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Zonghai Huang

4 accepted papers

2026

A Multisensory Neurofeedback–Based Immersive BCI Paradigm for Emotion Regulation

ICRA 2026poster

Enhancing brain activation efficiency is crucial in developing brain computer interface (BCI) paradigm for cognitive rehabilitation. However, the existing BCI paradigms mostly achieved limited sensory-activation without sufficient feedback of mind and body, significantly limiting the user engagement…

Cited by 0Scholar
2026

A Novel Human-Machine Dual-Task Gaming Framework for Visual-Attention Training

ICRA 2026poster

Efficient brain functional training with rehabilitation robots has been an important and challenging topic in the human-machine interaction (HMI) field. Adjusting the interaction and gaming behaviors between human and machine to effectively activate the brain’s functional behavior is still a substan…

Cited by 0Scholar
2026

A Spatiotemporal Brain Activity Visualization and Assessment Framework for Human-Robot Cognitive Interaction Training

ICRA 2026poster

Accurately assessing brain activity to modulate training parameters online is crucial for improving the human-robot cognitive interaction (HRCI) performance in closed-loop brain training. The major challenge for this technique lies in how to accurately model and characterize the intrinsic behavior o…

Cited by 0Scholar
2025

Engaging Mind and Body: An Immersive BCI Paradigm with Motion-Panoramic Virtual Reality

IROS 2025

Brain-computer interface (BCI) is an important technology in developing the closed-loop brain training system for cognitive functional rehabilitation. Most of existing BCI paradigms have not ensured desired immersiveness of mind and body, thereby limiting participants’ engagement in training tasks.

Cited by 0SourceScholar