IoT-Based Smart Edge for Global Health: Remote Monitoring With Severity Detection and Alerts Transmission

Global health which denotes equitable access to healthcare, particularly in remote-rural-developing regions, is characterized by unique challenges of affordability , accessibility , and availability for which one of the most promising technological interventions that is emerging is the Internet of T...

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Bibliographic Details
Published in:IEEE internet of things journal 2019-04, Vol.6 (2), p.2449-2462
Main Authors: Pathinarupothi, Rahul Krishnan, Durga, P, Rangan, Ekanath Srihari
Format: Article
Language:English
Subjects:
Bandwidths
Biomedical monitoring
Cardiology
Electrocardiography
Health
Internet of Things
Internet of Things (IoT)
Logic gates
m-Health
machine learning
Medical services
Monitoring
Performance evaluation
Physicians
Remote monitoring
Remote sensors
Sensors
smart health
wearable sensors
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Summary:Global health which denotes equitable access to healthcare, particularly in remote-rural-developing regions, is characterized by unique challenges of affordability , accessibility , and availability for which one of the most promising technological interventions that is emerging is the Internet of Things (IoT)-based remote health monitoring. We present an IoT-based smart edge system for remote health monitoring, in which wearable vital sensors transmit data into two novel software engines, namely rapid active summarization for effective prognosis (RASPRO) and criticality measure index (CMI) alerts, both of which we have implemented in the IoT smart edge. RASPRO transforms voluminous sensor data into clinically meaningful summaries called personalized health motifs (PHMs). The CMI alerts engine computes an aggregate criticality score. Our IoT smart edge employs a risk-stratified protocol consisting of rapid guaranteed push of alerts and PHMs directly to the physicians, and best effort pull of detailed data-on-demand through the cloud. We have carried out both clinical validation and performance evaluation of our smart edge system. The clinical validation on 183 patients demonstrated that the IoT smart edge is highly effective in remote monitoring, advance warning and detection of cardiac conditions, as quantified by three measures, precision (0.87), recall (0.83), and F1-score (0.85). Furthermore, performance evaluation showed significant reductions in the bandwidth (98%) and energy (90%), thereby making it suitable for emerging narrow-band IoT networks. In the deployment of our system in the cardiology institute of our University hospital, we observed that our IoT smart edge helped to increase the availability of physicians by 59%. Hence, our IoT smart edge system is a significant step toward addressing the requirements for global health.
ISSN:2327-4662
2327-4662
DOI:10.1109/JIOT.2018.2870068