A 0.01-mm<sup>2</sup> Mostly Digital Capacitor-Less AFE for Distributed Autonomous Neural Sensor Nodes

Huang, Jiannan; Laiwalla, Farah; Cui, Lingxiao; Leung, Vincent; Nurmikko, A. V.; Mercier, Patrick P.

doi:10.1109/lssc.2019.2894932

Cited by 35 publications

(8 citation statements)

References 10 publications

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“…The silicon footprint is four times smaller than the smallest AC-coupled front-end reported, and it is comparable to the recent DC-coupled ones. The power consumption is the lowest [7] JSSC'15 [13] JSSC'17 [9] JSSC'18 [4] SSCL'18 [14] JSSC'18 [8] TBCAS'19 [15] TBCAS'20 [10] This work 2 On-chip decimation filter. 3 Off-chip decimation filter.…”

Section: Measurement Resultsmentioning

confidence: 99%

An AC-Coupled Wideband Neural Recording Front-End With Sub-1 mm²×fJ/conv-step Efficiency and 0.97 NEF

Uran

Leblebici

Emami

et al. 2020

IEEE Solid-State Circuits Lett.

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This paper presents an energy-and-area-efficient ACcoupled front-end for multichannel recording of wideband neural signals.The proposed unit conditions local field and action potentials using an inverter-based capacitively-coupled low-noise amplifier, followed by a perchannel 10-bit asynchronous SAR ADC. The adaptation of unit-length capacitors minimizes the ADC area and relaxes the amplifier gain so that small coupling capacitors can be integrated. The prototype in 65nm CMOS achieves 4× smaller area and 3× higher energy-area efficiency compared to the state of the art with 164 µm×40 µm footprint and 0.78 mm 2 ×fJ/conv-step energy-area figure of merit. The measured 0.65 µW power consumption and 3.1 µVrms input-referred noise within 1Hz-10kHz bandwidth correspond to a noise efficiency factor of 0.97. Index Terms-AC coupling, front-end, inverter-based amplifier, monotonic switching, neural recording, successive approximation register analog-to-digital-converter, unit length capacitor.

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Section: Measurement Resultsmentioning

confidence: 99%

An AC-Coupled Wideband Neural Recording Front-End With Sub-1 mm²×fJ/conv-step Efficiency and 0.97 NEF

Uran

Leblebici

Emami

et al. 2020

IEEE Solid-State Circuits Lett.

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“…A proof-ofconcept experiment of the distributed sensor system (Figure 12A) is completed on the cortex by microminiaturization of the device "neurograin" as a network node but maintaining high signal fidelity. The neurograin system is composed of implantable, submillimeter, individually addressable (Huang et al, 2019), and microchip sets (Figure 12B). Each neurograin is an independent packed module of 500 μm × 500µm × 35 µm and wireless powered by inductive coupling technology for near-field transmission (Lee et al, 2018).…”

Section: Neurograinmentioning

confidence: 99%

In Vivo Neural Interfaces—From Small- to Large-Scale Recording

Zhang

Deng²,

Cai

et al. 2022

Front. Nanotechnol.

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Brain functions arise from the coordinated activation of neuronal assemblies distributed across multiple brain regions. The electrical potential from the neuron captured by the electrode can be processed to extract brain information. A large number of densely and simultaneously recorded neuronal potential signals from neurons spanning multiple brain regions contribute to the insight of specific behaviors encoded by the neural ensembles. In this review, we focused on the neural interfaces developed for small- to large-scale recordings and discussed the developmental challenges and strategies in microsystem, electrode device, and interface material levels for the future larger-scale neural ensemble recordings.

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“…The front end of a neurograin SoC integrates high-fidelity physiologic sensing (recording) and actuating (stimulation) interfaces, with a special focus on ultra-miniaturization and extremely low-power operation. To this end, we have designed a recording analog front end (AFE), a version of which is shown here for the acquisition of electrocorticographic (ECoG) signals using a DC-coupled V/I converter merged with an analog-to-digital converter (ADC) in an area-efficient capacitor-less approach [35]. The AFE directly senses neural potentials (without the need for bulky AC-coupling capacitors), and thus is able to occupy an overall footprint of 100 μm × 100 μm, while recording at a 1 kHz sampling rate and 8-bit resolution.…”

Section: System-on-chip Microimplantmentioning

confidence: 99%

Wireless Ensembles of Sub-mm Microimplants Communicating as a Network near 1 GHz in a Neural Application

Leung

Lee

et al. 2020

Preprint

Self Cite

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Multichannel electrophysiological sensors and stimulators, especially those used for studying the nervous system, are most commonly based on monolithic microelectrode arrays. Such architecture limits the spatial flexibility of individual electrode placement, posing constraints for scaling to a large number of nodes, particularly across non-contiguous locations. We describe the design and fabrication of sub-millimeter size electronic microchips (Neurograins) which autonomously perform neural sensing or electrical microstimulation, with emphasis on their wireless networking and powering. An ~1 GHz electromagnetic transcutaneous link to an external telecom hub enables bidirectional communication and control at the individual neurograin level. The link operates on a customized time division multiple access (TDMA) protocol designed to scale up to 1000 neurograins. The system is demonstrated as a cortical implant in a small animal (rat) model with anatomical limitations restricting the implant to 48 neurograins. We suggest that the neurograin approach can be generalized to overcome many scalability issues for wireless sensors and actuators as implantable microsystems

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A 0.01-mm² Mostly Digital Capacitor-Less AFE for Distributed Autonomous Neural Sensor Nodes

Cited by 35 publications

References 10 publications

An AC-Coupled Wideband Neural Recording Front-End With Sub-1 mm²×fJ/conv-step Efficiency and 0.97 NEF

An AC-Coupled Wideband Neural Recording Front-End With Sub-1 mm²×fJ/conv-step Efficiency and 0.97 NEF

In Vivo Neural Interfaces—From Small- to Large-Scale Recording

Wireless Ensembles of Sub-mm Microimplants Communicating as a Network near 1 GHz in a Neural Application

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A 0.01-mm2 Mostly Digital Capacitor-Less AFE for Distributed Autonomous Neural Sensor Nodes

Cited by 35 publications

References 10 publications

An AC-Coupled Wideband Neural Recording Front-End With Sub-1 mm2×fJ/conv-step Efficiency and 0.97 NEF

An AC-Coupled Wideband Neural Recording Front-End With Sub-1 mm2×fJ/conv-step Efficiency and 0.97 NEF

In Vivo Neural Interfaces—From Small- to Large-Scale Recording

Wireless Ensembles of Sub-mm Microimplants Communicating as a Network near 1 GHz in a Neural Application

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Product

Resources

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A 0.01-mm² Mostly Digital Capacitor-Less AFE for Distributed Autonomous Neural Sensor Nodes

An AC-Coupled Wideband Neural Recording Front-End With Sub-1 mm²×fJ/conv-step Efficiency and 0.97 NEF

An AC-Coupled Wideband Neural Recording Front-End With Sub-1 mm²×fJ/conv-step Efficiency and 0.97 NEF