Frosolone, Mirco (2021) An EEG-based Method for Fall Risk Prevention in Daily Life: Theoretical Background, Applications, and Perspectives. [Tesi di dottorato]

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Item Type: Tesi di dottorato
Resource language: English
Title: An EEG-based Method for Fall Risk Prevention in Daily Life: Theoretical Background, Applications, and Perspectives
Creators:
Creators
Email
Frosolone, Mirco
mircofrosolone@gmail.com
Date: 10 December 2021
Number of Pages: 126
Institution: Università degli Studi di Napoli Federico II
Department: Medicina Clinica e Chirurgia
Dottorato: Sanità pubblica e medicina preventiva
Ciclo di dottorato: 34
Coordinatore del Corso di dottorato:
nome
email
Troncone, Giancarlo
giancarlo.troncone@unina.it
Tutor:
nome
email
Arpaia, Pasquale
UNSPECIFIED
Date: 10 December 2021
Number of Pages: 126
Keywords: fall prevention, gait, EEG, attention, executive functions, cognitive engagement
Settori scientifico-disciplinari del MIUR: Area 09 - Ingegneria industriale e dell'informazione > ING-INF/06 - Bioingegneria elettronica e informatica
Area 09 - Ingegneria industriale e dell'informazione > ING-INF/07 - Misure elettriche e elettroniche
Area 06 - Scienze mediche > MED/26 - Neurologia
Date Deposited: 20 Dec 2021 13:50
Last Modified: 28 Feb 2024 11:39
URI: http://www.fedoa.unina.it/id/eprint/14311

Collection description

In this thesis, an EEG-based method for the prevention of falls to be employed in daily-life application is proposed. According to The World Health Organization (WHO), falls are a worldwide problem. They represent the second cause of death from unintentional injuries, and produce significant costs in charge to the healthcare system. Recent studies have shown that gait is not a higher order automated process, but includes a much more elaborate cortical involvement. The gait requires the use of complex cognitive abilities such as: i) an adequate cognitive load related to an effective cognitive engagement; ii) the use of the Executive Functions (EFs) during walking; and above all iii) the ability to allocate attentional resources while performing multiple concurrent activities during the walk. In order to develop a fall prevention system to be used in daily-life applications, a wearable and high portable EEG device was identified. The functional analysis of the EEG \textit{ab medica\textsuperscript{\textregistered} Helmate} was performed to verify its employability in the research of the cerebral correlates during the gait. To monitor cognitive load, an EEG-based method for cognitive engagement detection was realized in the learning and rehabilitation contexts. To identify which EEG features are mostly used in the literature for the evaluation of the EFs and their sub-functions, a review was carried out. Finally, a study for the assessment of attention/distraction during a dual-task oddball protocol was performed. Thus, the detection of attention, cognitive engagement, and EFs during dual-task walking allows to identify: i) a condition of impairment/overload of the subject's cognitive resources; and ii) the onset of a dangerous condition. Therefore, an EEG-based system and method for fall risk prevention can be implemented.

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