Paper Info
Title
Reduction of stroke assessment time for visually guided reaching task on KINARM exoskeleton robot.
Abstract
Robotic technologies provide objective, highly reliable tools for assessment of brain function following stroke. KINARM is an exoskeleton device that quantifies sensorimotor brain function using a visually guided reaching task among many other behavioral tasks. As further tasks are developed to more broadly assess different aspects of behavior using the robot, techniques and approaches are required to reduce the time it takes to complete each task. The present study investigates how the value of robot-measured parameters changes under alternative schemes that significantly reduce assessment time compared to the current assessment protocol for the visually guided reaching task. Results of the study are validated by addressing an important diagnostic question using an SVM classifier, showing that the alternative schemes provide nearly identical performance in terms of classification sensitivity, specificity and accuracy.
Year
DOI
Venue
2014
10.1109/EMBC.2014.6944821
EMBC
Keywords
Field
DocType
medical robotics,behavioral tasks,biomechanics,medical disorders,biomedical measurement,pattern classification,classification specificity,visually guided reaching task,classification sensitivity,svm classifier,visually guided reaching,kinarm,patient rehabilitation,support vector machine,stroke assessment,post stroke brain function assessment,kinarm exoskeleton robot,sensorimotor evaluation,classification accuracy,stroke assessment time reduction,sensorimotor brain function quantification,support vector machines,robot measured parameters
Computer vision,Simulation,Computer science,Stroke,Artificial intelligence,Exoskeleton robot
Conference
Volume
ISSN
Citations 
2014
1557-170X
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Sayyed Mostafa Mostafavi121.10
S P Dukelow200.34
Janice I. Glasgow3392127.97
Stephen H. Scott4124.01
P. Mousavi5425.62