor and Discriminant Analysis methods.
Starting Page	1
Ending Page	6
File Size	1011232
Page Count	6
File Format	PDF
ISBN	9781467360227
ISSN	19457901
e-ISBN	9781467360241
DOI	10.1109/ICORR.2013.6650429
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-06-24
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Visualization Thyristors physiological signals desirable difficulty Medical treatment machine learning stroke therapy Training Accuracy robotic reaching exercise error amplification Physiology motor performance Robots
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Control and Systems Engineering Rehabilitation

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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