Integrating EEG and MEG Signals to Improve Motor Imagery Classification in Brain–Computer Interface

• DOI: 10.1142/s0129065718500144
• Publication Date: 2018-04-02T12:19:45Z
• Authors: Marie-Constance C...; Mario Chavez; Denis Schwartz; Laurent Hugueville; Ankit N. Khambhati; Danielle S. Bassett; Fabrizio De Vico ...
• Keywords: Motor Imagery; Modality (human–computer interaction); Magnetoencephalography; Interface (matter)

We adopted a fusion approach that combines features from simultaneously recorded electroencephalogram (EEG) and magnetoencephalogram (MEG) signals to improve classification performances in motor imagery-based brain-computer interfaces (BCIs). applied our group of 15 healthy subjects found significant performance enhancement as compared standard single-modality approaches the alpha beta bands. Taken together, findings demonstrate advantage considering multimodal complementary tools for improving impact noninvasive BCIs.