EEG Channel Localization and Selection via Training with Noise Injection for BCI Applications.

Electroencephalography (EEG) is crucial for monitoring brain activity in neuroscience and clinical applications. However, the multitude of channels recorded by scalp electrodes poses challenges, including impractical usage and high model complexity. This paper addresses the challenges of high dimensionality in EEG data and introduces an innovative EEG channel selection algorithm, LSvT-NI, based on model training and noise injection, achieving substantial reductions in channels, model size, and complexity while maintaining high classification accuracy.

One-time-implantable spinal cord stimulation system prototype.

A prototype of a one-time-implantable spinal cord stimulation (SCS) system using wireless power and data-transmission techniques is presented in this paper. The power of the implant is induced by wireless coil coupling, and duplex amplitude-shift keying-load-shift keying wireless communication is used so that digital packets can be transmitted by the same inductive link. The proposed novel ASK demodulator attains high demodulation performance and small area without using any resistors and capacitors.