A novel gateway-based solution for remote elderly monitoring

Issam Boukhennoufa; Abbes Amira; Faycal Bensaali; Sahar Soheilian Esfahani

doi:10.1016/j.jbi.2020.103521

A novel gateway-based solution for remote elderly monitoring

J Biomed Inform. 2020 Sep:109:103521. doi: 10.1016/j.jbi.2020.103521. Epub 2020 Jul 31.

Authors

Issam Boukhennoufa¹, Abbes Amira², Faycal Bensaali³, Sahar Soheilian Esfahani⁴

Affiliations

¹ College of Engineering, Qatar University, Doha, Qatar. Electronic address: issam.b@qu.edu.qa.
² Institute of Artificial Intelligence, De Montfort University, Leicester, United Kingdom. Electronic address: abbes.amira@dmu.ac.uk.
³ College of Engineering, Qatar University, Doha, Qatar. Electronic address: f.bensaali@qu.edu.qa.
⁴ College of Engineering, Qatar University, Doha, Qatar. Electronic address: sahar.esfahani@qu.edu.qa.

PMID: 32745621
DOI: 10.1016/j.jbi.2020.103521

Abstract

Internet of Things (IoT) technologies have been applied to various fields such as manufacturing, automobile industry and healthcare. IoT-based healthcare has a significant impact on real-time remote monitoring of patients' health and consequently improving treatments and reducing healthcare costs. In fact, IoT has made healthcare more reliable, efficient, and accessible. Two major drawbacks which IoT suffers from can be expressed as: first, thelimited battery capacityof thesensorsis quickly depleted due to the continuous stream of data; second, the dependence of the system on the cloud for computations and processing causes latency in data transmission which is not accepted in real-time monitoring applications. This research is conducted to develop a real-time, secure, and energy-efficient platform which provides a solution for reducing computation load on the cloud and diminishing data transmission delay. In the proposed platform, the sensors utilize a state-of-the-art power saving technique known as Compressive Sensing (CS). CS allows sensors to retrieve the sensed data using fewer measurements by sending a compressed signal. In this framework, the signal reconstruction and processing are computed locally on a Heterogeneous Multicore Platform (HMP) device to decrease the dependency on the cloud. In addition, a framework has been implemented to control the system, set different parameters, display the data as well as send live notifications to medical experts through the cloud in order to alert them of any eventual hazardous event or abnormality and allow quick interventions. Finally, a case study of the system is presented demonstrating the acquisition and monitoring of the data for a given subject in real-time. The obtained results reveal that the proposed solution reduces 15.4% of energy consumption in sensors, that makes this prototype a good candidate for IoT employment in healthcare.

Keywords: Assisted living; Clouds; Graphical user interfaces; Healthcare; Internet of Things; Remote monitoring.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Aged
Delivery of Health Care
Humans
Internet of Things*