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Pasquale Arpaia
Also published under:P. Arpaia
Affiliation
Department of Electrical Engineering and Information Technology (DIETI), Università degli Studi di Naples Federico II, Naples, Italy
Topic
EEG Data,EEG Signals,Type 1 Diabetes Mellitus,Support Vector Machine,Artificial Neural Network,Blood Glucose,EEG Features,Experimental Run,Explainable Artificial Intelligence,Machine Learning,Neural Network,Absolute Power,Blood Glucose Concentration,Cognitive Tasks,Continuous Glucose Monitoring,Delta Band,Impedance Magnitude,Task Execution,Amount Of Insulin,Blood Glucose Levels,Canonical Correlation Analysis,Cognitive Load,Continuous Subcutaneous Insulin Infusion,Equivalent Approach,Equivalent Circuit,Executive Function,Feed-forward Network,Impedance Measurements,Independent Component Analysis,Machine Learning Models,Magnetic Field,SHapley Additive exPlanations,Shapley Value,Subcutaneous Injection,Artificial Pancreas,Band Power,Bioavailability Of Insulin,Classification Accuracy,Convolutional Neural Network,Delta Power,Difficulty Level,Dry Electrodes,Electrical Circuit,Energy Intake,Glycemic Index,Go-NoGo Task,Hall Sensor,Head-mounted Display,Human Tissue,Impedance Phase,
Biography
Pasquale Arpaia earned his master's and Ph.D. degrees in electrical engineering at University Federico II, Naples, Italy, where he is Full Professor of Instrumentation and Measurements. He is Director of the Interdepartmental Center for Research on Management and Innovation of Health (CIR-MIS) and Head of the Instrumentation and Measurement for Particle Accelerators Laboratory (IMPALab) and the Augmented Reality for Health Monitoring Laboratory (AR-HeMlab). His main research interests include instrumentation and measurement for magnets, advanced materials, beam, superconductors, power converters, and cryogenics of particle accelerators, biomedical instrumentation, Augmented Reality, Brain Computer Interfaces, evolutionary diagnostics, distributed measurement systems, ADC modelling, and testing.