Literature DB >> 21816172

Cognitive ability assessment by brain-computer interface validation of a new assessment method for cognitive abilities.

P Perego1, A C Turconi, G Andreoni, L Maggi, E Beretta, S Parini, C Gagliardi.   

Abstract

Brain-Computer Interfaces (BCIs) are systems which can provide communication and environmental control to people with severe neuromuscular diseases. The current study proposes a new BCI-based method for psychometric assessment when traditional or computerized testing cannot be used owing to the subject's output impairment. This administration protocol was based on, and validated against, a widely used clinical test (Raven Colored Progressive Matrix) in order to verify whether BCI affects the brain in terms of cognitive resource with a misstatement result. The operating protocol was structured into two phases: phase 1 was aimed at configuring the BCI system on the subject's features and train him/her to use it; during phase 2 the BCI system was reconfigured and the test performed. A step-by-step checking procedure was adopted to verify progressive inclusion/exclusion criteria and the underpinning variables. The protocol was validated on 19 healthy subjects and the BCI-based administration was compared with a paper-based administration. The results obtained by both methods were correlated as known for traditional assessment of a similarly culture free and reasoning based test. Although our findings need to be validated on pathological participants, in our healthy population the BCI-based administration did not affect performance and added a further control of the response due to the several variables included and analyzed by the computerized task.
Copyright © 2011 Elsevier B.V. All rights reserved.

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Year:  2011        PMID: 21816172     DOI: 10.1016/j.jneumeth.2011.06.025

Source DB:  PubMed          Journal:  J Neurosci Methods        ISSN: 0165-0270            Impact factor:   2.390


  7 in total

1.  An eye-tracker controlled cognitive battery: overcoming verbal-motor limitations in ALS.

Authors:  Barbara Poletti; Laura Carelli; Federica Solca; Annalisa Lafronza; Elisa Pedroli; Andrea Faini; Nicola Ticozzi; Andrea Ciammola; Paolo Meriggi; Pietro Cipresso; Dorothée Lulé; Albert C Ludolph; Giuseppe Riva; Vincenzo Silani
Journal:  J Neurol       Date:  2017-05-13       Impact factor: 4.849

2.  The use of P300-based BCIs in amyotrophic lateral sclerosis: from augmentative and alternative communication to cognitive assessment.

Authors:  Pietro Cipresso; Laura Carelli; Federica Solca; Daniela Meazzi; Paolo Meriggi; Barbara Poletti; Dorothée Lulé; Albert C Ludolph; Vincenzo Silani; Giuseppe Riva
Journal:  Brain Behav       Date:  2012-07       Impact factor: 2.708

3.  Assessing residual reasoning ability in overtly non-communicative patients using fMRI.

Authors:  Adam Hampshire; Beth L Parkin; Rhodri Cusack; Davinia Fernández Espejo; Judith Allanson; Evelyn Kamau; John D Pickard; Adrian M Owen
Journal:  Neuroimage Clin       Date:  2012-11-30       Impact factor: 4.881

Review 4.  Brain-Computer Interface for Clinical Purposes: Cognitive Assessment and Rehabilitation.

Authors:  Laura Carelli; Federica Solca; Andrea Faini; Paolo Meriggi; Davide Sangalli; Pietro Cipresso; Giuseppe Riva; Nicola Ticozzi; Andrea Ciammola; Vincenzo Silani; Barbara Poletti
Journal:  Biomed Res Int       Date:  2017-08-23       Impact factor: 3.411

5.  Classification of BCI Users Based on Cognition.

Authors:  N Firat Ozkan; Emin Kahya
Journal:  Comput Intell Neurosci       Date:  2018-05-09

6.  Preliminary psychometric properties of a standard vocabulary test administered using a non-invasive brain-computer interface.

Authors:  Seth Warschausky; Jane E Huggins; Ramses Eduardo Alcaide-Aguirre; Abdulrahman W Aref
Journal:  Front Hum Neurosci       Date:  2022-07-28       Impact factor: 3.473

7.  Brain-Computer Interfaces for Children With Complex Communication Needs and Limited Mobility: A Systematic Review.

Authors:  Silvia Orlandi; Sarah C House; Petra Karlsson; Rami Saab; Tom Chau
Journal:  Front Hum Neurosci       Date:  2021-07-14       Impact factor: 3.169

  7 in total

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