Cognitask: BCI system based on P300 for cognitive therapies

Authors

  • Facundo Barreto Laboratory of Rehabilitation Engineering and Neuromuscular and Sensory Research, Faculty of Engineering, National University of Entre Ríos, Oro Verde, E. R., Argentina https://orcid.org/0000-0002-3154-8015
  • L. Carolina Carrere Laboratory of Rehabilitation Engineering and Neuromuscular and Sensory Research, Faculty of Engineering, National University of Entre Ríos, Oro Verde, E. R., Argentina https://orcid.org/0000-0001-8222-2763
  • Carolina B. Tabernig Laboratory of Rehabilitation Engineering and Neuromuscular and Sensory Research, Faculty of Engineering, National University of Entre Ríos, Oro Verde, E. R., Argentina https://orcid.org/0000-0001-5122-5080

Keywords:

attention, brain-computer interface, cognitive therapy, p300, working memory, BCI2000, Python

Abstract

Brain-computer interfaces can be used within a therapy rehabilitation of cognitive functions such as attention and working memory. This paper presents the design, implementation and preliminary evaluation of Cognitask, a BCI for cognitive rehabilitation. It consists of a modified version of the P300-based speller BCI that allows the presentation of different cognitive tasks. During a task, the patient must complete a certain pattern by ordering a set of images presented disorderly in a visual stimulation matrix. The selection of each image is recognized using the P300 elicited when the patient looks at the matrix where images are flashing and selects one by attending to it. Cognitask consists of four modules. The first acquires and conditions the electroencephalography signal from six electrodes positioned at the fronto-central and parieto-occipital regions. The second processes the signals and translates them into a control signal. The third consists of a user-interface that presents the cognitive task to the patient. The last module consists of a graphical interface for the professional that allows configuration of the session parameters. Two evaluations of Cognitask were performed. The first evaluated the operational functioning of the system using input signals generated by a software. The second evaluated the performance of the system in three healthy volunteers. The results showed that Cognitask had a correct functioning and a maximum average success rate of 92%. These results suggest that Cognitask can be transferred to the clinical setting for evaluation in adults with cognitive deficits.

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Author Biographies

Facundo Barreto, Laboratory of Rehabilitation Engineering and Neuromuscular and Sensory Research, Faculty of Engineering, National University of Entre Ríos, Oro Verde, E. R., Argentina

Facundo S. Barreto received the B.S. degree in Bioengineering from National
University of Entre Ríos, Argentina, in 2021.

L. Carolina Carrere, Laboratory of Rehabilitation Engineering and Neuromuscular and Sensory Research, Faculty of Engineering, National University of Entre Ríos, Oro Verde, E. R., Argentina

L. Carolina Carrere received the B.S. degree in Bioengineering and, then, the Master degree in Biomedical Engineering from the National University of Entre Ríos, Argentina.  She is currently pursuing the Ph.D. degree in engineering at National University of Entre Ríos. She is Researcher at Rehabilitation Engineering and Neuromuscular Research Lab and Assistant Professor of Multivariable Calculus and Differential Equations and Solids Mechanics at the graduate program in Bioengineering at the Faculty of Engineering, National University of Entre Ríos. She has published several scientific articles in bioengineering.

Carolina B. Tabernig, Laboratory of Rehabilitation Engineering and Neuromuscular and Sensory Research, Faculty of Engineering, National University of Entre Ríos, Oro Verde, E. R., Argentina

Carolina B. Tabernig received the B.S. degree in Bioengineering; the Master degree in Biomedical Engineering and the Ph.D. degree in engineering from the National University of Entre Ríos, Argentina. In 2018, she earned the price of better doctoral thesis from Argentinean Society of Bioengineering. She is currently Researcher at Rehabilitation Engineering and Neuromuscular Research Lab and Professor of Rehabilitation and Therapy Equipment at the graduate program in Bioengineering at the Faculty of Engineering, National University of Entre Ríos. She has published many scientific articles in bioengineering and she is reviewer of many international journals of biomedical engineering

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Published

2022-02-02

How to Cite

Barreto, F., Carrere, L. C. ., & Tabernig, C. B. . (2022). Cognitask: BCI system based on P300 for cognitive therapies. IEEE Latin America Transactions, 20(6), 884–890. Retrieved from https://latamt.ieeer9.org/index.php/transactions/article/view/6030

Issue

Vol. 20 No. 6 (2022): Ordinary Issue

Section

Articles