Xi'an Jiaotong University

Researchers at Xi’an Jiaotong University and collaborating institutions developed E-STACNet to model spatial relationships between EEG channels alongside changes over time. Mean accuracies were 88.00% on BCI Competition IV 2a and 80.62% on Giga DB; DEAP valence and arousal classification reached 96.49% and 96.46%.

Researchers at the Second Affiliated Hospital of Xi'an Jiaotong University in northwestern China and the Key Laboratory of Biomedical Information Engineering of the Ministry of Education have built an in vitro screening platform combining electrospun PLCL with inkjet-printed reduced graphene oxide (rGO) and growth-factor micropatterns. Because it varies conductive, biochemical and topographical cues together, the platform can evaluate printing parameters and electric-field strength in a single system. Under 150 mV/cm direct-current stimulation, PC-12 cells showed more neurite-like outgrowth and better alignment than with no stimulation or at 300 mV/cm.

Researchers writing in npj Biomedical Innovations have proposed DSTF-Net, a framework that decodes steady-state visual evoked potentials (SSVEP) from frontal EEG alone, removing the need for electrodes over the occipital cortex. In cross-subject transfer to 20 new users, including eight brain-injured patients lying supine, it improved decoding accuracy by as much as 33.47% over baseline methods.