0000000000756499

AUTHOR

A. Mjahad

showing 1 related works from this author

Ventricular Fibrillation and Tachycardia detection from surface ECG using time-frequency representation images as input dataset for machine learning

2017

Parameter-less ventricular fibrillation detection with time-frequency representation.Time-frequency representations are treated as images for a classifier.A comparison for four classifiers demonstrates the validity of the proposed method.The proposed technique could be applied to any signal and research field.This is a novel approach to signal analysis. Background and objectiveTo safely select the proper therapy for Ventricullar Fibrillation (VF) is essential to distinct it correctly from Ventricular Tachycardia (VT) and other rhythms. Provided that the required therapy would not be the same, an erroneous detection might lead to serious injuries to the patient or even cause Ventricular Fibr…

TachycardiaSupport Vector MachineComputer scienceSpeech recognition0206 medical engineeringDatasets as TopicHealth Informatics02 engineering and technologyVentricular tachycardiaMachine learningcomputer.software_genreMachine LearningElectrocardiographyTachycardia0202 electrical engineering electronic engineering information engineeringmedicineHumansFibrillationbusiness.industrySignal Processing Computer-AssistedPattern recognitionmedicine.disease020601 biomedical engineeringComputer Science ApplicationsVentricular FibrillationVentricular fibrillation020201 artificial intelligence & image processingNeural Networks ComputerArtificial intelligencemedicine.symptombusinessClassifier (UML)computerSoftwareComputer Methods and Programs in Biomedicine
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