A 0.016 mm2 12 b \Delta \Sigma SAR With 14 fJ/conv. for Ultra Low Power Biosensor Arrays
The instrumentation systems for implantable brain- machine interfaces represent one of the most demanding applications for ultra low-power analogue-to-digital-converters (ADC) to date. To address this challenge, this paper proposes a ΔΣSAR topology for very large sensor arrays that allows an excepti...
Gespeichert in:
Veröffentlicht in: | IEEE transactions on circuits and systems. I, Regular papers Regular papers, 2017-10, Vol.64 (10), p.2655-2665 |
---|---|
Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | The instrumentation systems for implantable brain- machine interfaces represent one of the most demanding applications for ultra low-power analogue-to-digital-converters (ADC) to date. To address this challenge, this paper proposes a ΔΣSAR topology for very large sensor arrays that allows an exceptional reduction in silicon footprint by using a continuous time 0-2MASH topology. This configuration uses a specialized FIR window to decimate the ΔΣ modulator output and reject mismatch errors from the SAR quantizer, which mitigates the overhead from dynamic element matching techniques commonly used to achieve high precision. A fully differential prototype was fabricated using 0.18 μm CMOS to demonstrate 10.8 ENOB precision with a 0.016 mm 2 silicon footprint. Moreover, a 14 fJ/conv figure-of-merit can be achieved, while resolving signals with the maximum input amplitude of ±1.2 Vpp sampled at 200 kS/s. The ADC topology exhibits a number of promising characteristics for both high speed and ultra low-power systems due to the reduced complexity, switching noise, sampling load, and oversampling ratio, which are critical parameters for many sensor applications. |
---|---|
ISSN: | 1549-8328 1558-0806 |
DOI: | 10.1109/TCSI.2017.2703580 |