利用皮质脑电图频谱特性进行优化信号链设计：一种降低ADC分辨率要求的1.08模拟前端
Exploiting Electrocorticographic Spectral Characteristics for Optimized Signal Chain Design: A 1.08 Analog Front End With Reduced ADC Resolution Requirements.
作者信息
Smith William A, Mogen Brian J, Fetz Eberhard E, Sathe Visvesh S, Otis Brian P
出版信息
IEEE Trans Biomed Circuits Syst. 2016 Dec;10(6):1171-1180. doi: 10.1109/TBCAS.2016.2518923. Epub 2016 Apr 6.
Abstract
Electrocorticography (ECoG) is an important area of research for Brain-Computer Interface (BCI) development. ECoG, along with some other biopotentials, has spectral characteristics that can be exploited for more optimal front-end performance than is achievable with conventional techniques. This paper optimizes noise performance of such a system and discusses an equalization technique that reduces the analog-to-digital converter (ADC) dynamic range requirements and eliminates the need for a variable gain amplifier (VGA). We demonstrate a fabricated prototype in 1p9m 65 nm CMOS that takes advantage of the presented findings to achieve high-fidelity, full-spectrum ECoG recording. It requires 1.08 μW over a 150 Hz bandwidth for the entire analog front end and only 7 bits of ADC resolution.
摘要
脑皮层电图（ECoG）是脑机接口（BCI）开发研究的一个重要领域。ECoG与其他一些生物电位一样，具有频谱特性，利用这些特性可实现比传统技术更优的前端性能。本文优化了此类系统的噪声性能，并讨论了一种均衡技术，该技术可降低模数转换器（ADC）的动态范围要求，且无需使用可变增益放大器（VGA）。我们展示了一款采用1p9m 65纳米互补金属氧化物半导体（CMOS）工艺制造的原型，该原型利用上述研究结果实现了高保真、全频谱的ECoG记录。整个模拟前端在150赫兹带宽上仅需1.08微瓦功率，且ADC分辨率仅需7位。
相似文献
1
Exploiting Electrocorticographic Spectral Characteristics for Optimized Signal Chain Design: A 1.08 Analog Front End With Reduced ADC Resolution Requirements.利用皮质脑电图频谱特性进行优化信号链设计：一种降低ADC分辨率要求的1.08模拟前端
IEEE Trans Biomed Circuits Syst. 2016 Dec;10(6):1171-1180. doi: 10.1109/TBCAS.2016.2518923. Epub 2016 Apr 6.
2
CMOS Ultralow Power Brain Signal Acquisition Front-Ends: Design and Human Testing.CMOS 超低功耗脑信号采集前端：设计与人体测试。
IEEE Trans Biomed Circuits Syst. 2017 Oct;11(5):1111-1122. doi: 10.1109/TBCAS.2017.2723607. Epub 2017 Aug 1.
3
An Energy-Efficient CMOS Dual-Mode Array Architecture for High-Density ECoG-Based Brain-Machine Interfaces.一种用于高密度基于脑电的脑机接口的高能效 CMOS 双模阵列架构。
IEEE Trans Biomed Circuits Syst. 2020 Apr;14(2):332-342. doi: 10.1109/TBCAS.2019.2963302. Epub 2019 Dec 31.
4
A 16-Channel CMOS Chopper-Stabilized Analog Front-End ECoG Acquisition Circuit for a Closed-Loop Epileptic Seizure Control System.一种用于闭环癫痫发作控制系统的 16 通道 CMOS 斩波稳定模拟前端 ECoG 采集电路。
IEEE Trans Biomed Circuits Syst. 2018 Jun;12(3):543-553. doi: 10.1109/TBCAS.2018.2808415.
5
A 0.0023 mm /ch. Delta-Encoded, Time-Division Multiplexed Mixed-Signal ECoG Recording Architecture With Stimulus Artifact Suppression.一种 0.0023mm/ch 的、带 Delta 编码的、时分复用的混合信号 ECoG 记录架构，具有刺激伪影抑制功能。
IEEE Trans Biomed Circuits Syst. 2020 Apr;14(2):319-331. doi: 10.1109/TBCAS.2019.2963174. Epub 2019 Dec 31.
6
A 2.64- μW 71-dB SNDR Discrete-Time Signal-Folding Amplifier for Reducing ADC's Resolution Requirement in Wearable ECG Acquisition Systems.用于降低可穿戴式 ECG 采集系统中 ADC 分辨率要求的 2.64-μW、71-dB SNR 离散时间信号折叠放大器。
IEEE Trans Biomed Circuits Syst. 2020 Feb;14(1):48-64. doi: 10.1109/TBCAS.2019.2957030. Epub 2019 Dec 2.
7
An ECG recording front-end with continuous-time level-crossing sampling.一种具有连续时间过零采样的心电图记录前端。
IEEE Trans Biomed Circuits Syst. 2014 Oct;8(5):626-35. doi: 10.1109/TBCAS.2014.2359183. Epub 2014 Oct 14.
8
Enabling Low-Power, Multi-Modal Neural Interfaces Through a Common, Low-Bandwidth Feature Space.通过通用的低带宽特征空间实现低功耗、多模态神经接口。
IEEE Trans Neural Syst Rehabil Eng. 2016 May;24(5):521-31. doi: 10.1109/TNSRE.2015.2501752. Epub 2015 Nov 20.
9
Consistency of Long-Term Subdural Electrocorticography in Humans.长期硬脑膜下脑电监测在人类中的一致性。
IEEE Trans Biomed Eng. 2018 Feb;65(2):344-352. doi: 10.1109/TBME.2017.2768442.
10
A Sub- μW/Ch Analog Front-End for ∆-Neural Recording With Spike-Driven Data Compression.用于具有尖峰驱动数据压缩的 ∆-神经记录的亚微瓦/通道模拟前端。
IEEE Trans Biomed Circuits Syst. 2019 Feb;13(1):1-14. doi: 10.1109/TBCAS.2018.2880257. Epub 2018 Nov 9.
引用本文的文献
1
A 0.0023 mm /ch. Delta-Encoded, Time-Division Multiplexed Mixed-Signal ECoG Recording Architecture With Stimulus Artifact Suppression.一种 0.0023mm/ch 的、带 Delta 编码的、时分复用的混合信号 ECoG 记录架构，具有刺激伪影抑制功能。
IEEE Trans Biomed Circuits Syst. 2020 Apr;14(2):319-331. doi: 10.1109/TBCAS.2019.2963174. Epub 2019 Dec 31.
2
CMOS Ultralow Power Brain Signal Acquisition Front-Ends: Design and Human Testing.CMOS 超低功耗脑信号采集前端：设计与人体测试。
IEEE Trans Biomed Circuits Syst. 2017 Oct;11(5):1111-1122. doi: 10.1109/TBCAS.2017.2723607. Epub 2017 Aug 1.
本文引用的文献
1
A digitally assisted, signal folding neural recording amplifier.一种数字辅助的信号折叠神经记录放大器。
IEEE Trans Biomed Circuits Syst. 2014 Aug;8(4):528-42. doi: 10.1109/TBCAS.2013.2288680.
2
A frequency shaping neural recorder with 3 pF input capacitance and 11 plus 4.5 bits dynamic range.一种具有3皮法输入电容和11加4.5位动态范围的频率整形神经记录器。
IEEE Trans Biomed Circuits Syst. 2014 Aug;8(4):510-27. doi: 10.1109/TBCAS.2013.2293821.
3
The effect of micro-ECoG substrate footprint on the meningeal tissue response.微电极脑电图（micro-ECoG）基底覆盖面积对脑膜组织反应的影响。
J Neural Eng. 2014 Aug;11(4):046011. doi: 10.1088/1741-2560/11/4/046011. Epub 2014 Jun 18.
4
Frequency specific spatial interactions in human electrocorticography: V1 alpha oscillations reflect surround suppression.人类脑皮层电图中的频率特异性空间相互作用：V1alpha 振荡反映了周围抑制。
Neuroimage. 2013 Jan 15;65:424-32. doi: 10.1016/j.neuroimage.2012.10.020. Epub 2012 Oct 18.
5
Double-differential recording and AGC using microcontrolled variable gain ASIC.采用微控制可变增益 ASIC 的双重微分记录和自动增益控制。
IEEE Trans Neural Syst Rehabil Eng. 2013 Jan;21(1):47-54. doi: 10.1109/TNSRE.2012.2213842. Epub 2012 Aug 23.
6
The origin of extracellular fields and currents--EEG, ECoG, LFP and spikes.细胞外场和电流的起源——EEG、ECoG、LFP 和 spikes。
Nat Rev Neurosci. 2012 May 18;13(6):407-20. doi: 10.1038/nrn3241.
7
Brain-computer interfaces using electrocorticographic signals.脑-机接口使用脑电图信号。
IEEE Rev Biomed Eng. 2011;4:140-54. doi: 10.1109/RBME.2011.2172408.
8
Modeling the spatial reach of the LFP.建立 LFP 的空间范围模型。
Neuron. 2011 Dec 8;72(5):859-72. doi: 10.1016/j.neuron.2011.11.006.
9
Electrocorticographic control of a prosthetic arm in paralyzed patients.瘫痪患者的假肢的脑电控制。
Ann Neurol. 2012 Mar;71(3):353-61. doi: 10.1002/ana.22613. Epub 2011 Nov 2.
10
Power-law scaling in the brain surface electric potential.大脑表面电势的幂律标度。
PLoS Comput Biol. 2009 Dec;5(12):e1000609. doi: 10.1371/journal.pcbi.1000609. Epub 2009 Dec 18.
Zotero 插件