2016
DOI: 10.1109/tnsre.2016.2525829
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Automatic Parametrization of Somatosensory Evoked Potentials With Chirp Modeling

Abstract: In this paper, an approach using polynomial phase chirp signals to model somatosensory evoked potentials (SEPs) is proposed. SEP waveforms are assumed as impulses undergoing group velocity dispersion while propagating along a multipath neural connection. Mathematical analysis of pulse dispersion resulting in chirp signals is performed. An automatic parameterization of SEPs is proposed using chirp models. A Particle Swarm Optimization algorithm is used to optimize the model parameters. Features describing the l… Show more

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Cited by 10 publications
(3 citation statements)
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“…Typically, recordings are followed by real-time and or offline signal processing, which enables scientists to (i) detect the onset and progress of trauma, (ii) qualify and quantify the severity of SCI, and (iii) identify and distinguish even minuscule changes that could be due to the endogenous repair or exogenous therapeutic recovery. A few main methods of SSEP signal processing techniques are shape analysis [42,43], spectral coherence [44], slope analysis [45], adaptive coherence [46], chirp modeling [47], sparse modeling [48], as well as several other methods [49][50][51][52][53].…”
Section: Signal Analysismentioning
confidence: 99%
“…Typically, recordings are followed by real-time and or offline signal processing, which enables scientists to (i) detect the onset and progress of trauma, (ii) qualify and quantify the severity of SCI, and (iii) identify and distinguish even minuscule changes that could be due to the endogenous repair or exogenous therapeutic recovery. A few main methods of SSEP signal processing techniques are shape analysis [42,43], spectral coherence [44], slope analysis [45], adaptive coherence [46], chirp modeling [47], sparse modeling [48], as well as several other methods [49][50][51][52][53].…”
Section: Signal Analysismentioning
confidence: 99%
“…The SSEP measurement is a non-invasive procedure and is performed routinely in clinical settings and in the research models of SCI. It provides objective assessments of the onset, severity, and progress of the injury, as well as the endogenous and therapeutic recovery post-SCI [ 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 ]. The SSEP has extensively been used to assess stem cell replacement therapy [ 52 , 53 , 54 , 55 ] as well as plasticity and reorganization of neuropathways [ 31 , 56 ] post-SCI as well.…”
Section: Neuroelectrophysiology Monitoringmentioning
confidence: 99%
“…Furthermore, in most models, general classes of response profiles are modeled, rather than being able to model individual response profiles. Particle swarm optimization has been used in many computational biology models, including fitting somatosensory responses to chirp functions 43 and training recurrent neural networks which model gene regulatory networks. 21 Van Geit et al 41 developed an optimization program which allows for the optimization of neuron model parameters to fit time dependent traces.…”
Section: Introductionmentioning
confidence: 99%