Brain-Computer Interface (BCI) has emerged as an enhanced communication and control technology in recent years. In BCI based on electrophysiological characteristics (such as Electroencephalogram, EEG), Motor Imagery (MI) is an important branch that decodes users’ motor intentions for use in clinical rehabilitation, intelligent wheelchair control, c...

EEG of Pre-movement Phase Aids Brain-Computer Interface (BCI) in Recognizing Movement Intentions Background and Research Objectives Brain-Computer Interface (BCI) is a technology that translates human intentions directly through neural signals to control devices, holding extensive application prospects [1]. BCI has the potential to revolutionize va...

Visual Brain-Computer Interface Based on High-Frequency Steady-State Visual Evoked Fields Background Brain-Computer Interface (BCI) technology allows users to control machines by decoding specific brain activity signals. While invasive BCIs excel in capturing high-quality brain signals, their application is mainly limited to clinical settings. Non-...

Patients with Parkinson’s Disease (PD) often experience gait impairments, which severely affect their quality of life. Previous studies have suggested that β-frequency (15-30 Hz) oscillatory activity in the basal ganglia may be associated with gait impairments, but the exact dynamics of these oscillations during the gait process remain unclear. Add...

Learning Inverse Dynamics Using Brain-Inspired Computational Principles on Neuromorphic Hardware Background and Research Motivation In the modern field of robotics, there is great potential for low-latency neuromorphic processing systems enabling autonomous artificial agents. However, the variability and low precision of current hardware foundation...