Brain-machine interactive neuromodulation research tool with edge AI computing
Yan Li,
Yingnan Nie,
Zhaoyu Quan,
Han Zhang,
Rui Song,
Hao Feng,
Xi Cheng,
Wei Liu,
Xinyi Geng,
Xinwei Sun,
Yanwei Fu,
Shouyan Wang
Affiliations
Yan Li
Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
Yingnan Nie
Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
Zhaoyu Quan
Engineering Research Center of AI & Robotics, Ministry of Education, Fudan University, Shanghai, China; Academy for Engineering and Technology, Fudan University, Shanghai, China
Han Zhang
Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
Rui Song
Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
Hao Feng
Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
Xi Cheng
Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
Wei Liu
Engineering Research Center of AI & Robotics, Ministry of Education, Fudan University, Shanghai, China; Academy for Engineering and Technology, Fudan University, Shanghai, China
Xinyi Geng
Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
Xinwei Sun
School of Data Science, Fudan University, Shanghai, China
Yanwei Fu
School of Data Science, Fudan University, Shanghai, China
Shouyan Wang
Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China; Corresponding author. Fudan University, 220 Handan Road, Yangpu District, Shanghai, 200433, China.
Closed-loop neuromodulation with intelligence methods has shown great potentials in providing novel neuro-technology for treating neurological and psychiatric diseases. Development of brain-machine interactive neuromodulation strategies could lead to breakthroughs in precision and personalized electronic medicine. The neuromodulation research tool integrating artificial intelligent computing and performing neural sensing and stimulation in real-time could accelerate the development of closed-loop neuromodulation strategies and translational research into clinical application. In this study, we developed a brain-machine interactive neuromodulation research tool (BMINT), which has capabilities of neurophysiological signals sensing, computing with mainstream machine learning algorithms and delivering electrical stimulation pulse by pulse in real-time. The BMINT research tool achieved system time delay under 3 ms, and computing capabilities in feasible computation cost, efficient deployment of machine learning algorithms and acceleration process. Intelligent computing framework embedded in the BMINT enable real-time closed-loop neuromodulation developed with mainstream AI ecosystem resources. The BMINT could provide timely contribution to accelerate the translational research of intelligent neuromodulation by integrating neural sensing, edge AI computing and stimulation with AI ecosystems.
