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Hangzhou Dianzi University

5 entries
杭州电子科技大学 China University www.hdu.edu.cn ↗
October 2026

Network Decodes Motor Intent From New Users' EEG

EEG signals vary between people and drift over time, so a brain-computer interface usually has to be recalibrated for each new user. Researchers at Hangzhou Dianzi University built TSMD-Net, which learns from several existing subjects without any data from the new user, then pools what it learned about each one into a single classifier. It reached mean accuracies of 70.21%, 77.82% and 79.53% on three public EEG datasets.
August 2026

Memory Prosthetics Near First-in-Human Trials

Memory prosthetics — closed-loop brain-computer interfaces that decode hippocampal activity and deliver adaptive stimulation — are moving from animal proof-of-concept toward first-in-human trials, according to a review in iScience. The authors argue that chronically implantable systems require co-design of three subsystems that have been treated in isolation: biocompatible electrode interfaces, on-chip neuromorphic computation, and closed-loop control hardware. The review maps neuroscientific findings such as theta-phase tracking, theta-gamma coupling and sharp-wave ripple detection onto engineering specifications for latency, sampling and charge injection, and onto materials requirements for impedance, switching endurance and chronic stability. It also flags where small-cohort clinical results have been over-generalized.
July 2026

Study Involving Hangzhou Dianzi University Achieves 1024-Channel Recording in Pig Cortex

A collaborative study involving authors from Hangzhou Dianzi University and other institutions developed a three-dimensional helical stretchable neural probe and achieved 1024-channel signal acquisition in the pig cerebral cortex. The researchers also report single-unit recordings with long-term stability in the mouse deep brain, while flexible planar microelectrode arrays recorded subcutaneous EMG signals in mice. The probe is fabricated using planar microfabrication followed by thermally driven helical shaping, expanding wiring space and accommodating tissue motion. Mechanical simulations and cyclic stretching tests examined strain mitigation and electrochemical stability, respectively. These device and animal results do not establish long-term performance in humans.
March 2025

DGPDR: Discriminative Geometric Perception Dimensionality Reduction on the Riemannian Manifold for EEG Classification

The study proposes a discriminative, geometry-aware dimensionality reduction method on the Riemannian manifold for symmetric positive definite (SPD) matrices in EEG classification, aimed at boosting discrimination while reducing information loss. On BCI Competition IV Dataset 1 and Dataset 2a, the method improved classification accuracy by 5.0% and 19.38% respectively, indicating robust performance is retained after dimensionality reduction.
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