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<p>Design of power-efficient low-pass-filter is a requisite requirement of electroencephalogram acquisition systems owing to the long-term use of these systems in the diagnosis of brain-related chronic disorders. The article presents analysis of 4th -order LPF designed with class-AB, quasi-floating gate and flipped source follower approaches in 180&#xa0;nm technology. The gain of -4.7 dB, cut-off frequency of 98.77&#xa0;Hz, dynamic range of 49.05 dB, total harmonic distortion of -47.15 dB and area of 0.031 mm<sup>2</sup> are the findings displayed by the proposed LPF. Further, the values of coefficient of variation (with 1000 Monte-Carlo samples) for gain, DR and THD of the proposed QFG FSF LPF are − 0.03, 0.014, and − 0.039, respectively. Besides this, appraisal parameters like low power consumption (0.154 nW) and low figure-of-merit (1.37 × 10<sup>–15</sup>&#xa0;J) of proposed QFG FSF LPF confirms its viability for use in EEG acquisition systems.</p>

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Ultra Power-Efficient Flipped Source Follower Filter for EEG Acquisition Systems

  • 期刊论文

  • 发表日期：

    2025年10月8日

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  • Diksha Thakur ,
  • Kulbhushan Sharma,
  • Ashish Sachdeva

摘要

Design of power-efficient low-pass-filter is a requisite requirement of electroencephalogram acquisition systems owing to the long-term use of these systems in the diagnosis of brain-related chronic disorders. The article presents analysis of 4th -order LPF designed with class-AB, quasi-floating gate and flipped source follower approaches in 180 nm technology. The gain of -4.7 dB, cut-off frequency of 98.77 Hz, dynamic range of 49.05 dB, total harmonic distortion of -47.15 dB and area of 0.031 mm2 are the findings displayed by the proposed LPF. Further, the values of coefficient of variation (with 1000 Monte-Carlo samples) for gain, DR and THD of the proposed QFG FSF LPF are − 0.03, 0.014, and − 0.039, respectively. Besides this, appraisal parameters like low power consumption (0.154 nW) and low figure-of-merit (1.37 × 10–15 J) of proposed QFG FSF LPF confirms its viability for use in EEG acquisition systems.