A hybrid BCI for neurofeedback-based attention training: design and preliminary evaluation

Authors

  • Carmen Brigitte Aguilar Gonzales Laboratorio de Ingeniería en Rehabilitación e Investigaciones Neuromusculares y Sensoriales, Facultad de Ingeniería, Universidad Nacional de Entre Ríos, Oro Verde, E. R., Argentina https://orcid.org/0000-0002-6743-4845
  • Augusto Muñoz Laboratory of Engineering in Rehabilitation and Neuromuscular and Sensory Research, Faculty of Engineering, National University of Entre Ríos, Oro Verde https://orcid.org/0000-0002-4717-0109
  • Pedro Paulucci Müller Laboratory of Engineering in Rehabilitation and Neuromuscular and Sensory Research, Faculty of Engineering, National University of Entre Ríos, Oro Verde https://orcid.org/0000-0003-4892-2576
  • Lucía Carolina Carrere Laboratory of Engineering in Rehabilitation and Neuromuscular and Sensory Research, Faculty of Engineering, National University of Entre Ríos, Oro Verde https://orcid.org/0000-0001-8222-2763
  • Carolina Beatriz Tabernig Laboratory of Engineering in Rehabilitation and Neuromuscular and Sensory Research, Faculty of Engineering, National University of Entre Ríos, Oro Verde https://orcid.org/0000-0001-5122-5080

Keywords:

brain-computer interface, Attention deficit hyperactivity disorder, theta/beta ratio, neurofeedback, serious game

Abstract

Neurofeedback therapies based on brain-computer interfaces (BCI) can be used for the rehabilitation of attention deficit hyperactivity disorder (ADHD), as an alternative to conventional treatments. In this paper the design, implementation and preliminary evaluation of Attenti-ON, a hybrid BCI for ADHD rehabilitation, is presented. Attenti-ON uses a Serious Game commanded by the level of attention estimated by the theta/beta ratio of the electroencephalogram as a neurofeedback and also incorporates a manual activity that focuses attention on the required cognitive task., Attenti-ON consists of an user interface and four modules: the first one acquires the electroencephalography signals from prefrontal electrodes, located at Fp1 and Fp2, and conditions them. The second module procceses the signals and generates a valid command for the third module which consists in the Serious Game, developed in Unity. In this module the speed of an animated avatar is modified by the level of attention. The last module is the manual control consisting of a keyboard or joystick. Two evaluations of Attenti-ON were conducted. The first one was to assess the system’s operation by using a signals database. In the second one, the BCI’s closed loop-performance on a healthy volunteer was evaluated and aimed at verifying that the speed of the avatar varied according to the level of attention of the volunteer, which was modified by simulated interference situations. These preliminary results suggest that Attenti-ON could be transfered to the clinical setting for its evaluation for the treatment of ADHD.

Downloads

Download data is not yet available.

Author Biographies

Carmen Brigitte Aguilar Gonzales, Laboratorio de Ingeniería en Rehabilitación e Investigaciones Neuromusculares y Sensoriales, Facultad de Ingeniería, Universidad Nacional de Entre Ríos, Oro Verde, E. R., Argentina

Received the B.S. degree in Bioengineering from National University of Entre Ríos, Argentina, in 2020. In 2019, she obtained the EVC scholarship from the National Interuniversity Council with which she began her career in research. In 2020, she has published her first scientific article in a Bioengineering Journal.

Augusto Muñoz, Laboratory of Engineering in Rehabilitation and Neuromuscular and Sensory Research, Faculty of Engineering, National University of Entre Ríos, Oro Verde

Received the B.S. degree in Bioengineering from National University of Entre Ríos, Argentina, in 2020. He conducted his undergraduate thesis at the Rehabilitation Engineering and Neuromuscular Research Lab, National University of Entre Ríos.

Pedro Paulucci Müller, Laboratory of Engineering in Rehabilitation and Neuromuscular and Sensory Research, Faculty of Engineering, National University of Entre Ríos, Oro Verde

Received the B.S. degree in Bioengineering from National University of Entre Ríos, Argentina, in 2019. In 2018, he obtained the EVC scholarship from the National Interuniversity Council. In 2020, he has published his first scientific article in a Bioengineering Journal.

Lucía Carolina Carrere, Laboratory of Engineering in Rehabilitation and Neuromuscular and Sensory Research, Faculty of Engineering, National University of Entre Ríos, Oro Verde

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 Beatriz Tabernig, Laboratory of Engineering in Rehabilitation and Neuromuscular and Sensory Research, Faculty of Engineering, National University of Entre Ríos, Oro Verde

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.

References

American Psychiatric Association, Guía de consulta de los criterios diagnósticos del DSM-5®. 2013.

S. Cortese et al., «Comparative efficacy and tolerability of medications for attention-deficit hyperactivity disorder in children, adolescents, and adults: a systematic review and network meta-analysis», The Lancet Psychiatry, vol. 5, n.o 9, pp. 727-738, 2018.

T. E. Wilens y N. R. Morrison, «The intersection of attention-deficit/hyperactivity disorder and substance abuse», Curr. Opin. Psychiatry, vol. 24, n.o 4, pp. 280-285, 2011.

M. Arns, C. R. Clark, M. Trullinger, R. deBeus, M. Mack, y M. Aniftos, «Neurofeedback and Attention-Deficit/Hyperactivity-Disorder (ADHD) in Children: Rating the Evidence and Proposed Guidelines», Appl. Psychophysiol. Biofeedback, vol. 45, n.o 2, pp. 39-48, 2020.

U. Leins, G. Goth, T. Hinterberger, C. Klinger, N. Rumpf, y U. Strehl, «Neurofeedback for children with ADHD: A comparison of SCP and Theta/Beta protocols», Appl. Psychophysiol. Biofeedback, vol. 32, n.o 2, pp. 73-88, 2007.

J. Van Doren, M. Arns, H. Heinrich, M. A. Vollebregt, U. Strehl, y S. K. Loo, «Sustained effects of neurofeedback in ADHD: a systematic review and meta-analysis», Eur. Child Adolesc. Psychiatry, vol. 28, n.o 3, pp. 293-305, 2019.

D. van Son, M. de Rover, F. M. De Blasio, W. van der Does, R. J. Barry, y P. Putman, «Electroencephalography theta/beta ratio covaries with mind wandering and functional connectivity in the executive control network», Ann. N. Y. Acad. Sci., vol. 1452, n.o 1, pp. 52-64, 2019.

M. Sagiadinou y A. Plerou, «Brain-Computer Interface Design and Neurofeedback Training in the Case of ADHD Rehabilitation», en Advances in Experimental Medicine and Biology, vol. 1194, Springer, 2020, pp. 217-224.

M. Zhuang, «State-of-the-art non-invasive brain–computer interface for neural rehabilitation: A review», J. Neurorestoratology, vol. 08, n.o 01, pp. 12-25, 2020.

C. G. Lim et al., «A randomized controlled trial of a brain-computer interface based attention training program for ADHD», PLoS One, vol. 14, n.o 5, pp. 1-16, 2019.

J. R. Wolpaw, J. del R. Millán, y N. F. Ramsey, «Brain-computer interfaces: Definitions and principles», en Handbook of Clinical Neurology, vol. 168, Elsevier B.V., 2020, pp. 15-23.

C. Jeunet, F. Lotte, J. M. Batail, P. Philip, y J. A. Micoulaud Franchi, «Using Recent BCI Literature to Deepen our Understanding of Clinical Neurofeedback: A Short Review», Neuroscience, vol. 378, pp. 225-233, 2018.

O.-S. Mehdi y M. A. Lebedev, «Augmenting Attention with Brain–Computer Interfaces», en Brain–Computer Interfaces Handbook Technological and Theoretical Advances, 2018, pp. 549-555.

P. Paulucci, C. C. L, y C. B. Tabernig, «Realistic Video Games for BCI Aimed at Cognitive Rehabilitation Therapies», vol. 24, n.o 3, pp. 67-72, 2020.

C. G. Lim et al., «A Brain-Computer Interface Based Attention Training Program for Treating Attention Deficit Hyperactivity Disorder», PLoS One, vol. 7, n.o 10, 2012.

B. Hillard, A. S. El-Baz, L. Sears, A. Tasman, y E. M. Sokhadze, «Neurofeedback training aimed to improve focused attention and alertness in children with ADHD: A study of relative power of eeg rhythms using custom-made software application», Clin. EEG Neurosci., vol. 44, n.o 3, pp. 193-202, 2013.

J. E. Munoz, D. S. Lopez, J. F. Lopez, y A. Lopez, «Design and creation of a BCI videogame to train sustained attention in children with ADHD», 2015 10th Colomb. Comput. Conf. 10CCC 2015, pp. 194-199, 2015.

X. Qian et al., «Brain-computer-interface-based intervention re-normalizes brain functional network topology in children with attention deficit/hyperactivity disorder», Transl. Psychiatry, vol. 8, n.o 1, 2018.

T. Armstrong, ADD ADHD alternatives in the classroom. Virginia: ASCD, 1999.

G. Pfurtscheller, «The hybrid BCI», Front. Neurosci., vol. 4, n.o April, 2010.

D. W. Zhang et al., «Electroencephalogram Theta/Beta Ratio and Spectral Power Correlates of Executive Functions in Children and Adolescents With AD/HD», J. Atten. Disord., vol. 23, n.o 7, pp. 721-732, 2019.

R. Aldemir, E. Demirci, H. Per, M. Canpolat, S. Özmen, y M. Tokmakçı, «Investigation of attention deficit hyperactivity disorder (ADHD) sub-types in children via EEG frequency domain analysis», Int. J. Neurosci., vol. 128, n.o 4, pp. 349-360, 2018.

F. Fahimi, C. Guan, W. B. Goh, K. K. Ang, C. G. Lim, y T. S. Lee, «Personalized features for attention detection in children with Attention Deficit Hyperactivity Disorder», Proc. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. EMBS, pp. 414-417, 2017.

J. R. Stroop, «Studies of interference in serial verbal reactions», J. Exp. Psychol., vol. 18, n.o 6, pp. 643-662, 1935.

G. Schalk y J. Mellinger, A practical guide to brain-computer interfacing with BCI2000: General-purpose software for brain-computer interface research, data acquisition, stimulus presentation, and brain monitoring. Springer London, 2010.

«Contributions:BCI2000Automation» Available: https://www.bci2000.org/mediawiki/index.php/Contributions:BCI2000Automation (Accessed: September 3, 2020).

F. Fahimi, Z. Zhang, W. B. Goh, T. S. Lee, K. K. Ang, y C. Guan, «Inter-subject transfer learning with an end-to-end deep convolutional neural network for EEG-based BCI», J. Neural Eng., vol. 16, n.o 2, 2019.

«User Reference:SourceFilter» Available: https://www.bci2000.org/mediawiki/index.php/User_Reference:SourceFilter (Accessed: September 3, 2020).

«User Reference:SpectralEstimator» Available: https://www.bci2000.org/mediawiki/index.php/User_Reference:SpectralEstimator (Accessed: September 3, 2020).

W. Du Chang, H. S. Cha, K. Kim, y C. H. Im, «Detection of eye blink artifacts from single prefrontal channel electroencephalogram», Comput. Methods Programs Biomed., vol. 124, pp. 19-30, 2016.

«GUI de MATLAB - MATLAB & Simulink». Available: https://la.mathworks.com/discovery/matlab-gui.html. [Accessed: September 3, 2020]

C. B. Aguilar Gonzales y A. Muñoz, «Puesta en funcionamiento de una interfaz cerebro computadora para rehabilitación del trastorno de déficit de atención con hiperactividad», Universidad Nacional de Entre Ríos, 2020.

&F.-N. Oliveira-Junior, H. L., Casagrandea, W. D., Machadoa, F. S., Delisle-Rodrigueza, D., Souzab, M., Bastos-Filhoa, T., «Towards an EEG-Based BCI System for Neurofeedback Assisted Rehabilitation of Attention Deficit Hyperactivity Disorder», X Congr. Iberoam. Tecnol. Apoyo a la Discapac. (IBERDISCAP 2019), n.o March, pp. 8-11, 2019.

Published

2021-10-08

How to Cite

Aguilar Gonzales, C. B., Muñoz, A., Paulucci Müller, P., Carrere, L. C., & Tabernig, C. B. (2021). A hybrid BCI for neurofeedback-based attention training: design and preliminary evaluation. IEEE Latin America Transactions, 20(5), 746–752. Retrieved from https://latamt.ieeer9.org/index.php/transactions/article/view/5835