An Efficient and Compact Compressed Sensing Microsystem for Implantable Neural Recordings

作者：Zhang Jie^*; Suo Yuanming; Mitra Srinjoy; Chin Sang; Hsiao Steven; Yazicioglu Refet Firat; Tran Trac D; Etienne Cummings Ralph

来源：IEEE Transactions on Biomedical Circuits and Systems, 2014, 8(4): 485-496.

DOI：10.1109/TBCAS.2013.2284254

• Compressed sensing (CS)
• dictionary learning
• hardware implementation
• multi-electrode arrays (MEA)

Multi-Electrode Arrays (MEA) have been widely used in neuroscience experiments. However, the reduction of their wireless transmission power consumption remains a major challenge. To resolve this challenge, an efficient on-chip signal compression method is essential. In this paper, we first introduce a signal-dependent Compressed Sensing (CS) approach that outperforms previous works in terms of compression rate and reconstruction quality. Using a publicly available database, our simulation results show that the proposed system is able to achieve a signal compression rate of 8 to 16 while guaranteeing almost perfect spike classification rate. Finally, we demonstrate power consumption measurements and area estimation of a test structure implemented using TSMC 0.18 mu m process. We estimate the proposed system would occupy an area of around 200 mu m x 300 mu m per recording channel, and consumes 0.27 mu W operating at 20 KHz.

• 出版日期2014-8