2018
Real-Time Cardiac Arrhythmia Classification Using Memristor Neuromorphic Computing System
Hassan A, Khalaf A, Sayed K, Li H, Chen Y. Real-Time Cardiac Arrhythmia Classification Using Memristor Neuromorphic Computing System. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2018, 00: 2567-2570. PMID: 30440932, DOI: 10.1109/embc.2018.8512868.Peer-Reviewed Original ResearchConceptsNeuromorphic computing systemsComputing systemsCardiac arrhythmia classificationArrhythmia classificationReal-time processingTerms of accuracyDifferent beat typesAverage testing timeTesting timeAverage accuracyBeat typesBasic building blocksDetection techniquesPower consumptionOverall accuracyExperimental resultsClassificationAccuracySystemBuilding blocks
2017
A brain-computer interface based on functional transcranial doppler ultrasound using wavelet transform and support vector machines
Khalaf A, Sybeldon M, Sejdic E, Akcakaya M. A brain-computer interface based on functional transcranial doppler ultrasound using wavelet transform and support vector machines. Journal Of Neuroscience Methods 2017, 293: 174-182. PMID: 29017899, DOI: 10.1016/j.jneumeth.2017.10.003.Peer-Reviewed Original ResearchMeSH KeywordsBlood Flow VelocityBrainBrain-Computer InterfacesCerebrovascular CirculationCognitionFeasibility StudiesFemaleFunctional NeuroimagingHumansImaginationLanguageLinear ModelsMaleNeuropsychological TestsRestRotationSpace PerceptionSupport Vector MachineUltrasonography, Doppler, TranscranialWavelet AnalysisYoung AdultConceptsFunctional transcranial DopplerWord generation taskCognitive tasksMental rotationGeneration taskFunctional transcranial Doppler ultrasoundReal-time BCIMental rotation taskWord generationRotation taskNeural activationBrain-computer interfaceFive-level wavelet decompositionFTCD signalsTaskAverage accuracyBCISignificant improvementVector machine