GCTNet: Graph Convolution Transformer Network for Detecting Major Depressive Disorder Based on EEG Signals Research Background Major Depressive Disorder (MDD) is a prevalent mental illness characterized by significant and persistent low mood, affecting over 350 million people worldwide. MDD is one of the leading causes of suicide, resulting in appr...
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...
Clinical Gastrointestinal Disease Screening Based on the Bionic Artificial Tentacle Method Background Gastrointestinal diseases display a wide range of complex symptoms globally, such as diarrhea, gastrointestinal bleeding, malabsorption, malnutrition, and even neurological dysfunction. These diseases pose significant health challenges and socioeco...
Discussion on Risk-Sensitive Robot Control Based on Self-Attention Mechanism Research Background The kinematics and dynamics in robot control are key factors to ensure the precise completion of tasks. Most robot control schemes rely on various models to achieve task optimization, scheduling, and priority control. However, the dynamic characteristic...
Research Background In rescue missions, to improve search and rescue efficiency, an emerging solution is the use of a combination of electronic backpacks and insects, known as cyborg insects. These insects combine the advantages of biological and electronic technologies, with additional electronic backpacks used for communication, sensing, and cont...
Using Generative Cellular Automata to Study the Chiral Morphogenesis of Gold Background and Objectives Chirality is ubiquitous in nature and can be transferred and amplified between systems through specific molecular interactions and multi-scale couplings. However, the mechanisms of chiral formation and the critical steps during the growth process ...
Accelerating the Discovery of Ionizable Lipids for mRNA Delivery using Machine Learning and Combinatorial Chemistry Research Background To fully realize the potential of mRNA therapies, it is essential to expand the toolkit of lipid nanoparticles (LNPs). However, a key bottleneck in LNP development is identifying new ionizable lipids. Previous stud...
Academic Report: Advanced Optimal Tracking Integrating Neural Critic Technique for Asymmetric Constrained Zero-Sum Games Background and Research Problem In the field of modern control, game theory is the mathematical model that studies the competition and cooperation between intelligent decision-makers, involving an interaction decision problem wit...