Cooperation and mental states neurophysiological assessment for pilots’ training and expertise evaluation DOI
Gianluca Borghini, Andrea Giorgi, Vincenzo Ronca

et al.

Published: Nov. 20, 2023

The aim of the study was to validate a methodology for professional pilots' neurophysiological assessment improve training program tailoring and management. In particular, focused on quantifying (i) mental workload, (ii) stress level (iii) cooperation degree between two members crews. Two groups pilots were involved in experiments: Experienced Unexperienced. Additionally, Instructor responsible provide subjective evaluation about states cooperation. During entire flight simulations, brain activity acquired through Electroencephalography (EEG). results demonstrated that it is possible quantify operators' while dealing with simulations under realistic settings. Pilots' workload behavioral levels resulted be positively significantly correlated corresponding measurements (all R > 0.6, all p < 0.05), observed higher (p 0.05) than Although are preliminary, they show how capability tasks will instructors additional objective information. this information would allow sessions based crew's behavior.

Language: Английский

o-CLEAN: a novel multi-stage algorithm for the ocular artifacts’ correction from EEG data in out-of-the-lab applications DOI Creative Commons
Vincenzo Ronca, Gianluca Di Flumeri, Andrea Giorgi

et al.

Journal of Neural Engineering, Journal Year: 2024, Volume and Issue: 21(5), P. 056023 - 056023

Published: Sept. 19, 2024

In the context of electroencephalographic (EEG) signal processing, artifacts generated by ocular movements, such as blinks, are significant confounding factors. These overwhelm informative EEG features and may occur too frequently to simply remove affected epochs without losing valuable data. Correcting these remains a challenge, particularly in out-of-lab online applications using wearable systems (i.e. with low number channels, any additional channels track EOG).

Language: Английский

Citations

1

An investigation on mental stress detection from various physiological signals DOI

R. S. Sabeenian,

Sree Janani Kuralnatham Karuppannan

AIP conference proceedings, Journal Year: 2023, Volume and Issue: unknown

Published: Jan. 1, 2023

Language: Английский

Citations

3

Evaluating the cognitive and psychological effects of real-time auditory travel information on drivers using EEG DOI
Shubham Agrawal, Srinivas Peeta, Irina Benedyk

et al.

Behaviour and Information Technology, Journal Year: 2022, Volume and Issue: 42(10), P. 1617 - 1639

Published: June 26, 2022

Real-time travel information design with inadequate consideration of human factors can lead to driver distraction and diminish road safety. This study measures drivers' brain electrical activity patterns evaluate multiple aspects cognition psychology under real-time provision using insights from the neuroscience domain on localisation functions. The 84 participants are collected an electroencephalogram (EEG) in interactive driving simulator environment. impacts auditory characteristics (amount, sufficiency, content) different time stages interaction (before, during, after) frequency band powers EEG signals regions analyzed linear mixed models. Study results illustrate that drivers exert more cognitive effort perceive/process routes complex environments. Insufficient may evoke increased attention internal processing memory characterised by higher uncertainty, while route recommendation switch such increase stress anxiety. findings aid providers, both private public, as well auto manufacturers incorporate designing safer their delivery systems.

Language: Английский

Citations

5

Unsupervised Detection of Covariate Shift Due to Changes in EEG Headset Position: Towards an Effective Out-of-Lab Use of Passive Brain–Computer Interface DOI Creative Commons
Daniele Germano, Nicolina Sciaraffa, Vincenzo Ronca

et al.

Applied Sciences, Journal Year: 2023, Volume and Issue: 13(23), P. 12800 - 12800

Published: Nov. 29, 2023

In the field of passive Brain–computer Interfaces (BCI), need to develop systems that require rapid setup, suitable for use outside laboratories is a fundamental challenge, especially now, market flooded with novel EEG headsets good quality. However, lack control in operational conditions can compromise performance machine learning model behind BCI system. First, this study focuses on evaluating loss system, induced by different positioning headset (and course sensors), so generating variation features used calibrate algorithm. This phenomenon called covariate shift. Detecting shift occurrences advance allows preventive measures, such as informing user adjust position or applying specific corrections new coming data. We an unsupervised Machine Learning model, Isolation Forest, detect occurrence tested method two datasets, one controlled setting (9 participants), and other more realistic (10 participants). dataset, we simulated movement cap using channel reference configurations. For each test configuration, selected set electrodes near electrodes. Regarding aimed simulate laboratory, mimicking removal repositioning non-expert user. both recorded multiple sessions configuration while executing Workload tasks. The results obtained Forest allowed identification data, even 15-s recording sample. Moreover, showed strong significant negative correlation between percentage detected method, accuracy system (p-value < 0.01). approach opens perspectives developing robust flexible systems, potential move these technologies towards out-of-the-lab use, without supervision

Language: Английский

Citations

2

Cooperation and mental states neurophysiological assessment for pilots’ training and expertise evaluation DOI
Gianluca Borghini, Andrea Giorgi, Vincenzo Ronca

et al.

Published: Nov. 20, 2023

The aim of the study was to validate a methodology for professional pilots' neurophysiological assessment improve training program tailoring and management. In particular, focused on quantifying (i) mental workload, (ii) stress level (iii) cooperation degree between two members crews. Two groups pilots were involved in experiments: Experienced Unexperienced. Additionally, Instructor responsible provide subjective evaluation about states cooperation. During entire flight simulations, brain activity acquired through Electroencephalography (EEG). results demonstrated that it is possible quantify operators' while dealing with simulations under realistic settings. Pilots' workload behavioral levels resulted be positively significantly correlated corresponding measurements (all R > 0.6, all p < 0.05), observed higher (p 0.05) than Although are preliminary, they show how capability tasks will instructors additional objective information. this information would allow sessions based crew's behavior.

Language: Английский

Citations

2