Recent progress in wearable brain–computer interface (BCI) devices based on electroencephalogram (EEG) for medical applications: a review
J Zhang, J Li, Z Huang, D Huang, H Yu, Z Li - Health Data Science, 2023 - spj.science.org
Importance: Brain–computer interface (BCI) decodes and converts brain signals into
machine instructions to interoperate with the external world. However, limited by the …
machine instructions to interoperate with the external world. However, limited by the …
Electrophysiology and hyperscanning applied to e-learning for organizational training
M Balconi, L Angioletti, F Cassioli - The Learning Organization, 2023 - emerald.com
Purpose The purpose of this study is to investigate the effects of the remote training process
on distance learning with the application of neurometrics and investigate the features of the …
on distance learning with the application of neurometrics and investigate the features of the …
Hyperscanning EEG paradigm applied to remote vs. face-to-face learning in managerial contexts: Which is better?
M Balconi, L Angioletti, F Cassioli - Brain Sciences, 2023 - mdpi.com
We propose a hyperscanning research design, where electroencephalographic (EEG) data
were collected on an instructor and teams of learners. We compared neurophysiological …
were collected on an instructor and teams of learners. We compared neurophysiological …
Oscillatory wavelet-patterns in complex data: mutual estimation of frequencies and energy dynamics
M Simonyan, A Fisun, G Afanaseva… - The European Physical …, 2023 - Springer
In this work, we propose a modification of the wavelet oscillatory pattern method for
analyzing energy characteristics of oscillatory components in complex signals. The energy …
analyzing energy characteristics of oscillatory components in complex signals. The energy …
Self-awareness of goals task (SAGT) and planning skills: the neuroscience of decision making
M Balconi, L Angioletti, C Acconito - Brain Sciences, 2023 - mdpi.com
A goal's self-awareness and the planning to achieve it drive decision makers. Through a
neuroscientific approach, this study explores the self-awareness of goals by analyzing the …
neuroscientific approach, this study explores the self-awareness of goals by analyzing the …
Neurophysiological and Autonomic Correlates of Metacognitive Control of and Resistance to Distractors in Ecological Setting: A Pilot Study
In organisational contexts, professionals are required to decide dynamically and prioritise
unexpected external inputs deriving from multiple sources. In the present study, we applied …
unexpected external inputs deriving from multiple sources. In the present study, we applied …
Subject adaptive eeg-based visual recognition
This paper focuses on EEG-based visual recognition, aiming to predict the visual object
class observed by a subject based on his/her EEG signals. One of the main challenges is …
class observed by a subject based on his/her EEG signals. One of the main challenges is …
Not Everyone Chooses Profit (If It Is too Tiring): What Behavioral and EEG Data Tell Us
M Balconi, C Acconito, L Angioletti - Applied Sciences, 2024 - mdpi.com
Background: A more rewarding choice, even if it requires more effort, is usually preferred by
individuals; yet, in some cases, individuals choose less profitable and less tiring options …
individuals; yet, in some cases, individuals choose less profitable and less tiring options …
An electrophysiological study applied to remote learning: Preliminary results from an hyperscanning paradigm.
F Cassioli, M Balconi - Neuropsychological Trends, 2022 - psycnet.apa.org
The digitalization of learning in the organization represents both a necessity and an
opportunity. Little to no research explored how distance training affects cognitive and …
opportunity. Little to no research explored how distance training affects cognitive and …
Motor Imagery-based Brain-Computer Interfaces: Exploring Optimization and Transfer Learning Techniques for Multiclass Classification
VT Kenworthy, KM Nylænder - 2023 - ntnuopen.ntnu.no
Dette arbeidet fokuserer på å håndtere noen utfordinger innen hjerne-datamaskin-
grensesnitt (BCI) basert på forestilte bevegelser (MI), kalt MI-BCI, inkludert forbedring av …
grensesnitt (BCI) basert på forestilte bevegelser (MI), kalt MI-BCI, inkludert forbedring av …