Journal Article10.1109/TBCAS.2007.907868
An Energy-Efficient Micropower Neural Recording Amplifier
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TL;DR: The amplifier appears to be the lowest power and most energy-efficient neural recording amplifier reported to date and the low-noise design techniques that help the neural amplifier achieve input-referred noise that is near the theoretical limit of any amplifier using a differential pair as an input stage.
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Abstract: This paper describes an ultralow-power neural recording amplifier. The amplifier appears to be the lowest power and most energy-efficient neural recording amplifier reported to date. We describe low-noise design techniques that help the neural amplifier achieve input-referred noise that is near the theoretical limit of any amplifier using a differential pair as an input stage. Since neural amplifiers must include differential input pairs in practice to allow robust rejection of common-mode and power supply noise, our design appears to be near the optimum allowed by theory. The bandwidth of the amplifier can be adjusted for recording either neural spikes or local field potentials (LFPs). When configured for recording neural spikes, the amplifier yielded a midband gain of 40.8 dB and a -3-dB bandwidth from 45 Hz to 5.32 kHz; the amplifier's input-referred noise was measured to be 3.06 muVrms while consuming 7.56 muW of power from a 2.8-V supply corresponding to a noise efficiency factor (NEF) of 2.67 with the theoretical limit being 2.02. When configured for recording LFPs, the amplifier achieved a midband gain of 40.9 dB and a -3-dB bandwidth from 392 mHz to 295 Hz; the input-referred noise was 1.66 muVrms while consuming 2.08 muW from a 2.8-V supply corresponding to an NEF of 3.21. The amplifier was fabricated in AMI's 0.5-mum CMOS process and occupies 0.16 mm2 of chip area. We obtained successful recordings of action potentials from the robust nucleus of the arcopallium (RA) of an anesthesized zebra finch brain with the amplifier. Our experimental measurements of the amplifier's performance including its noise were in good accord with theory and circuit simulations.
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Citations
A Low Noise Low Power OTA with Adjustable Gain PID Feedback Network for EEG SoC Arrays
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Low-Power Biomedical Interfaces
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TL;DR: The state of the art of instrumentation architectures in the field of biomedical instrumentation is presented and their use in wearable and implantable biomedical signal acquisition systems are discussed.
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