Low-power high-resolution 32-channel neural recording system

Area of Science:

• Biomedical Engineering
• Integrated Circuits
• Neuroscience

Background:

• Neural recording systems are crucial for understanding brain activity.
• Existing systems often face limitations in power consumption and miniaturization.
• High-resolution analog-to-digital converters (ADCs) are essential for accurate neural signal digitization.

Purpose of the Study:

• To design and present a low-power, 32-channel neural recording system.
• To integrate high-resolution on-chip analog-to-digital converters (ADCs).
• To achieve a compact and power-efficient solution for neural data acquisition.

Main Methods:

• Developed a neural front-end with a low-noise, fully differential pre-amplifier, gain stage, and buffer.
• Integrated two 13-bit extended counting analog-to-digital converters (ADCs) operating at a 512 KHz sampling rate.
• Fabricated the prototype using a 0.6 micrometer CMOS process.

Main Results:

• The neural front-end exhibits a low power consumption of only 56 μW.
• The integrated system achieves a total chip power consumption of 22 mW with a 3.3V power supply.
• The entire system occupies a compact area of 3mm x 3mm.

Conclusions:

• The designed system offers a significant advancement in low-power, high-resolution neural recording.
• The compact size and low power consumption make it suitable for various implantable and wearable neurotechnology applications.
• This integrated design paves the way for more sophisticated and accessible brain-computer interfaces.