Journal Article

The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users

Schneider, Christoph, Saeedi, Sareh, Tonin, Luca, Perdikis, Serafeim, Millán, José del R.

2018

Overview

This work aims at corroborating the importance and efficacy of mutual learning in motor imagery (MI) brain-computer interface (BCI) by leveraging the insights obtained through our participation in the BCI race of the Cybathlon event. We hypothesized that, contrary to the popular trend of focusing mostly on the machine learning aspects of MI BCI training, a comprehensive mutual learning methodology that reinstates the three learning pillars (at the machine, subject, and application level) as equally significant could lead to a BCI-user symbiotic system able to succeed in real-world scenarios such as the Cybathlon event. Two severely impaired participants with chronic spinal cord injury (SCI), were trained following our mutual learning approach to control their avatar in a virtual BCI race game. The competition outcomes substantiate the effectiveness of this type of training. Most importantly, the present study is one among very few to provide multifaceted evidence on the efficacy of subject learning during BCI training. Learning correlates could be derived at all levels of the interface-application, BCI output, and electroencephalography (EEG) neuroimaging-with two end-users, sufficiently longitudinal evaluation, and, importantly, under real-world and even adverse conditions.

• Publisher: Public Library of Science,Public Library of Science (PLoS)
• Subject: Adaptation / Artificial intelligence / Biology and Life Sciences / Communication / Computational biology / Computer and Information Sciences / EEG / Electroencephalography / Engineering and Technology / Engineering schools / Fuzzy logic / Human-computer interaction / Human-computer interface / Hypotheses / Learning algorithms / Machine learning / Medical imaging / Medicine and Health Sciences / Mental task performance / Motor skill learning / Neuroimaging / Neurology / Parameter estimation / People and Places / Physical Sciences / Race / Research and Analysis Methods / Social Sciences / Software / Spinal cord injuries / Technology application / Training