Yi Su
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Yi Su has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Kee S. Moon
Department of Mechanical Engineering, San Diego State University, San Diego, CA 92182, USA
1 shared publication - Sudhamayee Routhu
Department of Electrical and Computer Engineering, San Diego State University, San Diego, CA 92182, USA
1 shared publication - Sung Q. Lee
Department of Mechanical Engineering, San Diego State University, San Diego, CA 92182, USA
1 shared publication - WooSub Youm
Electronics and Telecommunications Research Institute, ICT, 218 Gajeong-ro, Yuseong-gu, Daejeon 34129, Korea
1 shared publication - Yusuf Ozturk
ECE Department, San Diego State University, San Diego, CA
1 shared publication
Latest Publications
- Open Access
A Wireless 32-Channel Implantable Bidirectional Brain Machine Interface
All neural information systems (NIS) rely on sensing neural activity to supply commands and control signals for computers, machines and a variety of prosthetic devices. Invasive systems achieve a high signal-to-noise ratio (SNR) by eliminating the volume conduction problems caused by tissue and bone. An implantable brain machine interface (BMI) using intracortical electrodes provides excellent detection of a broad range of frequency oscillatory activities through the placement of a sensor in direct contact with cortex. This paper introduces a compact-sized implantable wireless 32-channel bidirectional brain machine interface (BBMI) to be used with freely-moving primates. The system is designed to monitor brain sensorimotor rhythms and present current stimuli with a configurable duration, frequency and amplitude in real time to the brain based on the brain activity report. The battery is charged via a novel ultrasonic wireless power delivery module developed for efficient delivery of power into a deeply-implanted system. The system was successfully tested through bench tests and in vivo tests on a behaving primate to record the local field potential (LFP) oscillation and stimulate the target area at the same time.
Open AccessA Wireless 32-Channel Implantable Bidirectional Brain Machine Interface
All neural information systems (NIS) rely on sensing neural activity to supply commands and control signals for computers, machines and a variety of prosthetic devices. Invasive systems achieve a high signal-to-noise ratio (SNR) by eliminating the volume conduction problems caused by tissue and bone. An implantable brain machine interface (BMI) using intracortical electrodes provides excellent detection of a broad range of frequency oscillatory activities through the placement of a sensor in direct contact with cortex. This paper introduces a compact-sized implantable wireless 32-channel bidirectional brain machine interface (BBMI) to be used with freely-moving primates. The system is designed to monitor brain sensorimotor rhythms and present current stimuli with a configurable duration, frequency and amplitude in real time to the brain based on the brain activity report. The battery is charged via a novel ultrasonic wireless power delivery module developed for efficient delivery of power into a deeply-implanted system. The system was successfully tested through bench tests and in vivo tests on a behaving primate to record the local field potential (LFP) oscillation and stimulate the target area at the same time.