Efficient Metastability Mitigation and Sub-Band Filtering in VCO-Based EEG Recording
This brief proposes an efficient structure for electroencephalogram (EEG) signal recording. A single-sample strategy is proposed to mitigate metastability issues in Voltage-Controlled Oscillator (VCO) Analog Front Ends (AFEs), offering timing margins of 14 phase cycles and simplifying the result arbitration logic to 1-bit multiplexing. Additionally, an analysis of existing EEG sub-band filter designs is presented, followed by an efficient band multiplexing serial multiplier structure that capitalizes on timing slacks. This design features a reduction in both the number of multipliers and the complexity of the multiplexing network. The proposed design was implemented using 40nm CMOS technology. The VCO-AFE demonstrates stable, error-free recordings with an input-referred noise (IRN) of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$0.66\boldsymbol {\mu }$ </tex-math></inline-formula>V<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\boldsymbol {_{rms}}$ </tex-math></inline-formula> within 0.5–60Hz, according to the measurement results. The proposed sub-band filter exhibits substantial savings of 11% and 51% in area and power, respectively, compared to prior work when scaled to the same technology node.
Authors
- Tongfei Wang (ORCID: https://orcid.org/0000-0002-6306-7371)
- Zijian Tang (ORCID: https://orcid.org/0000-0002-3063-3576)
- Yuan Ma (ORCID: https://orcid.org/0000-0002-6445-3741)
- Chao Zhang (ORCID: https://orcid.org/0000-0002-9583-0722)
- Milin Zhang (ORCID: https://orcid.org/0000-0001-7544-1837)
- Minqian Zheng
- Zhixiong Ma
- Chao Sun (ORCID: https://orcid.org/0000-0001-6902-8202)
Institutions
- Chinese Institute for Brain Research (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- IEEE Transactions on Circuits & Systems II Express Briefs
- Published
- 2024-08-20
- DOI
- https://doi.org/10.1109/tcsii.2024.3446187
- Primary Topic
- Blind Source Separation Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Beijing Municipal Natural Science Foundation