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A New Perspective for the Training Assessment: Machine Learning-Based Neurometric for Augmented User's Evaluation

Frontiers in Neuroscience. 2017;11 DOI 10.3389/fnins.2017.00325

 

Journal Homepage

Journal Title: Frontiers in Neuroscience

ISSN: 1662-4548 (Print); 1662-453X (Online)

Publisher: Frontiers Media S.A.

LCC Subject Category: Medicine: Internal medicine: Neurosciences. Biological psychiatry. Neuropsychiatry

Country of publisher: Switzerland

Language of fulltext: English

Full-text formats available: PDF, HTML, ePUB, XML

 

AUTHORS


Gianluca Borghini (Department of Molecular Medicine, Sapienza Università di RomaRome, Italy)

Gianluca Borghini (BrainSigns srlRome, Italy)

Gianluca Borghini (Neuroelectrical Imaging and BCI Lab, Fondazione Santa Lucia (IRCCS)Rome, Italy)

Pietro Aricò (Department of Molecular Medicine, Sapienza Università di RomaRome, Italy)

Pietro Aricò (BrainSigns srlRome, Italy)

Pietro Aricò (Neuroelectrical Imaging and BCI Lab, Fondazione Santa Lucia (IRCCS)Rome, Italy)

Gianluca Di Flumeri (BrainSigns srlRome, Italy)

Gianluca Di Flumeri (Neuroelectrical Imaging and BCI Lab, Fondazione Santa Lucia (IRCCS)Rome, Italy)

Gianluca Di Flumeri (Department of Anatomical, Histological, Forensic, and Orthopedic Sciences, Sapienza Università di RomaRome, Italy)

Nicolina Sciaraffa (BrainSigns srlRome, Italy)

Nicolina Sciaraffa (Neuroelectrical Imaging and BCI Lab, Fondazione Santa Lucia (IRCCS)Rome, Italy)

Nicolina Sciaraffa (Department of Anatomical, Histological, Forensic, and Orthopedic Sciences, Sapienza Università di RomaRome, Italy)

Alfredo Colosimo (Department of Anatomical, Histological, Forensic, and Orthopedic Sciences, Sapienza Università di RomaRome, Italy)

Maria-Trinidad Herrero (Clinical and Experimental Neuroscience (NiCE-IMIB), School of Medicine, Institute of Aging Research, University of MurciaMurcia, Spain)

Anastasios Bezerianos (Centre for Life Sciences, Singapore Institute for Neurotechnology, National University of SingaporeSingapore, Singapore)

Nitish V. Thakor (Centre for Life Sciences, Singapore Institute for Neurotechnology, National University of SingaporeSingapore, Singapore)

Fabio Babiloni (Department of Molecular Medicine, Sapienza Università di RomaRome, Italy)

Fabio Babiloni (BrainSigns srlRome, Italy)

EDITORIAL INFORMATION

Blind peer review

Editorial Board

Instructions for authors

Time From Submission to Publication: 14 weeks

 

Abstract | Full Text

Inappropriate training assessment might have either high social costs and economic impacts, especially in high risks categories, such as Pilots, Air Traffic Controllers, or Surgeons. One of the current limitations of the standard training assessment procedures is the lack of information about the amount of cognitive resources requested by the user for the correct execution of the proposed task. In fact, even if the task is accomplished achieving the maximum performance, by the standard training assessment methods, it would not be possible to gather and evaluate information about cognitive resources available for dealing with unexpected events or emergency conditions. Therefore, a metric based on the brain activity (neurometric) able to provide the Instructor such a kind of information should be very important. As a first step in this direction, the Electroencephalogram (EEG) and the performance of 10 participants were collected along a training period of 3 weeks, while learning the execution of a new task. Specific indexes have been estimated from the behavioral and EEG signal to objectively assess the users' training progress. Furthermore, we proposed a neurometric based on a machine learning algorithm to quantify the user's training level within each session by considering the level of task execution, and both the behavioral and cognitive stabilities between consecutive sessions. The results demonstrated that the proposed methodology and neurometric could quantify and track the users' progresses, and provide the Instructor information for a more objective evaluation and better tailoring of training programs.