Static Versus Dynamic Decoding Algorithms in a Non-Invasive Body-Machine Interface

In this study, we consider a non-invasive body-machine interface that captures body motions still available to people with spinal cord injury (SCI) and maps them into a set of signals for controlling a computer user interface while engaging in a sustained level of mobility and exercise. We compare t...

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Bibliographic Details
Published in:	IEEE transactions on neural systems and rehabilitation engineering Vol. 25; no. 7; pp. 893 - 905
Main Authors:	Seanez-Gonzalez, Ismael, Pierella, Camilla, Farshchiansadegh, Ali, Thorp, Elias B., Abdollahi, Farnaz, Pedersen, Jessica P., Mussa-Ivaldi, Ferdinando A.
Format:	Journal Article
Language:	English
Published:	United States IEEE 01.07.2017
Subjects:	Actigraphy - methods Adult Algorithms Assistive devices Body–machine interface (BMI) cervical spinal cord injury Computers Female handicapped aids Heuristic algorithms Humans Kalman filters Kinematics Male Man-Machine Systems Middle Aged Movement Pattern Recognition, Automated - methods Principal Component Analysis Reproducibility of Results Sensitivity and Specificity Signal Processing, Computer-Assisted Spinal Cord Injuries - physiopathology tetraplegia Unsupervised Machine Learning wheelchair control Wheelchairs
ISSN:	1534-4320, 1558-0210
Online Access:	Get full text
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