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Please use this identifier to cite or link to this item: http://hdl.handle.net/1807/18917

Title: Detection of Movement Intention Onset for Brain-machine Interfaces
Authors: McGie, Steven
Advisor: Popovic, Milos R.
Department: Biomedical Engineering
Keywords: brain-machine interface
neural engineering
rehabilitation engineering
neuroprosthetics
brain-computer interface
synchronous
EEG
ECoG
Issue Date: 15-Feb-2010
Abstract: The goal of the study was to use electrical signals from primary motor cortex to generate accurate predictions of the movement onset time of performed movements, for potential use in asynchronous brain-machine interface (BMI) systems. Four subjects, two with electroencephalogram and two with electrocorticogram electrodes, performed various movements while activity from their primary motor cortices was recorded. An analysis program used several criteria (change point, fractal dimension, spectral entropy, sum of differences, bandpower, bandpower integral, phase, and variance), derived from the neural recordings, to generate predictions of movement onset time, which it compared to electromyogram activity onset time, determining prediction accuracy by receiver operating characteristic curve areas. All criteria, excepting phase and change-point analysis, generated accurate predictions in some cases.
URI: http://hdl.handle.net/1807/18917
Appears in Collections:Master
Institute of Biomaterials and Biomedical Engineering - Master theses

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