An IoT Smart Environment in Support of Disease Diagnosis Decentralization

Abstract

The percentage of seniors in the global population is constantly growing and solutions in the field of fall detection and early detection of neuro-degenerative pathologies have a crucial role in order to increase life expectancy and quality of life. This study aims to extend fall detection and effective recognition of early signs of diseases to new smart environments, conceiving the decentralization of diagnostic monitoring in everyday life activities in a more pervasive paradigm. Inspiring to research outcomes, in this work an architecture is designed to detect falls in crowded indoor environments during events/exhibitions, for favoring a timely and effective intervention. It also foresees a continue monitoring of the gait for seniors during the visit, thus extracting key features which are stored on a dedicated database. The proposed solution allows third party researchers to perform analysis on the obtained gait datasets, through the adoption of advanced data-mining techniques for the detection of early signs of neuro-degenerative diseases and other pathologies. The architecture designed here aims to provide a step forward concerning the extension of smart monitoring environments for the detection of falls and early signs of pathologies in everyday life, in a more pervasive and decentralized paradigm.

Internet of Things (IoT)-Based Wireless Health: Enabling Technologies and Applications

“…Two papers introduce a couple of emerging concepts expected to be useful in advancing IoT-based wireless health [12,13]. The article [12] introduces an IoT-based smart environment that helps to implement decentralization in disease diagnosis. On the one hand, the work is able to perform fall detection in crowded indoor environments.…”