Paper Info
Title
A blind Adaptive Stimulation Artifact Rejection (ASAR) engine for closed-loop implantable neuromodulation systems
Abstract
In this work we propose an energy-efficient, implantable, real-time, blind Adaptive Stimulation Artifact Rejection (ASAR) engine. This enables concurrent neural stimulation and recording for state-of-the-art closed-loop neuromodulation systems. Two engines, implemented in 40nm CMOS, achieve convergence of <;42μs for Spike ASAR and <;167μs for LFP ASAR, and can attenuate artifacts up to 100mV <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p-p</sub> by 49.2dB, without any prior knowledge of the stimulation pulse. The LFP and Spike ASAR designs occupy an area of 0.197mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> and 0.209mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , and consume 1.73μW and 3.02μW, respectively at 0.644V.
Year
DOI
Venue
2017
10.1109/NER.2017.8008322
2017 8th International IEEE/EMBS Conference on Neural Engineering (NER)
Keywords
Field
DocType
closed-loop implantable neuromodulation systems,energy-efficient implantable real-time blind adaptive stimulation artifact rejection engine,ASAR engine,concurrent neural stimulation,concurrent neural recording,state-of-the-art closed-loop neuromodulation systems,CMOS,convergence,spike ASAR designs,LFP ASAR,attenuate artifacts
Convergence (routing),Computer vision,Computer science,Electronic engineering,Pulse (signal processing),CMOS,Neuromodulation,Artificial intelligence,Stimulation
Conference
ISSN
ISBN
Citations 
1948-3546
978-1-5090-4604-1
0
PageRank 
References 
Authors
0.34
4
5
Name
Order
Citations
PageRank
Sina Basir-Kazeruni1263.22
Stefan Vlaski22311.39
Hawraa Salami371.88
Ali H. Sayed49134667.71
Dejan Markovic5811115.54