tinyCare: A tinyML-based Low-Cost Continuous Blood Pressure Estimation on the Extreme Edge

We propose a solution that deploys Machine Learning (ML) techniques on resource-constrained edge devices (tinyMl)for the healthcare domain. In particular, we construct a complete end-to-end prototyped system that conducts ML inference with various ML techniques on microcontroller unit (MCU)-powered edge devices to predict blood-pressure-related vital metrics such as systolic (SBP), diastolic (DBP), and mean arterial (MAP) blood pressures using …