Title :
2.5D Heterogeneously Integrated Microsystem for High-Density Neural Sensing Applications
Author :
Po-Tsang Huang ; Shang-Lin Wu ; Yu-Chieh Huang ; Lei-Chun Chou ; Teng-Chieh Huang ; Tang-Hsuan Wang ; Yu-Rou Lin ; Chuan-An Cheng ; Wen-Wei Shen ; Ching-Te Chuang ; Kuan-Neng Chen ; Jin-Chern Chiou ; Wei Hwang ; Ho-Ming Tong
Author_Institution :
Nat. Chiao Tung Univ., Hsinchu, Taiwan
Abstract :
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 μ-probes and embedded through-silicon-via (TSVs) is presented for high-density neural sensing applications. This microsystem is composed of μ-probes with embedded TSVs, 4 dies and a silicon interposer. For capturing 16-channel neural signals, a 24 × 24 μ-probe array with embedded TSVs is fabricated on a 5×5 mm2 chip and bonded on the back side of the interposer. Thus, each channel contains 6 × 6 μ-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 (μ-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 μW for 16-channel neural sensing.
Keywords :
analogue-digital conversion; bioelectric potentials; brain; discrete wavelet transforms; feature extraction; lab-on-a-chip; low-power electronics; medical signal detection; medical signal processing; neurophysiology; silicon; 2.5D heterogeneously integrated biosensing microsystem; Si; area-power-efficient analog-to-digital converters; biopotential acquisition; brain function investigation; configurable discrete wavelet transforms; feature classification; feature extraction; filters; high-density neural sensing applications; lab-on-a-chip; low-power analog front-end circuits; micro-probe array; on-interposer bus design; power 676.3 muW; silicon interposer; sixteen-channel neural signal capturing; through-silicon-via; Analog-digital conversion; CMOS integrated circuits; Discrete wavelet transforms; Low-power electronics; Sensors; Through-silicon vias; 2.5D heterogeneous integration; $mu$-probes; Analog front-end (AFE); configurable discrete wavelet transform (DWT); low-power ADC; neural sensing microsystem; on-interposer bus; through-silicon-via (TSV);
Journal_Title :
Biomedical Circuits and Systems, IEEE Transactions on
DOI :
10.1109/TBCAS.2014.2385061
