NDLI: Data sample size needed for prediction of movement distributions

Content Provider	IEEE Xplore Digital Library
Author	Wright, Z.A. Fisher, M.E. Huang, F.C. Patton, J.L.
Copyright Year	2014
Description	Author affiliation: Sensory Motor Performance Program, Rehabilitation Inst. of Chicago, Chicago, IL, USA (Huang, F.C.) \|\| Univ. of Illinois at Chicago, Chicago, IL, USA (Wright, Z.A.; Fisher, M.E.; Patton, J.L.)
Abstract	Human movement ability should be described not only by its typical behavior, but also by the wide variation in capabilities. This would mean that subjects that are encouraged to move throughout their workspace but otherwise free to move any way they like might reveal their unique movement tendencies. In this study, we investigate how much information (data) is needed to reliably construct a movement distribution that predicts an individual's movement tendencies. We analyzed the distributions of position, velocity and acceleration data derived during self-directed motor exploration by stroke survivors (n=10 from a previous study) and healthy individuals (n=5). We examined whether these simple kinematic variables differed in terms of the amount of data required. We found a trend of decreasing time needed for characterization with the order of kinematic variable, for position, velocity, and acceleration, respectively. In addition, we investigated whether data requirements differ between stroke survivors and healthy. Our results suggest that healthy individuals may require more data samples (time for characterization), though the trend was only significant for position data. Our results provide an important step towards using statistical distributions to describe movement tendencies. Our findings could serve as more comprehensive tools to track recovery in or design more focused training intervention in neurorehabiliation applications.
Sponsorship	IEEE Eng. Med. Biol. Soc.
Starting Page	5780
Ending Page	5783
File Size	2829298
Page Count	4
File Format	PDF
ISBN	9781424479290
ISSN	1557170X
DOI	10.1109/EMBC.2014.6944941
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-08-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Acceleration Probability distribution Training Kinematics Statistical distributions Robot sensing systems
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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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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