Imperial College London
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DrYanLiu

Faculty of Engineering, Department of Electrical and Electronic Engineering

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yan.liu06 CV

 
 
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Location

 

Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Liu:2022:10.1109/TCSII.2022.3153786,
author = {Liu, H and Guo, T and Yan, P and Qi, L and Chen, M and Wang, G and Liu, Y},
doi = {10.1109/TCSII.2022.3153786},
journal = {IEEE Transactions on Circuits and Systems II: Express Briefs},
pages = {2682--2686},
title = {A Hybrid 1<sup>st</sup>/2<sup>nd</sup>-Order VCO-Based CTDSM With Rail-to-Rail Artifact Tolerance for Bidirectional Neural Interface},
url = {http://dx.doi.org/10.1109/TCSII.2022.3153786},
volume = {69},
year = {2022}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Bi-directional brain machine interfaces enable simultaneous brain activity monitoring and neural modulation. However stimulation artifact can saturate instrumentation front-end, while concurrent on-site recording is needed. This brief presents a voltage controlled-oscillator (VCO) based continuous-time $\rm \Delta \Sigma $ modulator (CTDSM) with rail-to-rail input range and fast artifact tracking. A hybrid $1^{st}/2^{nd}$ -order loop is designed to achieve high dynamic range (DR) and large input range. Stimulation artifact is detected by a phase counter and compensated by the $1^{st}$ -order loop. The residue signal is digitized by the $2^{nd}$ -order loop for high precision. Redundancy between the two loops is implemented as feedback capacitors elements with non-binary ratio to guarantee feedback stability and linearity. Fabricated in a 55-nm CMOS process, the prototype achieves 65.7dB SNDR across 10 kHz bandwidth with a full scale of 200 mVpp. And a ±1.2 V input range is achieved to suppress artifacts. Saline based experiment with simultaneous stimulation and recording demonstrates that the implemented system can track and tolerate rail-to-rail stimulation artifact within 30 $\mu \text{s}$ while small neural signal can be continuously monitored.
AU  - Liu,H
AU  - Guo,T
AU  - Yan,P
AU  - Qi,L
AU  - Chen,M
AU  - Wang,G
AU  - Liu,Y
DO  - 10.1109/TCSII.2022.3153786
EP  - 2686
PY  - 2022///
SN  - 1549-7747
SP  - 2682
TI  - A Hybrid 1<sup>st</sup>/2<sup>nd</sup>-Order VCO-Based CTDSM With Rail-to-Rail Artifact Tolerance for Bidirectional Neural Interface
T2  - IEEE Transactions on Circuits and Systems II: Express Briefs
UR  - http://dx.doi.org/10.1109/TCSII.2022.3153786
VL  - 69
ER  -
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