Search results for "Electrodiagnòstic"

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Detection of Ventricular Fibrillation Using the Image from Time-Frequency Representation and Combined Classifiers without Feature Extraction

2018

Due the fact that the required therapy to treat Ventricular Fibrillation (V F) is aggressive (electric shock), the lack of a proper detection and recovering therapy could cause serious injuries to the patient or trigger a ventricular fibrillation, or even death. This work describes the development of an automatic diagnostic system for the detection of the occurrence of V F in real time by means of the time-frequency representation (T F R) image of the ECG. The main novelties are the use of the T F R image as input for a classification process, as well as the use of combined classifiers. The feature extraction stage is eliminated and, together with the use of specialized binary classifiers, …

ElectrodiagnòsticECG electrocardiogram signalsComputer science0206 medical engineeringFeature extraction02 engineering and technologycombined classification algorithmslcsh:TechnologyImage (mathematics)lcsh:ChemistryTime–frequency representationimage analysisvoting majority method classifiersnon-stationary signalstime-frequency representation0202 electrical engineering electronic engineering information engineeringmedicineGeneral Materials ScienceInstrumentationlcsh:QH301-705.5Fluid Flow and Transfer Processesbusiness.industrybiomedical systemslcsh:TProcess Chemistry and TechnologyGeneral EngineeringPattern recognitionmedicine.disease020601 biomedical engineeringlcsh:QC1-999Computer Science ApplicationsTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESlcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040Ventricular fibrillationEnginyeria biomèdica020201 artificial intelligence & image processingArtificial intelligencebusinesslcsh:Engineering (General). Civil engineering (General)hierarchical classifiersImatges Processament Tècniques digitalslcsh:PhysicsApplied Sciences
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Real-Time Localization of Epileptogenic Foci EEG Signals: An FPGA-Based Implementation

2020

The epileptogenic focus is a brain area that may be surgically removed to control of epileptic seizures. Locating it is an essential and crucial step prior to the surgical treatment. However, given the difficulty of determining the localization of this brain region responsible of the initial seizure discharge, many works have proposed machine learning methods for the automatic classification of focal and non-focal electroencephalographic (EEG) signals. These works use automatic classification as an analysis tool for helping neurosurgeons to identify focal areas off-line, out of surgery, during the processing of the huge amount of information collected during several days of patient monitori…

ElectrodiagnòsticRemote patient monitoringComputer science02 engineering and technologyElectroencephalographylcsh:Technologylcsh:Chemistryepileptogenic focus03 medical and health sciences0302 clinical medicineClassifier (linguistics)0202 electrical engineering electronic engineering information engineeringmedicineGeneral Materials ScienceEpilepsy surgeryLatency (engineering)Field-programmable gate arrayInstrumentationThroughput (business)lcsh:QH301-705.5FPGAFluid Flow and Transfer Processesmedicine.diagnostic_testbusiness.industrylcsh:TProcess Chemistry and Technologyreal-time implementationepileptic eeg signal classificationGeneral EngineeringProcess (computing)Pattern recognitionelectroencephalogramlcsh:QC1-999Computer Science Applicationsfpgalcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040epileptic EEG signal classificationepilepsy020201 artificial intelligence & image processingEnginyeria biomèdicaArtificial intelligenceElectroencefalografiabusinesslcsh:Engineering (General). Civil engineering (General)030217 neurology & neurosurgerylcsh:Physics
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