The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
A 200 μW Eight-Channel EEG Acquisition ASIC for Ambulatory EEG Systems
Abstract
The growing interest toward the improvement of patients' quality of life and the use of medical signals in nonmedical applications such as entertainment, sports, and brain–computerinterfaces, requires the implementation of miniaturized and wireless biopotential acquisition systems with ultralow power dissipation. Therefore, this paper presents the implementation of a complete EEG acquisition ASIC tailored towards the needs of such applications, i.e., high-signal quality, low-power dissipation and ease of use. The presented ASIC includes eight readout front-end channels and an 11-bit analog-to-digital converter (ADC). The key to its high performance and low-power dissipation is the new AC coupled chopper stabilized instrumentation amplifier (ACCIA) implementation that uses a coarse–fine servoloop and reaches more than 120 dB CMRR, consumes only 2.3$\mu{\hbox{A}}$, and achieves a noise–efficiency factor (NEF) of 4.3. Furthermore, the ease of use of the ASIC is realized by incorporating Calibration and Electrode Impedance Measurement Modes to the ASIC. Therefore, the former can be used to check the functionality of the ASIC, as well as, to calibrate the gain matching of the channels, where as the latter can be used to track the quality of the biopotential electrode. The ASIC is implemented in 0.5$\mu{\hbox{m}}$CMOS process and the total current consumption is 66$\mu{\hbox{A}}$from 3 V.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
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
Cited by
An Implantable 455-Active-Electrode 52-Channel CMOS Neural Probe
Lopez, C. M., Andrei, A., Mitra, S., Welkenhuysen, M., Eberle, W., Bartic, C., Puers, R., Yazicioglu, R. F., & Gielen, G. G. E. (2014) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.2013.2284347 · Cited by 264
Self-citationVan Helleputte, N., Konijnenburg, M., Pettine, J., Jee, D.-W., Kim, H., Morgado, A., Van Wegberg, R., Torfs, T., Mohan, R., Breeschoten, A., et al. (2015) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.2014.2359962 · Cited by 253
Analysis and Design of Tunable Amplifiers for Implantable Neural Recording Applications
Rezaee-Dehsorkh, H., Ravanshad, N., Lotfi, R., Mafinezhad, K., & Sodagar, A. M. (2011) · IEEE Journal on Emerging and Selected Topics in Circuits and Systems · doi:10.1109/jetcas.2011.2174492 · Cited by 103
Multi-Channel Neural Recording Implants: A Review
Hashemi Noshahr, F., Nabavi, M., & Sawan, M. (2020) · Sensors · doi:10.3390/s20030904 · Cited by 66
32.9 nV/rt Hz ${-}$60.6 dB THD Dual-Band Micro-Electrode Array Signal Acquisition IC
Guo, J., Yuan, J., Huang, J., Law, J. K.-Y., Yeung, C.-K., & Chan, M. (2012) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.2012.2185590 · Cited by 45
Metadata
- Authors
- Yazicioglu, R. F., Merken, P., Puers, R., & Van Hoof, C.
- Venue
- IEEE Journal of Solid-State Circuits
- Published
- 2008-12
- Volume
- 43
- Issue
- 12
- Pages
- 3025-3038
- ISSN
- 0018-9200 (ISSN-L)
- 1558-173X
- OpenAlex
- W2122617960
- Cited by
- 271
- References
- 1
- FWCI
- 11.72
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A 200 μW Eight-Channel EEG Acquisition ASIC for Ambulatory EEG Systems. https://app.cochat.ai/papers/10.1109/jssc.2008.2006462
- The paper
- Yazicioglu, R. F., Merken, P., Puers, R., & Van Hoof, C. (2008). A 200 μW Eight-Channel EEG Acquisition ASIC for Ambulatory EEG Systems. IEEE Journal of Solid-State Circuits. https://doi.org/10.1109/jssc.2008.2006462
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.