An End-to-End Implanted Brain-Machine Interface Antenna System Performance Characterizations and Development

作者：Song Lingnan^*; Rahmat Samii Yahya

来源：IEEE Transactions on Antennas and Propagation, 2017, 65(7): 3399-3408.

DOI：10.1109/TAP.2017.2700163

• Antenna noise analysis
• brain-machine interface (BMI) antennas
• near-field inductive coupling
• RFID backscattering
• small loop antennas
• specific absorption rate (SAR)

Brain-machine interface (BMI) is a multidisciplinary field that has been recently developed in an attempt to help restore functionalities for paralyzed individuals. One of the key components for the implementation of a wireless BMI necessitates unique designs for both the internal brain and external head antennas. In this paper, we initially revisited the design of an optimized 1-mm(3) implantable antenna transferring power and data with a reduced size low profile external reader antenna by utilizing radio-frequency identification (RFID)-inspired backscattering. Detailed computational assessments and specific absorption rate evaluations are performed. Prototypes were characterized in terms of link efficiency through a realized RFID link with up to -25 dB link efficiency. The noise analysis for antennas in biological systems was performed using two novel absorption-noise models. And finally a channel capacity estimation was performed, proving that the BMI antenna link could support up to 100 recording channels. An end-to-end BMI antenna system characterization is detailed in this paper for multichannel implanted neural recording applications.

• 出版日期2017-7