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Fog computing in healthcare Internet of Things: A case study on ECG feature extraction
KTH, School of Information and Communication Technology (ICT), Industrial and Medical Electronics. University of Turku, Finland.
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2015 (English)In: Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015, Institute of Electrical and Electronics Engineers (IEEE), 2015, 356-363 p., 7363093Conference paper (Refereed)Text
Abstract [en]

Internet of Things technology provides a competent and structured approach to improve health and wellbeing of mankind. One of the feasible ways to offer healthcare services based on IoT is to monitor humans health in real-time using ubiquitous health monitoring systems which have the ability to acquire bio-signals from sensor nodes and send the data to the gateway via a particular wireless communication protocol. The real-time data is then transmitted to a remote cloud server for real-time processing, visualization, and diagnosis. In this paper, we enhance such a health monitoring system by exploiting the concept of fog computing at smart gateways providing advanced techniques and services such as embedded data mining, distributed storage, and notification service at the edge of network. Particularly, we choose Electrocardiogram (ECG) feature extraction as the case study as it plays an important role in diagnosis of many cardiac diseases. ECG signals are analyzed in smart gateways with features extracted including heart rate, P wave and T wave via a flexible template based on a lightweight wavelet transform mechanism. Our experimental results reveal that fog computing helps achieving more than 90% bandwidth efficiency and offering low-latency real time response at the edge of the network.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2015. 356-363 p., 7363093
Keyword [en]
ECG feature extraction, Fog computing, Healthcare, Heart rate, Internet of Things, Sensor network, Smart gateway, Biomedical signal processing, Computer circuits, Data mining, Data visualization, Diagnosis, Digital storage, Distributed computer systems, Electrocardiography, Extraction, Feature extraction, Fog, Health, Health care, Heart, Internet, Monitoring, Real time systems, Reconfigurable hardware, Seismic waves, Sensor networks, Sensor nodes, Ubiquitous computing, Wavelet transforms, Wireless telecommunication systems, Bandwidth efficiency, ECG Feature extractions, Health monitoring system, Heart rates, Internet of things technologies, Notification Service, Ubiquitous health monitoring, Wireless communication protocols, Gateways (computer networks)
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-186795DOI: 10.1109/CIT/IUCC/DASC/PICOM.2015.51ISI: 000380514500051ScopusID: 2-s2.0-84964284114ISBN: 9781509001545OAI: oai:DiVA.org:kth-186795DiVA: diva2:930294
Conference
15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015, 26 October 2015 through 28 October 2015
Note

QC 20160523 QC 20160922

Available from: 2016-05-23 Created: 2016-05-13 Last updated: 2016-09-22Bibliographically approved

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Rahmani, AmirTenhunen, Hannu
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