A Pixelated Monolithic CMOS PPG Sensor for Spatial Feature Acquisition Soo-Hun K

Abstract

This article presents a pixelated monolithic CMOS photoplethysmography (PPG) sensor. The spiking neural network (SNN)-inspired architecture, which includes an unbiased pho- todiode (PD)-based light-to-digit al converter (LDC), efficiently converts spatial features of PPG signals to multiple pixelated outputs. The sensor consists of 144 light-sensing neurons (LSNs) and simultaneously generates 1 b 12 row/12 column-wise pix- elated outputs. The spatial features of the PPG signals are thoroughly stu