Papers
10
Total Citations
193
H-Index
5
About
Xiaoqian Mao is a researcher specializing in brain-computer interfaces (BCIs), brain-robot interaction (BRI), and human-machine intelligence integration, with a particular focus on assistive technologies for elderly and disabled populations. His most influential contribution, "Progress in EEG-Based Brain Robot Interaction Systems" (2017, 73 citations), established a comprehensive overview of noninvasive EEG-based BRI technologies, cementing his authority in the field. Building on this foundation, Mao developed a hybrid BRI system fusing P300 and steady-state visual evoked potential (SSVEP) signals with machine intelligence to enhance real-time robot control performance (2019, 46 citations). His pioneering work on SSVEP-based hierarchical architectures for telepresence control of humanoid robots (2016, 37 citations) addressed the complex challenge of enabling full-body robotic movement through brainwave commands. Beyond neural interfaces, Mao has explored alternative human-robot interaction modalities, including Google Glass-based head gesture control and Kinect-driven body gesture navigation, demonstrating a broad systems-level approach to accessible robotics. With over 190 cumulative citations, his research meaningfully advances the goal of empowering individuals with physical limitations through intelligent, intuitive human-robot interaction technologies.
Research Focus
Key Achievements
Top Papers
- 1Progress in EEG-Based Brain Robot Interaction Systems73 citations · 2017
- 2A Brain–Robot Interaction System by Fusing Human and Machine Intelligence46 citations · 2019
- 3
- 4
- 5
- 6Object Extraction in Cluttered Environments via a P300-Based IFCE5 citations · 2017
- 7
- 8
- 9Kinect-based control of a DaNI robot via body gesture3 citations · 2016
- 10