EEG-based BCIs on motor imagery paradigm using wearable technologies: a systematic review

A Saibene, M Caglioni, S Corchs, F Gasparini - Sensors, 2023 - mdpi.com
In recent decades, the automatic recognition and interpretation of brain waves acquired by
electroencephalographic (EEG) technologies have undergone remarkable growth, leading …

[HTML][HTML] Specific feature selection in wearable EEG-based transducers for monitoring high cognitive load in neurosurgeons

P Arpaia, M Frosolone, L Gargiulo, N Moccaldi… - Computer Standards & …, 2025 - Elsevier
The electroencephalographic (EEG) features for discriminating high and low cognitive load
associated with fine motor activity in neurosurgeons were identified by combining wearable …

Lean Six Sigma to reduce the acute myocardial infarction mortality rate: a single center study

A Rosa, TA Trunfio, G Marolla, A Costantino… - The TQM …, 2023 - emerald.com
Purpose Cardiovascular diseases are the leading cause of death worldwide. In Italy, acute
myocardial infarction (AMI) is a major cause of hospitalization and healthcare costs. AMI is a …

[图书][B] Wearable Brain-Computer Interfaces: Prototyping EEG-Based Instruments for Monitoring and Control

P Arpaia, A Esposito, L Gargiulo, N Moccaldi - 2023 - taylorfrancis.com
This book presents a complete overview of the main EEG-based Brain-Computer Interface
(BCI) paradigms and the related practical solutions for their design, prototyping, and testing …

Multimodal feedback in assisting a wearable brain-computer interface based on motor imagery

P Arpaia, D Coyle, F Donnarumma… - … on Metrology for …, 2022 - ieeexplore.ieee.org
A multimodal sensory feedback was exploited in the present study to improve the detection
of neurological phenomena associated with motor imagery. At this aim, visual and haptic …

Heading for motor imagery brain-computer interfaces (MI-BCIs) usable out-of-the-lab: Impact of dry electrode setup on classification accuracy

MI Casso, C Jeunet, RN Roy - 2021 10th International IEEE …, 2021 - ieeexplore.ieee.org
A primary challenge to make motor-imagery Brain-Computer Interfaces (MI-BCIs)
technologies usable and actually used out-of-the-lab consists of providing EEG systems that …

EEG and HRV-Based Assessment of Neurosurgeons Training for Anxiety Regulation and Stress Monitoring

P Arpaia, G Carone, N Castelli… - … on Metrology for …, 2023 - ieeexplore.ieee.org
A neurofeedback (NF)-supported training is proposed to enable neurosurgeons to learn how
to regulate their emotions. Electroencephalographic (EEG) signal and heart rate (HR) of 5 …

Feasibility and Accuracy of a Dry and Wireless EEG Helmet for Upper Limb Motor Imagery-Based Brain-Computer Interfaces

M Ceradini, M Lassi, E Losanno… - … on Metrology for …, 2023 - ieeexplore.ieee.org
EEG-based brain-computer interfaces (BCIs) are a common tool in neurorehabilitation.
However, the benefits of EEG-based BCIs can be limited by the use of wet electrodes, which …

Toward an EEG-Based System for Monitoring Cognitive Load in Neurosurgeons

P Arpaia, R Ayadi, G Carone, N Castelli… - … on Metrology for …, 2023 - ieeexplore.ieee.org
In this study, a method combining statistical and machine learning approaches is proposed
to select the most informative EEG features for the detection of the cognitive load linked to …

Machine learning algorithms to study the hospitalization after cesarean section: a multicenter analysis

MR Marino, A Borrelli, G Bifulco, M Triassi… - Proceedings of the 2023 …, 2023 - dl.acm.org
Caesarean section (CS) is a surgical procedure in which the child is given birth through a
cut in the mother's abdomen. The surgery is relatively safe for both, especially when …