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.
Highlights
Neuroplasticity is an intrinsic property of the human central nervous system (CNS) and represents the ability of actively adapting to environmental pressures, physiological changes and experiences [1].Neuroplasticity occurs either during normal brain development when people begin to process new sensory information or as an adaptive mechanism to reform neurological paths due to brain or spinal cord injury (SCI)
The system can provide 32-channel of brain activity recording from implanted electrodes and four channels of stimulation to the brain or spinal cord based on a protocol submitted wirelessly to the device
The stimulation module we developed may not outperform some state of the art stimulators; as an integrated system with a compact size and multi-functionalities, the stimulation module is adequate as part of the bidirectional brain machine interface (BBMI) system
Summary
Yi Su 1,2,∗ , Sudhamayee Routhu 2 , Kee S. Lee 4 , WooSub Youm 4 and Yusuf Ozturk 2,∗. Academic Editors: Octavian Adrian Postolache, Alex Casson and Subhas Mukhopadhyay. Received: July 2016; Accepted: September 2016; Published: 24 September 2016
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