Using principal component analysis to reduce complex datasets produced by robotic technology in healthy participants

Using principal component analysis to reduce complex datasets produced by robotic technology in healthy participants

Abstract Background The KINARM robot produces a granular dataset of participant performance metrics associated with proprioceptive, motor, visuospatial, and executive function. This comprehensive battery includes several behavioral tasks that each generate 9 to 20 metrics of performance. Therefore,...

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Bibliographic Details
Main Authors: Michael D. Wood, Leif E. R. Simmatis, J. Gordon Boyd, Stephen H. Scott, Jill A. Jacobson
Format: Article
Language:English
Published: BMC 2018-07-01
Series:Journal of NeuroEngineering and Rehabilitation
Subjects:
KINARM
End-point robot
Principal component analysis
Data reduction
Online Access:http://link.springer.com/article/10.1186/s12984-018-0416-5

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http://link.springer.com/article/10.1186/s12984-018-0416-5

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