A novel unsorted spike feature based real-time sensory event detection for closed-loop control

Title
A novel unsorted spike feature based real-time sensory event detection for closed-loop control
Authors
한성민추준욱최귀원박종웅윤인찬
Keywords
spinal cord; pattern recognition; sensory event
Issue Date
2015-11
Publisher
International BioMedical Engineering Conference 2015 (IBEC 2015)
Citation
, 145
Abstract
The goal of the current study was to investigate the possibility of sensory event detection from the afferent signal recorded by using a multichannel micro-electrode on the dorsal root ganglion without spike sorting. We particularly considered to extract the most informative feature vector from recorded neural signals using feature combination of previous studies such as electroneurograhpy signals, electromyography signals and neural spikes. Principal component analysis was used to reduce dimensionality of feature vector, and multilayer perceptron classifier was used to detect sensory events. In this study, a novel unsorted spike-based feature extraction methods was proposed to enhance the detection accuracy of sensory events.
URI
http://pubs.kist.re.kr/handle/201004/58419
Appears in Collections:
KIST Publication > Conference Paper
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