A Wide Dynamic Range Neural Data Acquisition System with High-Precision Delta-Sigma ADC and On-Chip EC-PC Spike Processor

Jian Xu; Anh Tuan Nguyen; Tong Wu; Zhao Wenfeng; Diu Khue Luu; Zhi Yang

doi:10.1109/TBCAS.2020.2972013

A Wide Dynamic Range Neural Data Acquisition System with High-Precision Delta-Sigma ADC and On-Chip EC-PC Spike Processor

Jian Xu, Anh Tuan Nguyen, Tong Wu, Zhao Wenfeng, Diu Khue Luu, Zhi Yang

Biomedical Engineering

Research output: Contribution to journal › Article › peer-review

12 Scopus citations

Abstract

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.

Original language	English (US)
Article number	8985293
Pages (from-to)	425-440
Number of pages	16
Journal	IEEE transactions on biomedical circuits and systems
Volume	14
Issue number	3
DOIs	https://doi.org/10.1109/TBCAS.2020.2972013
State	Published - Jun 1 2020

Bibliographical note

Funding Information:
Manuscript received November 6, 2019; accepted January 25, 2020. Date of publication February 6, 2020; date of current version May 27, 2020. The technology portion of this work was supported in part by National Science Foundation CAREER Award #1845709, in part by the National Institutes of Health under Grant R01-MH111413-01, in part by the MnDRIVE Program at the University of Minnesota, and in part by a gift fund from Nerves Inc., Dallas, TX, USA. The experiment portion of this work was supported in part by Defense Advanced Research Projects Agency under Grants 1198 HR0011-17-2-0060 and N66001-15-C-4016, and NIH R21-NS111214-01. This article was recommended by Associate Editor Dr. Danilo Demarchi. (Corresponding authors: Jian Xu; Zhi Yang.) Jian Xu, Anh Tuan Nguyen, Tong Wu, Diu Khue Luu, and Zhi Yang are with the Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455 USA (e-mail: xuxx1268@umn.edu; nguy2833@umn.edu; wuxx1521@umn.edu; luu00009@umn.edu; yang5029@umn.edu).

Publisher Copyright:
© 2007-2012 IEEE.

Keywords

Data acquisition
EC-PC spike processor
delta-sigma ADC
dynamic range
electrical microstimulation
high precision

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10.1109/TBCAS.2020.2972013

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title = "A Wide Dynamic Range Neural Data Acquisition System with High-Precision Delta-Sigma ADC and On-Chip EC-PC Spike Processor",

abstract = "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.",

keywords = "Data acquisition, EC-PC spike processor, delta-sigma ADC, dynamic range, electrical microstimulation, high precision",

author = "Jian Xu and Nguyen, {Anh Tuan} and Tong Wu and Zhao Wenfeng and Luu, {Diu Khue} and Zhi Yang",

note = "Funding Information: Manuscript received November 6, 2019; accepted January 25, 2020. Date of publication February 6, 2020; date of current version May 27, 2020. The technology portion of this work was supported in part by National Science Foundation CAREER Award #1845709, in part by the National Institutes of Health under Grant R01-MH111413-01, in part by the MnDRIVE Program at the University of Minnesota, and in part by a gift fund from Nerves Inc., Dallas, TX, USA. The experiment portion of this work was supported in part by Defense Advanced Research Projects Agency under Grants 1198 HR0011-17-2-0060 and N66001-15-C-4016, and NIH R21-NS111214-01. This article was recommended by Associate Editor Dr. Danilo Demarchi. (Corresponding authors: Jian Xu; Zhi Yang.) Jian Xu, Anh Tuan Nguyen, Tong Wu, Diu Khue Luu, and Zhi Yang are with the Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455 USA (e-mail: xuxx1268@umn.edu; nguy2833@umn.edu; wuxx1521@umn.edu; luu00009@umn.edu; yang5029@umn.edu). Publisher Copyright: {\textcopyright} 2007-2012 IEEE.",

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AU - Wenfeng, Zhao

AU - Luu, Diu Khue

AU - Yang, Zhi

N1 - Funding Information: Manuscript received November 6, 2019; accepted January 25, 2020. Date of publication February 6, 2020; date of current version May 27, 2020. The technology portion of this work was supported in part by National Science Foundation CAREER Award #1845709, in part by the National Institutes of Health under Grant R01-MH111413-01, in part by the MnDRIVE Program at the University of Minnesota, and in part by a gift fund from Nerves Inc., Dallas, TX, USA. The experiment portion of this work was supported in part by Defense Advanced Research Projects Agency under Grants 1198 HR0011-17-2-0060 and N66001-15-C-4016, and NIH R21-NS111214-01. This article was recommended by Associate Editor Dr. Danilo Demarchi. (Corresponding authors: Jian Xu; Zhi Yang.) Jian Xu, Anh Tuan Nguyen, Tong Wu, Diu Khue Luu, and Zhi Yang are with the Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455 USA (e-mail: xuxx1268@umn.edu; nguy2833@umn.edu; wuxx1521@umn.edu; luu00009@umn.edu; yang5029@umn.edu). Publisher Copyright: © 2007-2012 IEEE.

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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.

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A Wide Dynamic Range Neural Data Acquisition System with High-Precision Delta-Sigma ADC and On-Chip EC-PC Spike Processor

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