Optimizing sampling rate of wrist-worn optical sensors for physiologic monitoring.

ABSTRACT:

Introduction

Personalized medicine has exposed wearable sensors as new sources of biomedical data which are expected to accrue annual data storage costs of approximately $7.2 trillion by 2020 (>2000 exabytes). To improve the usability of wearable devices in healthcare, it is necessary to determine the minimum amount of data needed for accurate health assessment.

Methods

Here, we present a generalizable optimization framework for determining the minimum necessary sampling rate for wearable sensors and apply our method to determine optimal optical blood volume pulse sampling rate. We implement t-tests, Bland-Altman analysis, and regression-based visualizations to identify optimal sampling rates of wrist-worn optical sensors.

Results

We determine the optimal sampl

SUBMITTER: Bent B 

PROVIDER: S-EPMC8057382 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature