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Open AccessArticle

A Wireless 32-Channel Implantable Bidirectional Brain Machine Interface

1
School of Electronic Information, Wuhan University, Wuhan 430072, China
2
Department of Electrical and Computer Engineering, San Diego State University, San Diego, CA 92182, USA
3
Department of Mechanical Engineering, San Diego State University, San Diego, CA 92182, USA
4
Electronics and Telecommunications Research Institute (ETRI), Daejeon 34129, Korea
*
Authors to whom correspondence should be addressed.
Academic Editors: Octavian Adrian Postolache, Alex Casson and Subhas Mukhopadhyay
Sensors 2016, 16(10), 1582; https://doi.org/10.3390/s16101582
Received: 20 July 2016 / Revised: 17 September 2016 / Accepted: 21 September 2016 / Published: 24 September 2016
(This article belongs to the Special Issue Sensing Technology for Healthcare System)
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. View Full-Text
Keywords: implantable biomedical sensor; brain-machine interfaces; wireless sensor networks; local field potential; stimulation implantable biomedical sensor; brain-machine interfaces; wireless sensor networks; local field potential; stimulation
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MDPI and ACS Style

Su, Y.; Routhu, S.; Moon, K.S.; Lee, S.Q.; Youm, W.; Ozturk, Y. A Wireless 32-Channel Implantable Bidirectional Brain Machine Interface. Sensors 2016, 16, 1582.

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