Clinically-Applicable High-BPS Motor Imagery Decoding Enabled by High-Density μECoG Brain-Computer Interfaces

View at publisher
Authors: E. Zhou, Zuyong Fang, Haowen Zhao, Tiger H. Tao, Zhitao Zhou
Cited by: 0
References: 7

Abstract

In this paper, we present a clinically-applicable braincomputer interface (BCI) system using a flexible, highdensity micro-electrocorticography (μECoG) electrode array for high-fidelity signal acquisition. The system enables real-time motor imagery decoding with a high information transfer rate (ITR) and offers advantages in portability, efficiency, and long-term stability. The miniaturized double-layer signal processing unit with a titanium shell exhibits durability and anti-aging performance. Integrated distribution and parallel computing significantly improve real-time capability. In clinical trials, the system allowed participants to play video games and operating assistive devices flexibly.

Fields of Study & Subjects

EEG and Brain-Computer Interfaces Neuroscience and Neural Engineering Muscle activation and electromyography studies

Publication details

Journal / source
IEEE International Conference on Micro Electro Mechanical Systems (MEMS)
Pages
459–461
Publication date
25 January 2026
Language
EN