The driving drowsiness has been identified as one of the major causes of road traffic accidents, causing fatalities and permanent injuring. Drowsy drivers are prone to suddenly lose control of the car, mostly without any prior behavioral cue. The present study involved 19 participants in a simulated driving protocol, designed to induce mental drowsiness into the drivers. The objective of the study consisted in testing an innovative Electroencephalographic (EEG)-based index, the MDrow index, in detecting the driving drowsiness. Such an index, derived from parietal EEG channels, was already validated in our previous work achieving outstanding performance with respect to more conventional techniques. In this study, the possibility of obtaining a similar index from the frontal sites in order to foster its exploitation in real environments has been investigated. The results demonstrated the capability of the "frontal" MDrow index in evaluating the driving drowsiness experienced by the participants with performance comparable to that one previously validated over parietal sites. Also, the impact of the reduction of the electrodes number on index reliability has been investigated, in order to evaluate its compatibility with current wearable EEG devices.

Validation of an EEG-based neurometric for online monitoring and detection of mental drowsiness while driving / Ronca, Vincenzo; Di Flumeri, Gianluca; Vozzi, Alessia; Giorgi, Andrea; Arico, Pietro; Sciaraffa, Nicolina; Babiloni, Fabio; Borghini, Gianluca. - 2022:(2022), pp. 3714-3717. (Intervento presentato al convegno 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) tenutosi a Glasgow, Scotland, United Kingdom) [10.1109/EMBC48229.2022.9871505].

Validation of an EEG-based neurometric for online monitoring and detection of mental drowsiness while driving

Ronca, Vincenzo
;
Di Flumeri, Gianluca;Vozzi, Alessia;Giorgi, Andrea;Arico, Pietro;Sciaraffa, Nicolina;Babiloni, Fabio;Borghini, Gianluca
2022

Abstract

The driving drowsiness has been identified as one of the major causes of road traffic accidents, causing fatalities and permanent injuring. Drowsy drivers are prone to suddenly lose control of the car, mostly without any prior behavioral cue. The present study involved 19 participants in a simulated driving protocol, designed to induce mental drowsiness into the drivers. The objective of the study consisted in testing an innovative Electroencephalographic (EEG)-based index, the MDrow index, in detecting the driving drowsiness. Such an index, derived from parietal EEG channels, was already validated in our previous work achieving outstanding performance with respect to more conventional techniques. In this study, the possibility of obtaining a similar index from the frontal sites in order to foster its exploitation in real environments has been investigated. The results demonstrated the capability of the "frontal" MDrow index in evaluating the driving drowsiness experienced by the participants with performance comparable to that one previously validated over parietal sites. Also, the impact of the reduction of the electrodes number on index reliability has been investigated, in order to evaluate its compatibility with current wearable EEG devices.
2022
44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
performance evaluation; electrodes; protocols; electroencephalography; road safety; indexes; reliability
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Validation of an EEG-based neurometric for online monitoring and detection of mental drowsiness while driving / Ronca, Vincenzo; Di Flumeri, Gianluca; Vozzi, Alessia; Giorgi, Andrea; Arico, Pietro; Sciaraffa, Nicolina; Babiloni, Fabio; Borghini, Gianluca. - 2022:(2022), pp. 3714-3717. (Intervento presentato al convegno 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) tenutosi a Glasgow, Scotland, United Kingdom) [10.1109/EMBC48229.2022.9871505].
File allegati a questo prodotto
File Dimensione Formato  
Ronca_Validation_2022.pdf

solo gestori archivio

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 332.35 kB
Formato Adobe PDF
332.35 kB Adobe PDF   Contatta l'autore

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1661968
Citazioni
  • ???jsp.display-item.citation.pmc??? 0
  • Scopus 2
  • ???jsp.display-item.citation.isi??? ND
social impact