Social robots and brain–computer interface video games for dealing with attention deficit hyperactivity disorder: A systematic review

JA Cervantes, S López, S Cervantes, A Hernández… - Brain Sciences, 2023 - mdpi.com
Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder
characterized by inattention, hyperactivity, and impulsivity that affects a large number of …

Wearable Brain–Computer Interfaces Based on Steady-State Visually Evoked Potentials and Augmented Reality: A Review

L Angrisani, P Arpaia, E De Benedetto… - IEEE Sensors …, 2023 - ieeexplore.ieee.org
Brain–computer interfaces (BCIs) are an integration of hardware and software
communication systems that allow a direct communication path between the human brain …

Impact of nutritional factors in blood glucose prediction in type 1 diabetes through machine learning

G Annuzzi, A Apicella, P Arpaia, L Bozzetto… - IEEE …, 2023 - ieeexplore.ieee.org
Type 1 Diabetes (T1D) is an autoimmune disease that affects millions of people worldwide.
A critical issue in T1D patients is the managing of Postprandial Glucose Response (PGR) …

Toward the application of XAI methods in EEG-based systems

A Apicella, F Isgrò, A Pollastro, R Prevete - arXiv preprint arXiv …, 2022 - arxiv.org
An interesting case of the well-known Dataset Shift Problem is the classification of
Electroencephalogram (EEG) signals in the context of Brain-Computer Interface (BCI). The …

EEG-Based Brain-Computer Interactions in Immersive Virtual and Augmented Reality: A Systematic Review

C Nwagu, A AlSlaity, R Orji - Proceedings of the ACM on Human …, 2023 - dl.acm.org
Brain-computer interactions allow humans to passively or actively control computer systems
using their brain activity. For more than a decade now, these interactions have been …

Employment of domain adaptation techniques in SSVEP-based brain–computer interfaces

A Apicella, P Arpaia, E De Benedetto, N Donato… - IEEE …, 2023 - ieeexplore.ieee.org
This work addresses the employment of Machine Learning (ML) and Domain Adaptation
(DA) in the framework of Brain-Computer Interfaces (BCIs) based on Steady-State Visually …

A novel measurement method for performance assessment of hands-free, XR-based Human-Machine Interfaces

L Angrisani, M D'Arco, E De Benedetto… - IEEE Sensors …, 2024 - ieeexplore.ieee.org
This article presents an innovative measurement method for assessing the information
transfer performance of hands-free human-machine interfaces (HMIs) based on extended …

Expanding the Frontiers of Wearable Brain-Computer Interfaces Combining Augmented Reality and Visually Evoked Potentials

L Angrisani, P Arpaia, E De Benedetto… - … on Metrology for …, 2023 - ieeexplore.ieee.org
Given the increasing demand for systems that enable seamless human-computer
interaction, this study presents the design and implementation of a highly wearable Brain …

[HTML][HTML] Cyborg Children: A Systematic Literature Review on the Experience of Children Using Extended Reality

M Everri, M Heitmayer - Children, 2024 - mdpi.com
This literature review presents a comprehensive and systematic account of research on the
experiences of children with extended reality (XR), including VR, AR, and other types of …

Evaluation of the Effectiveness of a Wearable, AR-based BCI for Robot Control in ADHD Treatment

P Arpaia, S Criscuolo, E De Benedetto… - … on Metrology for …, 2022 - ieeexplore.ieee.org
A highly wearable, single-channel Brain-Computer Interface based on Augmented Reality
and Steady-State Visually Evoked Potentials is proposed as a therapy for Attention Deficit …