A 15.2-ENOB 5-kHz BW 4.5-μW Chopped CT ΔΣ-ADC for Artifact-Tolerant Neural Recording Front Ends

被引:85
作者
Chandrakumar, Hariprasad [1 ]
Markovic, Dejan [1 ]
机构
[1] Univ Calif Los Angeles, Dept Elect & Comp Engn, Los Angeles, CA 90095 USA
关键词
Artifact tolerant; chopping; common-mode (CM) interference; continuous time (CT); delta sigma; dynamic range; front end; input impedance; linear input range; low power; neural recording; neuromodulation; DEEP-BRAIN-STIMULATION; CLOSED-LOOP; INSTRUMENTATION AMPLIFIER; DESIGN; IMPEDANCE; ARRAY; CMOS;
D O I
10.1109/JSSC.2018.2876468
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Implantable closed-loop neural stimulation is desirable for clinical translation and basic neuroscience research. Neural stimulation generates large artifacts at the recording sites, which saturate existing recording front ends. This paper presents a low-power continuous-time delta-sigma analog to digital converter (ADC), which along with an 8x gain capacitively-coupled chopper instrumentation amplifier (CCIA), realizes a front end that can digitize neural signals from 1 Hz to 5 kHz in the presence of 200-m V-pp differential artifacts and 700-mV(pp) common-mode (CM) artifacts. A modified loop-filter is used in the ADC along with new linearization techniques to significantly reduce power consumption. Fabricated in 40-nm CMOS, the ADC occupies an area of 0.053 mm(2), consumes 4.5 mu W from a 1.2-V supply, has an input impedance of 20 M Omega and bandwidth (BW) of 5 kHz, and achieves a peak signal to noise and distortion ratio (SNDR) of 93.5 dB for a 1.77-V-pp differential input at 1 kHz. The ADC's figure of merit (FOM) (using SNDR) is 184 dB, which is 6 dB higher than the state of the art in high-resolution ADCs. The complete front end occupies an area of 0.113 mm(2), consumes 7.3 mu W from a 1.2-V supply, has a dc input impedance of 1.5 G Omega, input-referred noise of 6.35 mu V-rms in 1 Hz-5 kHz, and total harmonic distortion of -81 dB for a 200-mV(pp) input at 1 kHz, and is immune to 700-mV(pp) CM interference. Compared to front ends intended for closed-loop neural recording, this paper improves the linear input range by 2x, the signal BW by 10x, the dynamic range by 12.6 dB, the FOM by 12.4 dB and remains immune to large CM interference while maintaining comparable power, area, and noise performance.
引用
收藏
页码:3470 / 3483
页数:14
相关论文
共 48 条
  • [31] Design of a Closed-Loop, Bidirectional Brain Machine Interface System With Energy Efficient Neural Feature Extraction and PID Control
    Liu, Xilin
    Zhang, Milin
    Richardson, Andrew G.
    Lucas, Timothy H.
    Van der Spiegel, Jan
    [J]. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS, 2017, 11 (04) : 729 - 742
  • [32] Energy Efficient Low-Noise Neural Recording Amplifier With Enhanced Noise Efficiency Factor
    Majidzadeh, Vahid
    Schmid, Alexandre
    Leblebici, Yusuf
    [J]. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS, 2011, 5 (03) : 262 - 271
  • [33] The Race for the Extra Decibel: A Brief Review of Current ADC Performance Trajectories
    Murmann, Boris
    [J]. IEEE Solid-State Circuits Magazine, 2015, 7 (03): : 58 - 66
  • [34] SOLID-STATE MICROSENSORS FOR CORTICAL NERVE RECORDINGS
    NAJAFI, K
    [J]. IEEE ENGINEERING IN MEDICINE AND BIOLOGY MAGAZINE, 1994, 13 (03): : 375 - 387
  • [35] A Low-Power, High CMRR Neural Amplifier System Employing CMOS Inverter-Based OTAs With CMFB Through Supply Rails
    Ng, Kian Ann
    Xu, Yong Ping
    [J]. IEEE JOURNAL OF SOLID-STATE CIRCUITS, 2016, 51 (03) : 724 - 737
  • [36] Matching Properties of Femtofarad and Sub-Femtofarad MOM Capacitors
    Omran, Hesham
    Alahmadi, Hamzah
    Salama, Khaled N.
    [J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, 2016, 63 (06) : 763 - 772
  • [37] Advances in closed-loop deep brain stimulation devices
    Parastarfeizabadi, Mahboubeh
    Kouzani, Abbas Z.
    [J]. JOURNAL OF NEUROENGINEERING AND REHABILITATION, 2017, 14 : 79
  • [38] A power optimized continuous-time ΔΣ ADC for audio applications
    Pavan, Shanthi
    Krishnapura, Nagendra
    Pandarinathan, Ramalingam
    Sankar, Prabu
    [J]. IEEE JOURNAL OF SOLID-STATE CIRCUITS, 2008, 43 (02) : 351 - 360
  • [39] Rozgic D., 2017, P IEEE BIOM CIRC SYS, P1
  • [40] Brain-controlled interfaces: Movement restoration with neural prosthetics
    Schwartz, Andrew B.
    Cui, X. Tracy
    Weber, Douglas J.
    Moran, Daniel W.
    [J]. NEURON, 2006, 52 (01) : 205 - 220