Record Details

Hand-Movement Prediction Using LFP Data

Electronic Theses of Indian Institute of Science

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Field Value
 
Title Hand-Movement Prediction Using LFP Data
 
Creator Muralidharan, Prasanna
 
Subject Mathematics
Brain-Machine Interface (BMI)
Biomedical Engineering
Pattern Perception
Local Field Potential (LFP)
Pattern Recognition
Neurobiology
 
Description The last decade has seen a surge in the development of Brain-Machine Interfaces (BMI) as assistive neural devices for paralysis patients. Current BMI research typically involves a subject performing movements by controlling a robotic prosthesis. The neural signal that we consider for analysis is the Local Field Potential (LFP). The LFP is a low frequency neural signal recorded from intra-cortical electrodes, and has been recognized as one containing movement information. This thesis investigates hand-movement prediction using LFP data as input. In Chapter 1, we give an overview of Brain Machine Interfaces. In Chapter 2, we review the necessary concepts in time series analysis and pattern recognition. In the final chapter, we discuss classification accuracies when considering Summed power and Coherence as feature vectors.
 
Contributor Rangarajan, Govindan
 
Date 2011-08-08T11:31:14Z
2011-08-08T11:31:14Z
2011-08-08
2010-03
 
Type Thesis
 
Identifier http://etd.iisc.ernet.in/handle/2005/1342
http://etd.ncsi.iisc.ernet.in/abstracts/1736/G23704-Abs.pdf
 
Language en_US
 
Relation G23704