@inbook{57aa697a727341e78be05df59073307f,
title = "Low power IoT platform for vital signs monitoring",
abstract = "Recent years have witnessed tremendous advances in wearable technology with many applications ranging from health and fitness, sports, security, and more recently augmented reality. Classical body area networks have been reduced to small, wearable devices such as smart watches where signal acquisition is accompanied by processing or streaming to a more powerful device such as a smart phone (or 'fog'), or directly to the Cloud. We present a system based around EPIC electric potential sensors which are capable of acquiring bio-electric signals, including an electrocardiogram-like signal (ECG). The paper compares a set of validation algorithms for the extraction of Heart Rate (HR) and Respiratory Rate (RR) suitable for use on EPIC sensor data acquired with the proposed system. These algorithms are evaluated in terms of precision and the estimated robustness and variance. The system is of particular relevance in the field of Augmented and Virtual Reality, in which such a miniaturised, wireless platform becomes a necessity [1].",
keywords = "Augmented and Virtual Reality, electric potential sensors, electrocardiogram, heart rate, internet of things, low power embedded systems, respiratory rate",
author = "Simon Coulter and M. Mostes and G. Lightbody and E. Popovici and W. Fennell",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 28th Irish Signals and Systems Conference, ISSC 2017 ; Conference date: 20-06-2017 Through 21-06-2017",
year = "2017",
month = jul,
day = "18",
doi = "10.1109/ISSC.2017.7983641",
language = "English",
series = "2017 28th Irish Signals and Systems Conference, ISSC 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2017 28th Irish Signals and Systems Conference, ISSC 2017",
address = "United States",
}