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We conduct inter-disciplinary research across neuro-engineering, artificial intelligence, robotics, neuroscience, and medicine. We study mainly on physiological signals, such as electromyogram (EMG), electroencephalogram (EEG) and electrocardiogram (ECG), extracting useful information such as motion intentions, sensory processing, emotional states and cognitive processing.
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NING JIANG Distinguished researcher、Doctoral supervisor Professor Jiang and Professor He's team
Dr. Jiangning's main research interests are signal analysis theory of biological signals such as electromyographic, EEG and ECG signals, information mining and specific engineering applications. In the aspect of signal theory, it includes the modeling of human neuromuscular system, the time-frequency analysis of electromyography and electroencephalography in human autonomous activities, and the extraction of neural information. Specific applications include myoelectric control of intelligent prosthesis with multiple degrees of freedom; Application of intelligent rehabilitation robot based on bioelectric signal in the rehabilitation of stroke and paraplegia; Biofeedback technology based on bioelectrical signal; The prevention and monitoring of sports fatigue. He first proposed the framework and algorithm of multi-channel surface electromyographic signal processing, which opened a new direction in the field of electromyographic control prosthetics. In terms of brain-computer interface, the ultra-short delay non-invasive brain-computer interface developed by him can detect people's motor consciousness within 300 milliseconds, which is the core technology of the world's most advanced non-invasive intelligent rehabilitation system. In 2015, Dr. Jiang was selected into the eleventh National Thousand Talents Plan for Young People, and in 2022, he was selected into the Innovative Leading Talents Project of Sichuan Province "Tianfu Emei Plan". In the same year, he and Dong Bilong, director of the National Center for the Elderly, jointly won the Shenzhen High-level Medical Talents Project (10 million yuan).
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