most citedEvaluation of Motor Imagery-Based BCI methods in neurorehabilitation of Parkinson's Disease patients

28 citations · 28 across the 6 of their papers we have counts for

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eess.SP2020

Influence of some cardiovascular risk factors on the rela-tionship between age and blood pressure

Giulia Silveri, Lorenzo Pascazio, Milos Ajcevic +2

Blood Pressure (BP) is a biological signal related to the cardiovascular system that inevitably is affected by ageing. Moreover, it is also influenced by the presence of cardiovasc…

eess.SP2020

Influence of the gender on the relationship between heart rate and blood pressure

Giulia Silveri, Lorenzo Pascazio, Milos Ajcevic +2

Blood Pressure (BP) and Heart Rate (HR) provide information on clin-ical condition along 24h. Both signals present circadian changes due to sympa-thetic/parasympathetic control sys…

eess.SP2020

Novel Classification of Ischemic Heart Disease Using Artificial Neural Network

Giulia Silveri, Marco Merlo, Luca Restivo +2

Ischemic heart disease (IHD), particularly in its chronic stable form, is a subtle pathology due to its silent behavior before developing in unstable angina, myocardial infarction…

eess.SP2020

Transfer Learning improves MI BCI models classification accuracy in Parkinson's disease patients

Aleksandar Miladinović, Miloš Ajčević, Pierpaolo Busan +5

Motor-Imagery based BCI (MI-BCI) neurorehabilitation can improve locomotor ability and reduce the deficit symptoms in Parkinson's Disease patients. Advanced Motor-Imagery BCI metho…

eess.SP2020

Identification of Ischemic Heart Disease by using machine learning technique based on parameters measuring Heart Rate Variability

Giulia Silveri, Marco Merlo, Luca Restivo +5

The diagnosis of heart diseases is a difficult task generally addressed by an appropriate examination of patients clinical data. Recently, the use of heart rate variability (HRV) a…