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In the pursuit to clarify the concept of “BCI illiteracy”, we investigated the possibilities of attaining basic binary (yes/no) communication via brain‑computer interface (BCI). We tested four BCI paradigms: steady‑state visual evoked potentials (SSVEP), tactile, visual, and auditory evoked potentials (P300). The proposed criterion for assessing for the possibility of communication are based on the number of correct choices obtained in a given BCI paradigm after a short calibration session, without prior training. In this study users answered 20 simple “yes/no” questions. Fourteen or more correct answers rejected the null hypothesis of random choices at P=0.05. All of the 30 healthy volunteers were able to attain above‑chance choices in at least one of the four paradigms. Additionally, we tested the system in clinical settings on a patient recovering from disorders of consciousness, achieving successful communication in 2 out of 3 paradigms. In light of these facts, after a review of the sparse literature, and in the interest of motivating further research, we propose a paraphrase of de Finetti’s provocative statement: “BCI illiteracy does not exist”.
Brain Computer Interface (BCI) is a system that al‑ lows communication without the mediation of muscles, using only brain waves. This technology passed from science-fiction to the laboratory decades ago, but real world applications, in fields from gaming and military to assistive technologies and consciousness assess‑ ment, are still operating at the proof of concept level. To change this landscape, building on a strong academic background, BrainTech Ltd. (http://braintech.pl) is pur‑ suing a project to create stable, robust, and usable BCI technologies, ready for the above mentioned real world applications. Software includes stable implementations of the major paradigms: P300 evoked potentials (visu‑ al and auditory), steady-state visual evoked potentials (SSVEP), and motor imagery. Features aimed at increas‑ ing productivity in both academic and practical appli‑ cations include the “BCI Control Panel”(*), which helps either the experimenter or caregiver in the setup and online control of the BCI session by displaying, for ex‑ ample, electrode impedances and online performance. Several indicators like accuracy or information transfer rate can be stored together with the signal, facilitating offline scientific analysis. Hardware systems include: (1) comfortable headcap with water-based electrodes, offering high quality signal without application of con‑ ducting gel, which normally requires washing hair after each EEG session, (2) 8-channel 24-bit wireless EEG am‑ plifier, offering online monitoring of electrode contacts and Gigaohm input impedance, either integrated into the headcap or offering connectors for standard EEG electrodes, (3) next generation of the “BCI Appliance”* – a dedicated hardware renderer for flexible stimuli for high-frequency SSVEP, first presented at CeBIT in 2012 as a base for the fastest BCI presented at this fair. (*“BCI Control Panel” and “BCI Appliance” are trademarks filed for protection to the Polish Patent Office). Demo of the discussed systems will be available in the presentation accompanying the Conference. The lecture will briefly discuss new research possibilities opened by the “BCI Appliance”, comfort of application of the novel EEG headcap, and facilitation of both real world BCI applica‑ tions and scientific research brought about by the pre‑ sented software.
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