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Training leads to increased auditory brain–computer interface performance of end-users with motor impairments

Halder, S and Käthner, I and Kübler, A (2016) 'Training leads to increased auditory brain–computer interface performance of end-users with motor impairments.' Clinical Neurophysiology, 127 (2). 1288 - 1296. ISSN 1388-2457

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Objective Auditory brain–computer interfaces are an assistive technology that can restore communication for motor impaired end-users. Such non-visual brain–computer interface paradigms are of particular importance for end-users that may lose or have lost gaze control. We attempted to show that motor impaired end-users can learn to control an auditory speller on the basis of event-related potentials. Methods Five end-users with motor impairments, two of whom with additional visual impairments, participated in five sessions. We applied a newly developed auditory brain–computer interface paradigm with natural sounds and directional cues. Results Three of five end-users learned to select symbols using this method. Averaged over all five end-users the information transfer rate increased by more than 1800% from the first session (0.17 bits/min) to the last session (3.08 bits/min). The two best end-users achieved information transfer rates of 5.78 bits/min and accuracies of 92%. Conclusions Our results show that an auditory BCI with a combination of natural sounds and directional cues, can be controlled by end-users with motor impairment. Training improves the performance of end-users to the level of healthy controls. Significance To our knowledge, this is the first time end-users with motor impairments controlled an auditory brain–computer interface speller with such high accuracy and information transfer rates. Further, our results demonstrate that operating a BCI with event-related potentials benefits from training and specifically end-users may require more than one session to develop their full potential.

Item Type: Article
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Elements
Date Deposited: 17 Aug 2020 13:10
Last Modified: 17 Aug 2020 14:15

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