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Proceedings ArticleDOI

A 0.013mm 2 5μW DC-coupled neural signal acquisition IC with 0.5V supply

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TLDR
This work presents a neural interface in 65nm CMOS and operating at a 0.5V supply that obtains performance comparable or superior to state-of-the-art systems in a silicon area over 3× smaller by using a scalable architecture that avoids on-chip passives and takes advantage of high-density logic.
Abstract
Recent success in brain-machine interfaces has provided hope for patients with spinal-cord injuries, Parkinson's disease, and other debilitating neurological conditions [1], and has boosted interest in electronic recording of cortical signals State-of-the-art recording solutions [2–5] rely heavily on analog techniques at relatively high supply voltages to perform signal conditioning and filtering, leading to large silicon area and limited programmability We present a neural interface in 65nm CMOS and operating at a 05V supply that obtains performance comparable or superior to state-of-the-art systems in a silicon area over 3× smaller These results are achieved by using a scalable architecture that avoids on-chip passives and takes advantage of high-density logic The use of 65nm CMOS eases integration with low-power digital systems, while the low supply voltage makes the design more compatible with wireless powering schemes [6]

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Citations
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Proceedings ArticleDOI

A low-power current-reuse analog front-end for multi-channel neural signal recording

TL;DR: This work presents a new current-reuse analog front-end (AFE), which is scalable to very large number of recording channels, thanks to its small implementation area and its low-power consumption.
Journal ArticleDOI

Plugging Electronics Into Minds: Recent Trends and Advances in Neural Interface Microsystems

TL;DR: Despite rapid advancements in our electronics industry, connecting our minds to machines (e.g., robots and computers) through brain-machine interface (BMI) technologies remains an unfulfilled human ambition.
Proceedings ArticleDOI

Robust, reconfigurable, and power-efficient biosignal recording systems

TL;DR: The design requirements of biosignal recording interfaces for use in remote, unconstrained environments are reviewed and it is proposed to process electrophysiological signals in the phase domain, since there is no physical bound on phase.
Proceedings ArticleDOI

26.6 A 6.5µW 10kHz-BW 80.4dB-SNDR Continuous-Time ΔΣ Modulator with G m -Input and 300mV pp Linear Input Range for Closed-Loop Neural Recording

TL;DR: A continuous-time delta-sigma modulator (CT-ALM) with Gm -input for closed-loop neural recording achieves a high input impedance, 300mVpp linear input range, 80.4dB SNDR, and 76dB CMRR, and consumes only 6.5μW with a signal bandwidth of 10kHz.
Journal ArticleDOI

2.5D Heterogeneously Integrated Microsystem for High-Density Neural Sensing Applications

TL;DR: The successful in-vivo test demonstrated the proposed 2.5D heterogeneously integrated bio-sensing microsystem with μ-probes and embedded through-silicon-via (TSVs) for high-density neural sensing applications.
References
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Journal ArticleDOI

Brain–machine interfaces: past, present and future

TL;DR: This paper discusses designing a fully implantable biocompatible recording device, further developing real-time computational algorithms, introducing a method for providing the brain with sensory feedback from the actuators, and designing and building artificial prostheses that can be controlled directly by brain-derived signals.
Journal ArticleDOI

A Low-Power Integrated Circuit for a Wireless 100-Electrode Neural Recording System

TL;DR: A prototype integrated circuit for wireless neural recording from a 100-channel microelectrode array was developed and a two-chip system was used to record neural signals from a Utah Electrode Array in cat cortex and transmit the digitized signals wirelessly to a receiver.
Journal ArticleDOI

A micropower low-noise monolithic instrumentation amplifier for medical purposes

TL;DR: A CMOS low-power low-noise monolithic instrumentation amplifier is described and it can produce variable gains of 14/20/26/40 dB, which are set by control software.
Journal ArticleDOI

An Energy-Efficient Micropower Neural Recording Amplifier

TL;DR: The amplifier appears to be the lowest power and most energy-efficient neural recording amplifier reported to date and the low-noise design techniques that help the neural amplifier achieve input-referred noise that is near the theoretical limit of any amplifier using a differential pair as an input stage.
Journal ArticleDOI

256-Channel Neural Recording and Delta Compression Microsystem With 3D Electrodes

TL;DR: Results of in vitro experimental recordings from intact mouse hippocampus validate the circuit design and the on-chip electrode bonding technology.
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