An Ultra Low Power Pulse Oximeter Sensor Based on Compressed Sensing

Abstract

We describe an ultra low power pulse oximeter sensor for long term, non-invasive monitoring of SpO2 and heart rate in Body Area Networks (BAN). Commercial pulse oximeter sensors consume about 20-60 mW of power during continuous operation. Other researchers have shown that accurate and noise robust wireless pulse oximeter sensors can be designed to operate with as little as 1.5 mW. The LEDs consume bulk of the power budget in pulse oximeter sensors. In this work, we describe a compressed sensing approach to sample the photodetector output, so that the LEDs can be turned off for longer periods and thus save sensor power. We randomly sample Photoplethysmogram (PPG) signals with about 10-40x fewer samples than with uniform sampling and demonstrate that the accuracy of heart rate estimation and blood pressure estimation are not compromised, using MIMIC database. This provides power savings of the order of 10-40x for a pulse oximeter sensor, by reducing the duration LEDs need to be turned on.