Cited by 165Analog and Mixed-Signal Circuit DesignNeuroscience and Neural EngineeringRadio Frequency Integrated Circuit Design

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Energy Efficient Low-Noise Neural Recording Amplifier With Enhanced Noise Efficiency Factor

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Majidzadeh, Vahid, Schmid, Alexandre, Leblebici, Yusuf·2011·IEEE Transactions on Biomedical Circuits and Systems

DOI 10.1109/tbcas.2010.2078815

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Abstract

This paper presents a neural recording amplifier array suitable for large-scale integration with multielectrode arrays in very low-power microelectronic cortical implants. The proposed amplifier is one of the most energy-efficient structures reported to date, which theoretically achieves an effective noise efficiency factor (NEF) smaller than the limit that can be achieved by any existing amplifier topology, which utilizes a differential pair input stage. The proposed architecture, which is referred to as a partial operational transconductance amplifier sharing architecture, results in a significant reduction of power dissipation as well as silicon area, in addition to the very low NEF. The effect of mismatch on crosstalk between channels and the tradeoff between noise and crosstalk are theoretically analyzed. Moreover, a mathematical model of the nonlinearity of the amplifier is derived, and its accuracy is confirmed by simulations and measurements. For an array of four neural amplifiers, measurement results show a midband gain of 39.4 dB and a -3-dB bandwidth ranging from 10 Hz to 7.2 kHz. The input-referred noise integrated from 10 Hz to 100 kHz is measured at 3.5 μVrms and the power consumption is 7.92 μW from a 1.8-V supply, which corresponds to NEF = 3.35. The worst-case crosstalk and common-mode rejection ratio within the desired bandwidth are - 43.5 dB and 70.1 dB, respectively, and the active silicon area of each amplifier is 256 μm × 256 μm in 0.18-μm complementary metal-oxide semiconductor technology.

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Circuit techniques for reducing the effects of op-amp imperfections: autozeroing, correlated double sampling, and chopper stabilization
Enz, C., & Temes, G. C. (1996) · Proceedings of the IEEE · doi:10.1109/5.542410 · Cited by 1,909
A low-power low-noise cmos for amplifier neural recording applications
Harrison, R. R., & Charles, C. (2003) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.2003.811979 · Cited by 1,695
Real-time prediction of hand trajectory by ensembles of cortical neurons in primates
Wessberg, J., Stambaugh, C. R., Kralik, J. D., Beck, P. D., Laubach, M., Chapin, J. K., Kim, J., Biggs, S. J., Srinivasan, M. A., & Nicolelis, M. A. L. (2000) · Nature · doi:10.1038/35042582 · Cited by 1,491
A micropower low-noise monolithic instrumentation amplifier for medical purposes
Steyaert, M. S. J., & Sansen, W. M. C. (1987) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.1987.1052869 · Cited by 577
An Energy-Efficient Micropower Neural Recording Amplifier
Wattanapanitch, W., Fee, M., & Sarpeshkar, R. (2007) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2007.907868 · Cited by 441
Charge‐Based MOS Transistor Modeling
Enz, C., & Vittoz, E. A. (2006) · Wiley eBooks · doi:10.1002/0470855460 · Cited by 419
Single unit recording capabilities of a 100 microelectrode array
Nordhausen, C. T., Maynard, E. M., & Normann, R. A. (1996) · Brain Research · doi:10.1016/0006-8993(96)00321-6 · Cited by 358
Charge-Based MOS Transistor Modeling - The EKV Model for Low-Power and RF IC Design
Enz, C., & Vittoz, E. A. (2006) · Cited by 238
A Low-Power Integrated Bioamplifier With Active Low-Frequency Suppression
Gosselin, B. J., Sawan, M., & Chapman, C. A. (2007) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2007.914490 · Cited by 176
A Fully Integrated Neural Recording Amplifier With DC Input Stabilization
Mohseni, P., & Najafi, K. (2004) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2004.824126 · Cited by 173

Flagged first, then by citations

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Research works printed but not linked: 1

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Nath, S., Guha, K., & Baishnab, K. L. (2023) · Lecture notes in electrical engineering · doi:10.1007/978-981-99-4495-8_28 · Cited by 3
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Wang, Y. (2015) · Journal of Vibroengineering · doi:10.21595/jve.2014.15614 · Cited by 3
“Nowadays, it is mainly controlled on the basis of CAE analysis or verification of the two [4-7].”
A low power neural recording amplifier with programmable gain and bandwidth
Thanigaivelan, B., Wiles, J., & Hamilton, T. J. (2012) · IEEE International Symposium on Circuits and Systems proceedings · doi:10.1109/iscas.2012.6271732 · Cited by 3
“Performance Attribute This Work [7] [1] [8] [9] [2]”
Background
Advances in Invasive Brain–Computer Interface Technology and Decoding Methods for Restoring Movement and Future Applications
Bouton, C. E. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-805353-9.00029-2 · Cited by 3
G m /I D Method based Low-power, Low-noise Pre-amplifier Design for EEG
Gupta, L., Kumar, A., & Singh, S. (2019) · Cited by 3
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Park, J. H., Tang, T., Zhang, L., Ng, K. A., & Yoo, J. (2019) · IEEE Asian Solid-State Circuits Conference (A-SSCC) · doi:10.1109/a-sscc47793.2019.9056916 · Cited by 3
“The direct charge pump leakage current compensation methods, such as the replicated leakage cancellation [2], the current pulse position randomization [3] and the pulse split method [4], cannot efficiently handle the leakage issue with the presence of process, voltage and temperature (PVT) variations.”
Method
CMOS differential neural amplifier with high input impedance
Rummens, F., Renaud, S., & Lewis, N. (2015) · IEEE International New Circuits and Systems Conference (NEWCAS) · doi:10.1109/newcas.2015.7182037 · Cited by 3
“Few publications propose a modification of the amplifier structure [13], [14].”
Background
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Saberhosseini, S. S. (2012) · Iranian Conference on Electrical Engineering · doi:10.1109/iraniancee.2012.6292376 · Cited by 3
A new architecture for neural signal amplification in implantable brain machine interfaces
Rehman, S. U., & Kamboh, A. M. (2013) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2013.6610108 · Cited by 3
A Compact and Autoclavable System for Acute Extracellular Neural Recording and Brain Pressure Monitoring for Humans
Angotzi, G. N., Baranauskas, G., Vato, A., Bonfanti, A. G., Zambra, G., Maggiolini, E., Semprini, M., Ricci, D., Ansaldo, A., Castagnola, E., et al. (2014) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2014.2312794 · Cited by 3
Implantable Neural Sensors for Brain Machine Interface
Jang, J., Lee, J.-H., Kang, M., & Song, Y. (2015) · KAIST research series · doi:10.1007/978-94-017-9981-2_3 · Cited by 3
Noise minimization limits in multichannel integrated circuits dedicated to neurobiology experiments
Kmon, P. (2016) · Microelectronics Journal · doi:10.1016/j.mejo.2016.02.008 · Cited by 3
Modular ASIC-based system for large-scale electrical stimulation and recording of brain activity in behaving animals
Szypulska, M., Dwužnik, M., Wiacek, P. K., Skoczeń, A., Fiutowski, T., Jedraczka, M., Dusik, J., Ahmed, M. I., Dąbrowski, W., Hottowy, P., et al. (2016) · International Conference Mixed Design of Integrated Circuits and Systems · doi:10.1109/mixdes.2016.7529735 · Cited by 3
“Modern systems for multielectrode signals recoding are based on dedicated ASICs that realize signals amplification, filtering and multiplexing on a single chip [7-9].”
Background
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Li, H., & Mason, A. J. (2011) · IEEE Biomedical Circuits and Systems Conference (BioCAS) · doi:10.1109/biocas.2011.6107730 · Cited by 3
A multichannel analog front-end for recording neural electrical signals
Feng, Y., Wang, Z., Lü, X., Shuai, A., & Xian, L. (2014) · International Symposium on Bioelectronics and Bioinformatics (ISBB) · doi:10.1109/isbb.2014.6820944 · Cited by 2
“The work presented in [13] reduces the input-referred noise to 3.”
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Kashani, Z., & Kiani, M. (2022) · IEEE Biomedical Circuits and Systems Conference (BioCAS) · doi:10.1109/biocas54905.2022.9948658 · Cited by 2
“Conventional neural amplifiers have often been designed for at least an order of magnitude higher frequency [32]-[34].”
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Reich, S., Fritschi, D., Sporer, M., & Ortmanns, M. (2022) · IEEE Interregional NEWCAS Conference (NEWCAS) · doi:10.1109/newcas52662.2022.9842066 · Cited by 2
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Wang, T.-Y., Lai, M.-R., Twigg, C. M., & Peng, S.-Y. (2013) · IEEE Biomedical Circuits and Systems Conference (BioCAS) · doi:10.1109/biocas.2013.6679682 · Cited by 2
“Summary of performance comparison Parameter [1] [2] [3] [4] [5] BPA2 [5] BPA3 This work 2003 2007 2011 2012 2012 2012 Technology (μm) 1.”
Effective noise minimization in multichannel recording circuits processed in modern technologies for neurobiology experiments
Kmon, P., Gryboś, P., Żołądź, M., & Szczygieł, R. (2014) · IEEE Biomedical Circuits and Systems Conference (BioCAS) · doi:10.1109/biocas.2014.6981733 · Cited by 2
“There are many different approaches of front-end amplifiers responsible for conditioning neural signals [5-10].”
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Jana, D., Ghosh, S., Krishna, R. S. S. M. R., Mandal, S., & Mal, A. K. (2018) · Lecture notes in electrical engineering · doi:10.1007/978-981-10-8240-5_1 · Cited by 2
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Han, L., Li, X., & Yang, Z. (2021) · 2021 3rd International Conference on Intelligent Control, Measurement and Signal Processing and Intelligent Oil Field (ICMSP) · doi:10.1109/icmsp53480.2021.9513221 · Cited by 2
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Wang, G., You, C., Feng, C., Yao, W., Zhao, Z., Xue, N., & Yao, L. (2024) · Biosensors · doi:10.3390/bios14070343 · Cited by 1
“As mentioned in the Supplementary Materials, the equivalent input impedance (at 1 kHz) of OPA ranges from 6.6 M Ω (20 pF) [38] to 14.9 M Ω (9.7 pF) [39], and the impedance of the commercial probe (at 1 kHz) ranges from 5 k Ω to 2.5 M Ω [7].”
BackgroundInfluential
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Majidzadeh, V., & Schmid, A. (2013) · Springer eBooks · doi:10.1007/978-1-4614-6702-1_5 · Cited by 1
Self-citation
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“Techniques such as input device sizing [14], correlated double sampling [15], and chopping [13] are utilized to reduce the input-referred noise.”
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Rezaei, M., Maghsoudloo, E., Bories, C., Koninck, Y. D., & Gosselin, B. J. (2017) · IEEE International New Circuits and Systems Conference (NEWCAS) · doi:10.1109/newcas.2017.8010181 · Cited by 1
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“Results comparison Parameter [2] [4] This Work Technology 1.”
BackgroundMethod
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“Research in wearable biomedical devices needs to focus on how to extract, amplify and filter the extremely small bioelectrical signals while consuming minimal power to extend battery life and increase the portability of the device, which poses a significant challenge to conventional ECG designers [12], [13].”
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“Parameters [19] [20] [21] [22] This work”
A Low-Power Low-Noise Neural recording Bioamplifier
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“…2007 [6] 45-5.3k 40.9 2.7 3.1 2.8 7.56 0.5 Gosselin 2007 [2] 105-9.2kHz 52 4.9 5.6 1.8 8.6 0.18 Rezaee 2011 [7] 300-10k 57.5 3 2.4 1.8 20.8 0.18 Majidzadeh 2011 [8] 10-7.2k 39.4 3.35 3.5 1.8 7.92 0.18 Qian 2011 [9] 0.36-1.3k 39.4 3.09 3.07 2.8 2.4 0.13 Zhang2012 [10] 0.05-10.5k 40 2.9 2.2 1…”
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“Currently a wide range of electrophysiological recording and neural interfacing systems are present in the market [8-14] and system improvement methods are introduced in various articles [15, 16].”
Background
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“For a differential amplifier using MOSFETs as the input devices operating in subthreshold and being the sole contributors to the noise [12].”
Method
Introduction
Yılmaz, G., & Dehollain, C. (2017) · Analog circuits and signal processing/Analog circuits and signal processing series · doi:10.1007/978-3-319-49337-4_1
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Majidzadeh, V., & Schmid, A. (2013) · Springer eBooks · doi:10.1007/978-1-4614-6702-1_4
Self-citation
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Yan, F., Liu, J., Sun, K., Xiong, B., Mo, W., Guan, J., & Li, Z. (2026) · IEEE Transactions on Consumer Electronics · doi:10.1109/tce.2026.3665931
Circuits intégrés d’enregistrement et d’analyse en temps réel des potentiels de champ neuronaux : application au traitement de la maladie de Parkinson, par contrôle adaptatif de stimulations cérébrales profondes
Zbrzeski, A. (2011) · doi:10.70675/bcdca4a1z134fz47d7z829az85887c961d9b

Authors: Majidzadeh, V., Schmid, A., & Leblebici, Y.
Affiliations: École Polytechnique Fédérale de Lausanne (CH)
ORCID: Schmid, Alexandre
Venue: IEEE Transactions on Biomedical Circuits and Systems
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Published: 2011-06
Volume: 5
Issue: 3
Pages: 262-271
ISSN: 1932-4545 (ISSN-L)
1940-9990
DOI: 10.1109/tbcas.2010.2078815
OpenAlex: W2164282321
Cited by: 165
References: 16
Citations by year: 2026: 1 · 2025: 3 · 2024: 7 · 2023: 4 · 2022: 9 · 2021: 8 · 2020: 8 · 2019: 15 · 2018: 13 · 2017: 13 · 2016: 15 · 2015: 21 · 2014: 19 · 2013: 13 · 2012: 12
FWCI: 9.09
Type: journal article
Language: en
Open access: green
infoscience.epfl.ch
Licence: ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html (vor)
Locations: IEEE Transactions on Biomedical Circuits and Systems (publishedVersion)
PubMed (publishedVersion)
Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion)
Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion, cc-by-nc-nd)
Topics: Physical Sciences › Engineering › Electrical and Electronic Engineering › Analog and Mixed-Signal Circuit Design
Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neural Engineering
Physical Sciences › Engineering › Electrical and Electronic Engineering › Radio Frequency Integrated Circuit Design
Keywords: noise efficiency factor, low-power amplifier, microelectrode arrays, cortical implants, crosstalk, common-mode rejection ratio, amplifier nonlinearity, input-referred noise, energy efficiency

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Energy Efficient Low-Noise Neural Recording Amplifier With Enhanced Noise Efficiency Factor

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