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Sensors 2016, 16(10), 1582; doi:10.3390/s16101582

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
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)
View Full-Text   |   Download PDF [2873 KB, uploaded 24 September 2016]   |  

Abstract

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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