Power-Efficient Respiratory Rate Estimation via Minimal Sensing
Edgar J Lobaton
Project runs from 09/01/2015 to 08/31/2019
The project aims to develop a framework for collecting and pre-processing data from wearable sensing devices in the lab and real-world scenarios. We will aim to characterize their signal quality. We will make use of a system which allows users to wear various devices for weeks at the time, stream the data to an aggregator and then to the cloud. The ASSIST HET device will be integrated in this pipeline, and we will aim to integrate all data into a database that can be used by the center. The database will provide a frontend for collaborators and partners to access ASSIST data. Signal descriptors will be computed in order to characterize the quality of the signals and the presence of artifacts. We will focus our analysis on heart rate (HR) and heart rate variability (HRV). We will perform the analyzes on the data captured by the IRB protocol from Dr. Lobaton’s team using multiple wearable devices including the HET, as well as the data from Dr. Michelle Hernandez’s protocols.