Guoqian Jiang
Papers
1
Total Citations
12
H-Index
1
About
Dr. Guoqian Jiang is a leading researcher in biomedical signal processing and human–machine interaction, with a primary focus on developing intelligent systems for motor rehabilitation and assistive technologies. His most-cited work, “E²FNet: An EEG- and EMG-Based Fusion Network for Hand Motion Intention Recognition” (2024), addresses a critical challenge in rehabilitation robotics: the limitations of single-signal approaches. By designing a deep fusion network that integrates electroencephalography (EEG) and electromyography (EMG) signals, Dr. Jiang significantly improves the accuracy and robustness of hand motion intention decoding. This work, already garnering 12 citations shortly after publication, demonstrates his ability to tackle real-world clinical problems—such as poor signal quality in limb disorder patients—through innovative multi-modal architectures. His contributions are pivotal for advancing brain–computer interfaces and neuroprosthetics, offering more reliable control for assistive devices. Dr. Jiang’s research stands at the intersection of neural engineering and deep learning, providing practical solutions that directly impact the quality of life for individuals with motor impairments.
Research Focus
Key Achievements
Top Papers
- 1