GCTNet: A Graph Convolutional Transformer Network for Major Depressive Disorder Detection Based on EEG Signals

Engineering, Electrical Engineering, Information Science, Computer Science, Artificial Intelligence, Medicine, Psychiatry, Neurology, Clinical Psychology, Medical Imaging,
Major Depressive Disorder   EEG   Deep Learning   Phase Locking Value   Contrastive Learning  

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...

A User-Friendly Visual Brain-Computer Interface Based on High-Frequency Steady-State Visual Evoked Fields Recorded by OPM-MEG

A User-Friendly Visual Brain-Computer Interface Based on High-Frequency Steady-State Visual Evoked Fields Recorded by OPM-MEG

Engineering, Electrical Engineering, Information Science, Electronic Information, Computer Science, Automation, Artificial Intelligence, Medicine, Neurology, Medical Imaging, Life Sciences, Cell Biology, Bioengineering, Biophysics,
brain-computer interface   high frequency   steady-state visual evoked field   magnetoencephalography   optically pumped magnetometer  

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-...

Auditory Cues Modulate the Short Timescale Dynamics of STN Activity During Stepping in Parkinson’s Disease

Information Science, Electronic Information, Computer Science, Automation, Artificial Intelligence, Medicine, Neurology, Neurosurgery, Life Sciences, Biophysics,
Parkinson's disease   Gait impairment   Basal ganglia   Auditory cues   Brain stimulation   Hidden Markov model   Alpha rhythms  

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 Kinematics Using Neural Computational Primitives on Neuromorphic Hardware

Engineering, Electrical Engineering, Information Science, Electronic Information, Automation, Artificial Intelligence, Life Sciences, Bioengineering,
inverse kinematics   neural computation   neuromorphic hardware   motor control   spiking neural network  

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...

Tactile Perception: A Biomimetic Whisker-Based Method for Clinical Gastrointestinal Diseases Screening

Engineering, Mechanical Engineering, Information Science, Artificial Intelligence, Medicine, Gastroenterology, Medical Imaging, Life Sciences, Bioengineering,
Gastrointestinal Diseases   Biomimetic Whisker   Tactile Perception   Artificial Intelligence   Screening  

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...

Exploration-based Model Learning with Self-Attention for Risk-Sensitive Robot Control

Engineering, Mechanical Engineering, Information Science, Computer Science, Automation, Artificial Intelligence,
robot control   self-attention   model learning   risk-sensitive   reinforcement learning   dynamics model   kinematics model  

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...