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.
School of Electronic Information, Wuhan University, Wuhan 430072, China. yi.su@whu.edu.cn.|Department of Electrical and Computer Engineering, San Diego State University, San Diego, CA 92182, USA. yi.su@whu.edu.cn.
Yi
Y
Su
Department of Electrical and Computer Engineering, San Diego State University, San Diego, CA 92182, USA. sudhamayeeedu@gmail.com.
Sudhamayee
S
Routhu
Department of Mechanical Engineering, San Diego State University, San Diego, CA 92182, USA. kmoon@mail.sdsu.edu.
Kee S
KS
Moon
Electronics and Telecommunications Research Institute (ETRI), Daejeon 34129, Korea. hermann@etri.re.kr.
Sung Q
SQ
Lee
Electronics and Telecommunications Research Institute (ETRI), Daejeon 34129, Korea. wsyoum@etri.re.kr.
WooSub
W
Youm
Department of Electrical and Computer Engineering, San Diego State University, San Diego, CA 92182, USA. yozturk@mail.sdsu.edu.
Yusuf
Y
Ozturk
D015374:Biosensing Techniques / Q000379:methods*; D062207:Brain-Computer Interfaces; D006801:Humans; D012815:Signal Processing, Computer-Assisted; D059629:Signal-To-Noise Ratio; D059015:Wireless Technology
brain-machine interfaces; implantable biomedical sensor; local field potential; stimulation; wireless sensor networks
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