Bring mental activity into action! An enhanced online co-adaptive brain-computer interface training protocol
| Autor: | David Steyrl, Ursula Costa, Reinhold Scherer, Eloy Opisso, Gernot Müller-Putz, Josef Faller |
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| Rok vydání: | 2016 |
| Předmět: |
Adult
Male medicine.diagnostic_test Computer science Speech recognition Brain Electroencephalography Middle Aged Mental activity Online Systems ComputingMethodologies_PATTERNRECOGNITION InformationSystems_MODELSANDPRINCIPLES Action (philosophy) Human–computer interaction Brain-Computer Interfaces Task Performance and Analysis medicine Humans Female Protocol (object-oriented programming) Communication channel Brain–computer interface Aged |
| Zdroj: | EMBC |
| ISSN: | 2694-0604 |
| Popis: | Non-stationarity and inherent variability of the noninvasive electroencephalogram (EEG) makes robust recognition of spontaneous EEG patterns challenging. Reliable modulation of EEG patterns that a BCI can robustly detect is a skill that users must learn. In this paper, we present a novel online co-adaptive BCI training paradigm. The system autonomously screens users for their ability to modulate EEG patterns in a predictive way and adapts its model parameters online. Results of a supporting study in seven first-time BCI users with disability are very encouraging. Three of 7 users achieved online accuracy > 70% for 2-class BCI control after 24 minutes of training. Online performance in 6 of 7 users was significantly higher than chance level. Online control was based on one single bipolar EEG channel. Beta band activity carried most discriminant information. Our fully automatic co-adaptive online approach allows to evaluate whether user benefit from current BCI technology within a reasonable timescale. |
| Databáze: | OpenAIRE |
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