SSVEP-based brain–computer interface enabling graded dyspnoea self-report: proof-of-concept study in healthy volunteers
Year: 2026
Type: article
Abstract: BACKGROUND: Mechanically ventilated patients may experience respiratory suffering, which is difficult to assess when verbal communication is impaired. We evaluated the performance of a steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) designed to enable self-reporting of dyspnoea in this context. METHODS: Forty-nine healthy volunteers were studied under five respiratory conditions: normal breathing (NB), inspiratory resistive loading (IRL), inspiratory threshold loading (ITL), CO₂ inhalation (CO₂), and a return to NB as wash-out (NBWO). Respiratory discomfort was evaluated using a visual analogue scale (VAS). Two BCIs models were tested: a detection BCI (D-BCI), designed to discriminate between 'breathing is OK' and 'breathing is difficult', and a quantification BCI in the form of a LED-based analogue scale (LAS), composed of five light-emitting diodes. Visual stimuli were delivered at different frequency sets: 12-15 Hz, 15-20 Hz, and 20-30 Hz for the D-BCI; low frequencies (13-17-19-23-29 Hz) and high frequencies (41-43-47-53-59 Hz) for the LAS. Performance was assessed using receiver operating characteristic (ROC) curves; the area under the ROC curve (AUC) was the primary outcome. RESULTS: Participants reported significant respiratory discomfort during IRL, ITL, and CO₂ conditions in the D-BCI groups, and during ITL and CO₂ in the LAS groups, as reflected by higher dyspnoea VAS scores compared to NB. The best-performing frequency sets were 20-30 Hz for the D-BCI (AUC 0.89 [0.89-0.90]) and low frequencies for the LAS (AUC 0.84 [0.83-0.85]). CONCLUSIONS: This study demonstrates that an SSVEP-based BCI can sucessfully detect and quantify experimentally induced dyspnoea in healthy individuals. Further research is needed to evaluate its clinical applicability for assessing dyspnoea in non-communicative patients.
Institutions: Inserm, Sorbonne Université, Neurophysiologie respiratoire expérimentale et clinique, Université Paris Sciences et Lettres, ESPCI Paris, Assistance Publique – Hôpitaux de Paris, Pitié-Salpêtrière Hospital, Fédération Hospitalo-Universitaire, Paris Center for Microbiome Medicine, Centre National de la Recherche Scientifique, Institut du Cerveau
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,990
OpenAlex ID: W7126180966