Isabell Kiral-Kornek, Subhrajit Roy, et al.
EBioMedicine
Deep learning technology is uniquely suited to analyse neu-rophysiological signals such as the electroencephalogram (EEG) and local field potentials (LFP) and promises to outperform traditional machine-learning based classification and feature extraction algorithms. Furthermore, novel cognitive com-puting platforms such as IBM's recently introduced neuro-morphic TrueNorth chip allow for deploying deep learning techniques in an ultra-low power environment with a mini-mum device footprint. Merging deep learning and TrueNorth technologies for real-Time analysis of brain-Activity data at the point of sensing will create the next generation of wear-ables at the intersection of neurobionics and artificial intel-ligence.
Isabell Kiral-Kornek, Subhrajit Roy, et al.
EBioMedicine
Jianbin Tang, Benjamin Scott Mashford, et al.
IEEE GRSL
Aurélie Névéol, Antonio Jose Jimeno Yepes, et al.
LREC 2018
Antonio Jose Jimeno Yepes, Andrew MacKinlay
ALTA 2016