Steady state visual evoked potentials-based patient interface under breathing constraints

Abstract : Steady state visual evoked potentials (SSVEP) have been widely utilized in brain computer interfacing (BCI) in last years. In this paper, we present a study exploring the possibilities of SSVEP to manage the communication between patients suffering respiratory disorders and health care providers. By imposing different breathing constraints, five healthy subjects communicated their breathing sensations (breathing well/breathing bad) using a visual frequency tagging paradigm: two visual stimuli with different flickering frequencies (15 and 20 Hz) were simultaneously presented on a screen. Using electroencephalographic (EEG) signals from only three EEG electrodes, two spectral features were extracted by a spatial filter in a sliding window, then classified by an unsupervised algorithm based on k-medians. Average detection success rates were of 70% during breathing discomfort, and of 83% when subjects breathed comfortably. Results suggest that SSVEP-based BCI may be a promising choice to improve patient-caregiver communication in situations of breathing discomfort when verbal communication is difficult
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Xavier Navarro, Sebastien Campion, Fabrizio de Vico Fallani, Pierre Pouget, Thomas Similowski, et al.. Steady state visual evoked potentials-based patient interface under breathing constraints. Neural Engineering (NER), 2015 7th International IEEE/EMBS Conference, 2015, montpellier, France. ⟨10.1109/NER.2015.7146579⟩. ⟨hal-01207793⟩

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