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A 0.0918mm2 73-dB SNDR 10-kHz BW VCO-Based CT ΔΣ Modulator for Artifact-Tolerant Neural Recording Front Ends | IEEE Conference Publication | IEEE Xplore

A 0.0918mm2 73-dB SNDR 10-kHz BW VCO-Based CT ΔΣ Modulator for Artifact-Tolerant Neural Recording Front Ends


Abstract:

This article presents a voltage-controlled oscillator (VCO)-based continuous-time (CT) sigma delta modulator for recording neural signals. The first integrator of the mod...Show More

Abstract:

This article presents a voltage-controlled oscillator (VCO)-based continuous-time (CT) sigma delta modulator for recording neural signals. The first integrator of the modulator utilizes a Gm-c structure, which enhances the transconductance of the integrator through an booster amplifier, and uses source degradation to increase the linearity of the integrator. The integrator and DAC apply current reuse techniques to ensure the normal operation of the integrator while increasing the linear input range of the system and greatly reducing the system power consumption. The second integrator adopts a VCO structure and uses PFD to extract phase information while also achieving multi-bit quantization. Compared with traditional second-order CTDSM, the power consumption is lower and the system is more digital. Fabricated in 180-nm CMOS, the prototype modulator achieves 73dB SNDR in 10kHz bandwidth,0.0918mm2 active area,300-mVpp linear input range and consumes 11.27μW.
Date of Conference: 03-05 November 2023
Date Added to IEEE Xplore: 15 February 2024
ISBN Information:
Conference Location: Nanjing, China

I. INTRODUCTION

With the continuous advancement of CMOS technology, neural recording circuits have developed rapidly towards digitization, compactness, and low power consumption. The early neural recording systems were mainly composed of instrument amplifiers (IA) and low resolution analog-to-digital converter (ADC) [1] - [3]. IA had the characteristics of high gain and low input noise, but the high gain of amplifiers easily saturate the stimulation artifacts, thus this approach only supports acquisition scenarios without artifacts. In recent years, a novel approach of directly collect neural signals with high resolution and low power ADC has been proposed, which can accurately collect neural signals and stimulation artifacts [4] - [5]. The structure of the two solutions is shown in Figure 1.

References

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