The DOI matches its Crossref record; 32 of the 33 references it cites were found in a registry or an index.
A low-power low-noise cmos for amplifier neural recording applications
Abstract
There is a need among scientists and clinicians for low-noise low-power biosignal amplifiers capable of amplifying signals in the millihertz-to-kilohertz range while rejecting large dc offsets generated at the electrode-tissue interface. The advent of fully implantable multielectrode arrays has created the need for fully integrated micropower amplifiers. We designed and tested a novel bioamplifier that uses a MOS-bipolar pseudoresistor element to amplify low-frequency signals down to the millihertz range while rejecting large dc offsets. We derive the theoretical noise-power tradeoff limit - the noise efficiency factor - for this amplifier and demonstrate that our VLSI implementation approaches this limit by selectively operating MOS transistors in either weak or strong inversion. The resulting amplifier, built in a standard 1.5-μm CMOS process, passes signals from 0.025Hz to 7.2 kHz with an input-referred noise of 2.2 μVrms and a power dissipation of 80 μW while consuming 0.16 mm2of chip area. Our design technique was also used to develop an electroencephalogram amplifier having a bandwidth of 30 Hz and a power dissipation of 0.9 μW while maintaining a similar noise-power tradeoff.
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In the citing paper
“A common ac-coupled bioamplifier, shown in Fig. 6(a), uses capacitive feedback to accurately set the midband gain as a ratio of the input and feedback capacitors ( C I /C F ) [168].”
From Active Neural Interface Circuits and Systems for Selective Control of Peripheral Nerves: A Review (2024) · cites this paper as [168]
In the citing paper
“which can range up to tens of M Ω in biopotential amplifier applications [168].”
From Active Neural Interface Circuits and Systems for Selective Control of Peripheral Nerves: A Review (2024) · cites this paper as [168]
In the citing paper
“It is preferable to implement highly resistive elements with transistors compared to their discrete alternatives due to the large silicon area required to achieve the necessary values”
From Active Neural Interface Circuits and Systems for Selective Control of Peripheral Nerves: A Review (2024) · cites this paper as [168]
In the citing paper
“Indeed, previous studies [53, 98, 128], which used either a symmetrical cascode OTA or a 2-stage Miller OTA, reported NEFs ranging from 4 to 17.”
From Implantable neurotechnologies: a review of integrated circuit neural amplifiers (2016) · cites this paper as [53]
In the citing paper
“The most common way is to add a low noise amplifier (LNA) to the front end of the recording (Harrison and Charles, 2003; Harrison et al., 2007) and then to add the digital quantization circuits (Zou et al., 2009; Liu et al., 2017; Yu et al., 2018).”
From Advances in Neural Recording and Stimulation Integrated Circuits (2021) · cites this paper as Harrison and Charles, 2003
Citations
Cites
The Design of CMOS Radio-Frequency Integrated Circuits
Lee, T. H. (2003) · Cambridge University Press eBooks · doi:10.1017/cbo9780511817281 · Cited by 3,497
Operation and modeling of the MOS transistor
Tsividis, Y. (1987) · Cited by 3,162
Analog VLSI and Neural Systems
Mead, C. (1989) · CaltechAUTHORS (California Institute of Technology) · Cited by 2,776
Analog Integrated Circuit Design
Carusone, A. C., Johns, D. A., & Martin, K. W. (1996) · Cited by 2,509
Analog integrated circuit design
Hurst, S. L. (1998) · Microelectronics Journal · doi:10.1016/s0026-2692(97)00051-7 · Cited by 1,734
Enz, C., Krummenacher, F., & Vittoz, E. A. (1995) · Analog Integrated Circuits and Signal Processing · doi:10.1007/bf01239381 · Cited by 1,272
CMOS analog integrated circuits based on weak inversion operations
Vittoz, E. A., & Fellrath, J. (1977) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.1977.1050882 · Cited by 814
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
High-quality recording of bioelectric events
van Rijn, A. C. M., Peper, A., & Grimbergen, C. A. (1991) · Medical & Biological Engineering & Computing · doi:10.1007/bf02441666 · Cited by 451
High-quality recording of bioelectric events
van Rijn, A. C. M., Peper, A., & Grimbergen, C. A. (1990) · Medical & Biological Engineering & Computing · doi:10.1007/bf02441961 · Cited by 429
Flagged first, then by citations
1 of the 33 references couldn’t be matched to a known paper.
Research works printed but not linked: 1
- Dagtekin, A multichannel chopper modulated neural recording system, 757
Cited by
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Items 1,001–1,002 of 1,002
A Practical Approach to Introducing Electrical Undergraduates to Artificial Neural Networks
Halkiadis, I. S. (2009) · International Journal of Electrical Engineering & Education · doi:10.7227/ijeee.46.2.1 · Cited by 2
Design Considerations for Implantable Neural Circuits and Systems
Hsu, W.-Y., Hsieh, P.-H., & Chen, H. (2023) · Handbook of Neuroengineering · doi:10.1007/978-981-16-5540-1_19 · Cited by 1
Metadata
- Authors
- Harrison, R. R., & Charles, C.
- Affiliations
- University of Utah (US)
- Venue
- IEEE Journal of Solid-State Circuits
- Published
- 2003-06
- Volume
- 38
- Issue
- 6
- Pages
- 958-965
- ISSN
- 0018-9200 (ISSN-L)
- OpenAlex
- W2159318368
- Cited by
- 1,695
- References
- 33
- Citations by year
- 2026: 41 · 2025: 55 · 2024: 71 · 2023: 71 · 2022: 74 · 2021: 118 · 2020: 82 · 2019: 80 · 2018: 93 · 2017: 86 · 2016: 90 · 2015: 90 · 2014: 85 · 2013: 80 · 2012: 82
- FWCI
- 24.78
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Journal of Solid-State Circuits (publishedVersion)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Analog and Mixed-Signal Circuit Design
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Radio Frequency Integrated Circuit Design
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Low-power high-performance VLSI design
- Keywords
- neural recording, DC offset rejection, noise efficiency factor, weak and strong inversion, VLSI design
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