4.7 Article Proceedings Paper

2.5D Heterogeneously Integrated Microsystem for High-Density Neural Sensing Applications

期刊

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TBCAS.2014.2385061

关键词

Analog front-end (AFE); configurable discrete wavelet transform (DWT); low-power ADC; neural sensing microsystem; on-interposer bus; through-silicon-via (TSV); 2.5D heterogeneous integration; mu-probes

资金

  1. Ministry of Science and Technology [MOST 102-2220-E-009-062, MOST 103-2221-E-009-202-MY3]
  2. NPIE, Taiwan, R.O.C.
  3. Aim for the Top University Program of the National Chiao Tung University
  4. Ministry of Education, Taiwan, R.O.C.
  5. UST-UCSD International Center of Excellence in Advanced Bioengineering - Taiwan National Science Council I-RiCE Program [NSC-101-2911-I-009-101]

向作者/读者索取更多资源

Heterogeneously integrated and miniaturized neural sensing microsystems are crucial for brain function investigation. In this paper, a 2.5D heterogeneously integrated bio-sensing microsystem with mu-probes and embedded through-silicon-via (TSVs) is presented for high-density neural sensing applications. This microsystem is composed of mu-probes with embedded TSVs, 4 dies and a silicon interposer. For capturing 16-channel neural signals, a 24 x 24 mu-probe array with embedded TSVs is fabricated on a 5 x 5 mm2 chip and bonded on the back side of the interposer. Thus, each channel contains 6 x 6 mu-probes with embedded TSVs. Additionally, the 4 dies are bonded on the front side of the interposer and designed for biopotential acquisition, feature extraction and classification via low-power analog front-end (AFE) circuits, area-power-efficient analog-to-digital converters (ADCs), configurable discrete wavelet transforms (DWTs), filters, and a MCU. An on-interposer bus (mu-SPI) is designed for transferring data on the interposer. Finally, the successful in-vivo test demonstrated the proposed 2.5D heterogeneously integrated bio-sensing microsystem. The overall power of this microsystem is only 676.3 mu W for 16-channel neural sensing.

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