Adaptive asynchronous analog to digital conversion for compressed biomedical sensing

Agarwal, Ruchi; Trakimas, Michael; Sonkusale, Sameer

doi:10.1109/biocas.2009.5372083

Cited by 9 publications

(1 citation statement)

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“…Many of the recorded signals (especially ECG [4] and EAPs) however exhibit short active periods in the form of spikes interrupting potentially long silent periods. This can lead to significant oversampling if those signals are sampled uniformly.…”

Section: Introductionmentioning

confidence: 99%

Continuous-Time Acquisition of Biosignals Using a Charge-Based ADC Topology

Maslik

Liu

Lande

et al. 2018

IEEE Trans. Biomed. Circuits Syst.

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This paper investigates continuous-time (CT) signal acquisition as an activity-dependent and nonuniform sampling alternative to conventional fixed-rate digitisation. We demonstrate the applicability to biosignal representation by quantifying the achievable bandwidth saving by nonuniform quantisation to commonly recorded biological signal fragments allowing a compression ratio of 5 and 26 when applied to electrocardiogram and extracellular action potential signals, respectively. We describe several desirable properties of CT sampling, including bandwidth reduction, elimination/reduction of quantisation error, and describe its impact on aliasing. This is followed by demonstration of a resource-efficient hardware implementation. We propose a novel circuit topology for a charge-based CT analogue-to-digital converter that has been optimized for the acquisition of neural signals. This has been implemented in a commercially available 0.35 CMOS technology occupying a compact footprint of 0.12 mm. Silicon verified measurements demonstrate an 8-bit resolution and a 4 kHz bandwidth with static power consumption of 3.75 W from a 1.5 V supply. The dynamic power dissipation is completely activity-dependent, requiring 1.39 pJ energy per conversion.

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Section: Introductionmentioning

confidence: 99%