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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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Neural Dust: Ultrasonic Biological Interface

Dongjin Seo
TL;DR: Seo et al. as discussed by the authors proposed neural dust, an entirely new method of wireless power and data telemetry using ultrasound, which can address fundamental issues associated with using EM to interrogate miniaturized implants.
Proceedings ArticleDOI

Ultra Low Power Digital Front-End for Single Lead ECG Acquisition

TL;DR: A low power single lead electrocardiogram front end acquisition system in 0.18um CMOS process with supply voltage 0.5V is presented in this paper.
Book ChapterDOI

Neural recording interfaces for intracortical implants

TL;DR: A 64-channel inductively powered neural recording ­sensor ­array that implements a local autocalibration mechanism that configures the transfer characteristics of the recording site and the power consumption is 377 μW.

Analysis and Design of Decision Feedback Equalizers for Bitrates of 10 Gbps and Beyond in Submicron CMOS

TL;DR: In this paper, the authors provide a guideline on how to design and specify a decision feedback equalizer (DFE) for bitrates of 10 Gbps and beyond for clock data recovery.
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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