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工学院专题学术讲座∣Shaomin Zhang: Invasive Brain-machine Interface Studies at Zhejiang University
时间
9月24日(周四)
11:00- 12:30
地点
西湖大学云栖校区2号楼 411教室
主持
工学院讲席教授 Mohamad Sawan
受众
全体师生
分类
学术与研究
工学院专题学术讲座∣Shaomin Zhang: Invasive Brain-machine Interface Studies at Zhejiang University
时间:2020年9月24日(周四) 上午11:00- 12:30
Time: 11:00-12:30, Thursday, September 24, 2020
地点:西湖大学云栖校区2号楼 411教室
Venue: Room 411, 4th Floor, Building 2, Yunqi Campus
主持人: 西湖大学工学院讲席教授 Mohamad Sawan
Host: Mohamad Sawan, Chair Professor, School of Engineering, Westlake University
主讲嘉宾/Speaker:
Professor Shaomin Zhang
Institute of Brain-machine Interface,
Qiushi Academy for Advanced Studies,
Zhejiang University
主讲人简介/Biography
Prof. Shaomin Zhang received his B.Sc. And Ph.D. in Biomedical Engineering from Zhejiang University in 2002 and 2007, respectively. After that, he became interested in BMIs (Brain-Machine Interfaces) and began to work on Roborat (Animal-robots). During his postdoctoral studies, he worked on the hybrid neural decoder combining Spikes and LFPs (Local field potential). He also took part in setting up the first nonhuman primate BMI Lab in China. From 2012 to 2014, he joined the BrainGate research team led by Prof. John Donoghue at Brown University. After his return, working closely with the neurosurgeons, he made the first clinical study of invasive BMI in China. The participants could control the robotic hand with their ECoG (Electrocorticogram) signals to make the rock-scissors-paper movement.
讲座摘要/Abstract:
Brain-machine interfaces (BMIs) offer a direct path for the brain to communicate with the outside world, mainly using central neural activities to control external devices. In the past decade, the QAAS-BMI team at Zhejiang University has been carrying out invasive BMIs research from animal experiments to clinical studies. We developed several neural decoding algorithms for dealing with the dynamic and nonlinear neural signals when extracting movement intention from the brain. We also demonstrated that the activity of the motor neuron ensemble could be translated into control commands of external devices. With the help from the participants with epilepsy, we further showed that the electrocorticography signals from the motor and sensory cortex could be employed to precisely control an artificial hand in realtime.
*本讲座仅开放校内师生参加
讲座联系人/Contact:
工学院 Sawan 研究团队
陈运萱 chenyunxuan@westlake.edu.cn