Advancing Brain-Machine Interfaces: High Data Rate Battery-Free Implants

被引：0

作者：

Hasanvand, Aminolah ^{[1
]}

Khaleghi, Ali ^{[1
]}

Beguet, Cyril ^{[2
]}

Wanda, Paul ^{[2
]}

Balasingham, Ilangko ^{[1
]}

机构：

[1] Norwegian Univ Sci & Technol, Dept Elect Syst IES, Trondheim, Norway

[2] Blackrock Microsyst Europe GmbH, Hannover, Germany

来源：

2023 IEEE MTT-S INTERNATIONAL MICROWAVE BIOMEDICAL CONFERENCE, IMBIOC | 2023年

基金：

欧盟地平线“2020”;

关键词：

Implantable wireless brain-machine interfaces; multielectrode arrays; near-field wireless charging; wireless radio frequency backscatter; EFFICIENT;

D O I：

10.1109/IMBIOC56839.2023.10305091

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Implantable wireless brain-machine interfaces (BMI) encounter significant challenges in miniaturization, power consumption, and high data volume. While systems utilizing high resolution microelectrode arrays offer precision brain readout and/or stimulation, achieving high-rate wireless connectivity (32-128 Mbps) consumes excessive power, unsuitable for long-term use with implant batteries. This paper addresses wireless connectivity and power challenges by employing radio frequency backscatter and near-field wireless charging. This approach eliminates transceiver electronics in the implantable, reducing implant power consumption by offloading complexity to off-body reader electronics. It enables wireless powering of implantable neural recording and stimulation chips through magnetic coupling, enabling a fully implantable brain-machine interface. We present preliminary test results for this design scenario, demonstrating the feasibility of our approach.

引用

页码：70 / 72

页数：3

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