Exploración del Potencial de SSVER-BCI Basado en Medición sin Contacto Utilizando Magnetómetros Bombeados Ópticamente

Brain-computer interfaces (BCIs) based on electroencephalogram (EEG) have been widely applied in health monitoring and neurorehabilitation. However, EEG signals are often attenuated and distorted by tissues like the scalp and skull, limiting EEG-based BCI performance. In contrast, magnetoencephalography (MEG) with contactless measurement offers higher spatial resolution and immunity to volume conduction effects. Traditional MEG systems, based on superconducting quantum interference devices (SQUIDs), are hindered by their size and cost, while optically pumped magnetometers (OPMs) have made OPM-MEG-based BCIs more practical and accessible. Nevertheless, the performance potential of OPM-MEG in BCI applications remains underexplored. To address this, we developed an OPM-MEG BCI system based on steady-state visual evoked response (SSVER) and conducted a systematic evaluation of its performance, highlighting the practical advantages of OPM-MEG in this context. Furthermore, we proposed a fusion framework for OPM-MEG and EEG to further enhance system performance. Offline experiments conducted with 13 participants showed that the developed EEG-BCI achieved an average accuracy of 94.30% and an information transfer rate (ITR) of 122.76 bits/min, the developed OPM-MEG BCI achieved an average accuracy of 98.68% and an ITR of 138.20 bits/min, while the hybrid BCI achieved an average accuracy of 99.72% and an ITR of 159.4 bits/min. The findings highlight the advantages of OPM-MEG for BCI applications and validate the proposed fusion framework as a viable means to enhance decoding performance, thereby extending the potential use cases of OPM-MEG-based systems.