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Related Experiment Video

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An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces
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A Low Noise Neural Recording Frontend IC With Power Management for Closed-Loop Brain-Machine Interface Application.

Weijian Chen, Weisong Liang, Xu Liu

    IEEE Transactions on Biomedical Circuits and Systems
    |October 9, 2023
    PubMed
    Summary

    This study presents a power management integrated circuit (PMIC) for brain-machine interfaces (BMI). The novel design ensures stable voltage for neural recording, crucial for treating neural diseases.

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    Area of Science:

    • Biomedical Engineering
    • Neuroscience
    • Integrated Circuit Design

    Background:

    • Implantable bioelectronics systems offer potential treatments for neural diseases.
    • Stable power supply is critical for the reliable operation of brain-machine interface (BMI) chips.

    Purpose of the Study:

    • To develop a prototype power management integrated circuit (PMIC) with heavy load capability.
    • To ensure a stable voltage supply for artifact-tolerant neural recording integrated circuits (ATNR-IC).

    Main Methods:

    • Proposed a reverse nested miller compensation (RNMC) low dropout regulator (LDO) with a transient enhancer for the PMIC.
    • Evaluated power consumption at standby (0.55 mW) and full stimulation (22.5 mW) loads.
    • Assessed LDO transient response with overshoot (110 mV) and downshoot (71 mV) during full load transitions.

    Main Results:

    • The PMIC provides a stable 3.3 V supply voltage under a load current peak-to-peak range of 560 μA from a 4-channel stimulator.
    • The system demonstrates potential for extension to scenarios with more stimulating channels.
    • The ATNR-IC, powered by the PMIC, amplified a 1 mVpp neural signal and 20 mVpp artifact by 28 dB without saturation.

    Conclusions:

    • The developed PMIC effectively supports neural recording and stimulation functions in BMI systems.
    • The design offers a stable and robust power solution for implantable bioelectronic devices.
    • This work contributes to advancing BMI technology for neural disease treatment.