An Error-Based Approximation Sensing Circuit for Event-Triggered, Low Power Wearable Sensors

TL;DR

This paper introduces a novel error-based event-driven sampling circuit for wearable sensors, significantly reducing data and power consumption while maintaining signal fidelity, enabling more efficient and longer-lasting wearable devices.

Contribution

The design and validation of the Polygonal Approximation Sampler (PAS), a reconfigurable event-based sampling circuit that outperforms traditional periodic sampling in wearable sensor applications.

Findings

Up to 99% data reduction for single-channel signals.

Up to 80% data reduction for multi-channel signals.

Maintains signal quality with minor performance degradation.

Abstract

Event-based sensors have the potential to optimize energy consumption at every stage in the signal processing pipeline, including data acquisition, transmission, processing and storage. However, almost all state-of-the-art systems are still built upon the classical Nyquist-based periodic signal acquisition. In this work, we design and validate the Polygonal Approximation Sampler (PAS), a novel circuit to implement a general-purpose event-based sampler using a polygonal approximation algorithm as the underlying sampling trigger. The circuit can be dynamically reconfigured to produce a coarse or a detailed reconstruction of the analog input, by adjusting the error threshold of the approximation. The proposed circuit is designed at the Register Transfer Level and processes each input sample received from the ADC in a single clock cycle. The PAS has been tested with three different types of archetypal signals captured by wearable devices (electrocardiogram, accelerometer and respiration data) and compared with a standard periodic ADC. These tests show that single-channel signals, with slow variations and constant segments (like the used single-lead ECG and the respiration signals) take great advantage from the used sampling technique, reducing the amount of data used up to 99% without significant performance degradation. At the same time, multi-channel signals (like the six-dimensional accelerometer signal) can still benefit from the designed circuit, achieving a reduction factor up to 80% with minor performance degradation. These results open the door to new types of wearable sensors with reduced size and higher battery lifetime.