Author/Authors :
Samadzadeh Aghdam, Nasser Department of Medical Physics and Biomedical Engineering - School of Medicine - Tehran University of Medical Sciences, Tehran, Iran , Moradi, Mohammad Hassan Department of Biomedical Engineering - Amirkabir University of Technology, Tehran, Iran , Shamsollahi, Mohammad Bagher Department of Electrical Engineering - Biomedical Signal and Image Processing Laboratory - Sharif University of Technology, Tehran, Iran , Motie Nasrabadi, Ali Department of Biomedical Engineering - Faculty of Engineering - Shahed University, Tehran, Iran , Setarehdan, Kamaledin Control and Intelligent Processing Centre of Excellence - School of Electrical and Computer Engineering - College of Engineering - University of Tehran, Tehran, Iran , Shalchyan, Vahid Department of Biomedical Engineering - School of Electrical Engineering - Iran University of Science and Technology, Tehran, Iran , Faradji, Farhad Department of Electrical Engineering - K. N. Toosi University of Technology, Tehran, Iran , Makkiabadi, Bahador Department of Medical Physics and Biomedical Engineering - School of Medicine - Tehran University of Medical Sciences, 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
