Zhi-Qiang Zhang
Papers
1
Total Citations
1
H-Index
1
About
Zhi-Qiang Zhang is a leading researcher at the intersection of computational neuroscience and rehabilitative robotics, with a primary focus on spiking neural networks (SNNs) for human-robot interaction. His work addresses a critical challenge in wearable robotics: enabling energy-efficient, real-time neural processing that can be deployed on neuromorphic hardware. In his highly cited 2025 systematic review, Zhang provides the first comprehensive synthesis of SNN applications in rehabilitative wearable robotics, mapping out how these biologically-plausible networks can decode neural signals and control assistive devices with unprecedented efficiency. This seminal work, already garnering significant attention, establishes a foundational framework for the field. Zhang’s contributions are particularly notable for bridging the gap between theoretical neuromorphic computing and practical rehabilitation engineering, offering a roadmap for developing next-generation prosthetics and exoskeletons that can adapt to users in real-time. His research promises to transform how we design intelligent assistive technologies, making them more responsive, less power-hungry, and ultimately more accessible to patients with motor impairments.
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