A Wide Dynamic Range Neural Data Acquisition System With High-Precision Delta-Sigma ADC and On-Chip EC-PC Spike...

Area of Science:

• Biomedical Engineering
• Neuroscience
• Electrical Engineering

Background:

• Advanced bidirectional neuromodulation technologies require high-performance neural interfaces.
• Existing systems often face limitations in dynamic range, power consumption, and real-time processing capabilities.

Purpose of the Study:

• To develop and demonstrate a proof-of-concept neural data acquisition (DAQ) system.
• To integrate a low-power, high-precision analog-to-digital converter (ADC) and a real-time spike processor.
• To support closed-loop control and neural information decoding for neuromodulation.

Main Methods:

• Designed a 15-bit, low-power Delta-Sigma ADC utilizing techniques like opamp-sharing and multi-bit SAR quantizer.
• Implemented a real-time spike processor using an exponential component-polynomial component (EC-PC) algorithm.
• Fabricated the prototype chip in a 0.13 μm CMOS process and conducted bench-top and In-Vivo experiments.

Main Results:

• The ADC achieved a peak signal-to-noise and distortion ratio (SNDR) of 91.8 dB and a dynamic range of 93.0 dB.
• The system demonstrated a low power consumption of 20 μW with a figure-of-merit (FOM) of 31.4 fJ/conversion-step.
• Successfully acquired high-quality neural activities from a rat's motor cortex and reduced system saturation recovery time.

Conclusions:

• The developed DAQ system offers a high-performance, low-power solution for neural data acquisition.
• The integrated EC-PC spike processor enables efficient real-time neural signal processing.
• This system is suitable for advanced bidirectional neuromodulation applications requiring closed-loop control.