A Low-Power Area-Efficient Compressive Sensing Approach for Multi-Channel Neural Recording

被引：0

作者：

Shoaran, Mahsa ^{[1
]}

Lopez, Mariazel Maqueda ^{[1
]}

Pasupureddi, Vijaya Sankara Rao ^{[1
]}

Leblebici, Yusuf ^{[1
]}

Schmid, Alexandre ^{[1
]}

机构：

[1] Ecole Polytech Fed Lausanne, Swiss Fed Inst Technol, Microelect Syst Lab LSM, CH-1015 Lausanne, Switzerland

来源：

2013 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS) | 2013年

关键词：

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

High-density wireless intracranial neural recording is a promising technology enabling the autonomous diagnosis and therapy of brain diseases. Increasing the number of recording channels is accompanied by the increased amount of data resulting in an unacceptable transmission power. A comprehensive study of possible compressed sensing methods in the context of neural signals has been done, and the compression of signals originating from different channels in the spatial domain has been implemented at the system and circuit levels. Results of the simulations in a UMC 0.18 mu m CMOS technology and subsequent reconstructions show the possibility of compressing with ratios as high as 2.6 with a recovery SNR of at least 10dB using extremely compact and low-power circuits. The power efficiency and limited area per channel confirm the relevance of the proposed approach for multi-channel high-density neural interfaces.

引用

页码：2191 / 2194

页数：4

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