A Sparse Sampling Sensor Front-end IC for Low Power Continuous SpO$_2$ \& HR Monitoring
Sina Faraji Alamouti, Jasmine Jan, Cem Yalcin, Jonathan Ting, Ana, Claudia Arias, and Rikky Muller

TL;DR
This paper introduces a low-power sensor IC for continuous SpO2 and HR monitoring that uses a novel sparse sampling algorithm to significantly reduce power consumption while maintaining accuracy, suitable for flexible organic or silicon photodiodes.
Contribution
It presents a reconstruction-free sparse sampling algorithm integrated into a sensor IC, reducing power consumption by 70% without sacrificing measurement accuracy.
Findings
Achieved less than 1 bpm HR error in vivo.
Reduced power consumption by approximately 70%.
Validated performance against clinical reference standards.
Abstract
Photoplethysmography (PPG) is an attractive method to acquire vital signs such as heart rate and blood oxygenation and is frequently used in clinical and at-home settings. Continuous operation of health monitoring devices demands a low power sensor that does not restrict the device battery life. Silicon photodiodes (PD) and LEDs are commonly used as the interface devices in PPG sensors; however, using of flexible organic devices can enhance the sensor conformality and reduce the cost of fabrication. In most PPG sensors, most of system power consumption is concentrated in powering LEDs, traditionally consuming mWs. Using organic devices further increases this power demand since these devices exhibit larger parasitic capacitances and typically need higher drive voltages. This work presents a sensor IC for continuous SpO and HR monitoring that features an on-chip reconstruction-free…
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Taxonomy
TopicsEEG and Brain-Computer Interfaces · ECG Monitoring and Analysis · Analog and Mixed-Signal Circuit Design
