Zhendong Mu

Jiangxi University of Technology, Tokyo Institute of Technology

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About

Dr. Zhendong Mu is a researcher at the forefront of human-robot interaction and multimodal sensing, whose work bridges the gap between biological signals and machine intelligence. His primary research areas include brain-computer interfaces (BCI), gesture recognition, and sensor fusion. Dr. Mu’s most cited work, "Control method of robot detour obstacle based on EEG" (2021, 11 citations), demonstrates a pioneering approach to enabling robots to navigate around obstacles using electroencephalography (EEG) signals, offering a non-invasive pathway for assistive robotics. His earlier foundational contribution, "Multimodal gesture recognition based on Choquet integral" (2011, 5 citations), introduced a novel fusion technique that integrates data from cameras and 3D accelerometers. By computing optimal fuzzy measures for each sensor modality, this method significantly enhances gesture recognition accuracy, laying groundwork for more intuitive human-machine interfaces. Dr. Mu’s work is notable for its practical application of fuzzy logic to real-world sensor fusion challenges, and his research continues to influence the development of responsive, adaptive robotic systems that can interpret both conscious commands and natural human gestures.