Search results for " empirical mode decomposition"

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Empirical mode decomposition and neural network for the classification of electroretinographic data

2013

The processing of biosignals is increasingly being utilized in ambulatory situations in order to extract significant signals' features that can help in clinical diagnosis. However, this task is hampered by the fact that biomedical signals exhibit a complex behaviour characterized by strong non-linear and non-stationary properties that cannot always be perceived by simple visual examination. New processing methods need be considered. In this context, we propose to apply a signal processing method, based on empirical mode decomposition and artificial neural networks, to analyse electroretinograms, i.e. the retinal response to a light flash, with the aim to detect and classify retinal diseases…

EngineeringAchromatopsiaBiomedical EngineeringContext (language use)Settore FIS/03 - Fisica Della MateriaHilbert–Huang transformRetinal DiseasesNight BlindnessElectroretinographyMyopiamedicineHumansComputer visionCongenital stationary night blindnessSignal processingArtificial neural networkbusiness.industryVisual examinationEye Diseases HereditaryGenetic Diseases X-LinkedSignal Processing Computer-AssistedPattern recognitionmedicine.diseaseSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Computer Science Applicationselectroretinogram empirical mode decomposition artificial neural network Achromatopsia Congenital Stationary Night BlindnessClinical diagnosisNeural Networks ComputerArtificial intelligencebusinessMedical & Biological Engineering & Computing
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An EEMD Aided Comparison of Time Histories and Its Application in Vehicle Safety

2017

In the context of signal processing, the comparison of time histories is required for different purposes, especially for the model validation of vehicle safety. Most of the existing metrics focus on the mathematical value only. Therefore, they suffer the measuring errors, disturbance, and uncertainties and can hardly achieve a stable result with a clear physical interpretation. This paper proposes a novel scheme of time histories comparison to be used in vehicle safety analysis. More specifically, each signal for comparison is decomposed into a trend signal and several intrinsic mode functions (IMFs) by ensemble empirical mode decomposition. The trend signals reflect the general variation a…

model validationDynamic time warpingGeneral Computer ScienceComputer science02 engineering and technologyHilbert–Huang transformEngineering (all)0203 mechanical engineeringVehicle safety0202 electrical engineering electronic engineering information engineeringIn vehicledynamic time warping (DTW)General Materials Sciencevehicle crashSimulationSignal processingdynamic time warping (DTW); Ensemble Empirical Mode Decomposition (EEMD); model validation; Time-history; vehicle crash; Computer Science (all); Materials Science (all); Engineering (all)Computer Science (all)General Engineering020302 automobile design & engineeringEnsemble Empirical Mode Decomposition (EEMD)Measurement uncertainty020201 artificial intelligence & image processingMaterials Science (all)lcsh:Electrical engineering. Electronics. Nuclear engineeringlcsh:TK1-9971AlgorithmTime-historyShape analysis (digital geometry)Motor vehicle crash
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