TY - JOUR
T1 - A Wide Dynamic Range Neural Data Acquisition System with High-Precision Delta-Sigma ADC and On-Chip EC-PC Spike Processor
AU - Xu, Jian
AU - Nguyen, Anh Tuan
AU - Wu, Tong
AU - Wenfeng, Zhao
AU - Luu, Diu Khue
AU - Yang, Zhi
N1 - Publisher Copyright:
© 2007-2012 IEEE.
PY - 2020/6/1
Y1 - 2020/6/1
N2 - A high-performance, wide dynamic range, fully-integrated neural interface is one key component for many advanced bidirectional neuromodulation technologies. In this paper, to complement the previously proposed frequency-shaping amplifier (FSA) and high-precision electrical microstimulator, we will present a proof-of-concept design of a neural data acquisition (DAQ) system that includes a 15-bit, low-power Delta-Sigma analog-to-digital converter (ADC) and a real-time spike processor based on one exponential component-polynomial component (EC-PC) algorithm. High-precision data conversion with low power consumption and small chip area is achieved by employing several techniques, such as opamp-sharing, multi-bit successive approximation (SAR) quantizer, two-step summation, and ultra-low distortion data weighted averaging (DWA). The on-chip EC-PC engine enables low latency, automatic detection, and extraction of spiking activities, thus supporting closed-loop control, real-time data compression and /or neural information decoding. The prototype chip was fabricated in a 0.13 μm CMOS process and verified in both bench-top and In-Vivo experiments. Bench-top measurement results indicate the designed ADC achieves a peak signal-to-noise and distortion ratio (SNDR) of 91.8 dB and a dynamic range of 93.0 dB over a 10 kHz bandwidth, where the total power consumption of the modulator is only 20 μW at 1.0 V supply, corresponding to a figure-of-merit (FOM) of 31.4fJ /conversion-step. In In-Vivo experiments, the proposed DAQ system has been demonstrated to obtain high-quality neural activities from a rat's motor cortex and also greatly reduce recovery time from system saturation due to electrical microstimulation.
AB - A high-performance, wide dynamic range, fully-integrated neural interface is one key component for many advanced bidirectional neuromodulation technologies. In this paper, to complement the previously proposed frequency-shaping amplifier (FSA) and high-precision electrical microstimulator, we will present a proof-of-concept design of a neural data acquisition (DAQ) system that includes a 15-bit, low-power Delta-Sigma analog-to-digital converter (ADC) and a real-time spike processor based on one exponential component-polynomial component (EC-PC) algorithm. High-precision data conversion with low power consumption and small chip area is achieved by employing several techniques, such as opamp-sharing, multi-bit successive approximation (SAR) quantizer, two-step summation, and ultra-low distortion data weighted averaging (DWA). The on-chip EC-PC engine enables low latency, automatic detection, and extraction of spiking activities, thus supporting closed-loop control, real-time data compression and /or neural information decoding. The prototype chip was fabricated in a 0.13 μm CMOS process and verified in both bench-top and In-Vivo experiments. Bench-top measurement results indicate the designed ADC achieves a peak signal-to-noise and distortion ratio (SNDR) of 91.8 dB and a dynamic range of 93.0 dB over a 10 kHz bandwidth, where the total power consumption of the modulator is only 20 μW at 1.0 V supply, corresponding to a figure-of-merit (FOM) of 31.4fJ /conversion-step. In In-Vivo experiments, the proposed DAQ system has been demonstrated to obtain high-quality neural activities from a rat's motor cortex and also greatly reduce recovery time from system saturation due to electrical microstimulation.
KW - Data acquisition
KW - EC-PC spike processor
KW - delta-sigma ADC
KW - dynamic range
KW - electrical microstimulation
KW - high precision
UR - http://www.scopus.com/inward/record.url?scp=85079073365&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85079073365&partnerID=8YFLogxK
U2 - 10.1109/TBCAS.2020.2972013
DO - 10.1109/TBCAS.2020.2972013
M3 - Article
C2 - 32031949
AN - SCOPUS:85079073365
SN - 1932-4545
VL - 14
SP - 425
EP - 440
JO - IEEE transactions on biomedical circuits and systems
JF - IEEE transactions on biomedical circuits and systems
IS - 3
M1 - 8985293
ER -