Literature DB >> 28783638

CMOS Ultralow Power Brain Signal Acquisition Front-Ends: Design and Human Testing.

Alireza Karimi-Bidhendi, Omid Malekzadeh-Arasteh, Mao-Cheng Lee, Colin M McCrimmon, Po T Wang, Akshay Mahajan, Charles Yu Liu, Zoran Nenadic, An H Do, Payam Heydari.   

Abstract

Two brain signal acquisition (BSA) front-ends incorporating two CMOS ultralow power, low-noise amplifier arrays and serializers operating in mosfet weak inversion region are presented. To boost the amplifier's gain for a given current budget, cross-coupled-pair active load topology is used in the first stages of these two amplifiers. These two BSA front-ends are fabricated in 130 and 180 nm CMOS processes, occupying 5.45 mm 2 and 0.352 mm 2 of die areas, respectively (excluding pad rings). The CMOS 130-nm amplifier array is comprised of 64 elements, where each amplifier element consumes 0.216 μW from 0.4 V supply, has input-referred noise voltage (IRNoise) of 2.19 μV[Formula: see text] corresponding to a power efficiency factor (PEF) of 11.7, and occupies 0.044 mm 2 of die area. The CMOS 180 nm amplifier array employs 4 elements, where each element consumes 0.69 μW from 0.6 V supply with IRNoise of 2.3 μV[Formula: see text] (corresponding to a PEF of 31.3) and 0.051 mm 2 of die area. Noninvasive electroencephalographic and invasive electrocorticographic signals were recorded real time directly on able-bodied human subjects, showing feasibility of using these analog front-ends for future fully implantable BSA and brain- computer interface systems.

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Year:  2017        PMID: 28783638      PMCID: PMC6508959          DOI: 10.1109/TBCAS.2017.2723607

Source DB:  PubMed          Journal:  IEEE Trans Biomed Circuits Syst        ISSN: 1932-4545            Impact factor:   3.833


  1 in total

1.  A benchtop system to assess the feasibility of a fully independent and implantable brain-machine interface.

Authors:  Po T Wang; Everardo Camacho; Ming Wang; Yongcheng Li; Susan J Shaw; Michelle Armacost; Hui Gong; Daniel Kramer; Brian Lee; Richard A Andersen; Charles Y Liu; Payam Heydari; Zoran Nenadic; An H Do
Journal:  J Neural Eng       Date:  2019-11-12       Impact factor: 5.379

  1 in total

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