The 2017 and 2018 Iranian Brain-Computer Interface Competitions

Nasser Samadzadeh Aghdam; Mohammad Hassan Moradi; Mohammad Bagher Shamsollahi; Ali Motie Nasrabadi; Seyed Kamaledin Setarehdan; Vahid Shalchyan; Farhad Faradji; Bahador Makkiabadi

doi:10.4103/jmss.JMSS_65_19

The 2017 and 2018 Iranian Brain-Computer Interface Competitions

J Med Signals Sens. 2020 Jul 3;10(3):208-216. doi: 10.4103/jmss.JMSS_65_19. eCollection 2020 Jul-Sep.

Authors

Nasser Samadzadeh Aghdam¹, Mohammad Hassan Moradi², Mohammad Bagher Shamsollahi³, Ali Motie Nasrabadi⁴, Seyed Kamaledin Setarehdan⁵, Vahid Shalchyan⁶, Farhad Faradji⁷, Bahador Makkiabadi¹

Affiliations

¹ Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
² Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran.
³ Department of Electrical Engineering, Biomedical Signal and Image Processing Laboratory, Sharif University of Technology, Tehran, Iran.
⁴ Department of Biomedical Engineering, Faculty of Engineering, Shahed University, Tehran, Iran.
⁵ Control and Intelligent Processing Centre of Excellence, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.
⁶ Department of Biomedical Engineering, School of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran.
⁷ Department of Electrical Engineering, K. N. Toosi University of Technology, Tehran, Iran.

Abstract

This article summarizes the first and second Iranian brain-computer interface competitions held in 2017 and 2018 by the National Brain Mapping Lab. Two 64-channel electroencephalography (EEG) datasets were contributed, including motor imagery as well as motor execution by three limbs. The competitors were asked to classify the type of motor imagination or execution based on EEG signals in the first competition and the type of executed motion as well as the movement onset in the second competition. Here, we provide an overview of the datasets, the tasks, the evaluation criteria, and the methods proposed by the top-ranked teams. We also report the results achieved with the submitted algorithms and discuss the organizational strategies for future campaigns.

Keywords: Brain–computer interface; electroencephalography; motor execution; motor imagery; movement onset.