An efficient and compact compressed sensing microsystem for implantable neural recordings

• Published in: IEEE transactions on biomedical circuits and systems 2014-08, Vol.8 (4), p.485-496
• Main Authors: Jie Zhang, Yuanming Suo, Mitra, Srinjoy, Chin, Sang, Hsiao, Steven, Yazicioglu, Refet Firat, Tran, Trac D., Etienne-Cummings, Ralph
• Format: Article
• Language: English
• Subjects: Animals; Compressed sensing; Compressed sensing (CS); Dictionaries; dictionary learning; Electrodes, Implanted; Electronics, Medical - instrumentation; Equipment Design; Estimation; hardware implementation; multi-electrode arrays (MEA); Neurons - physiology; Sensors; Shape; System-on-chip; Telemetry; Vectors
• ISSN: 1932-4545; 1940-9990
• DOI: 10.1109/TBCAS.2013.2284254

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 μm process. We estimate the proposed system would occupy an area of around 200 μm ×300 μm per recording channel, and consumes 0.27 μW operating at 20 KHz .