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AuthorHeurtefeux, Karel
AuthorMohsin, Nasreen
AuthorMenouar, Hamid
AuthorAbuali, Najah
Available date2025-10-16T07:06:41Z
Publication Date2015-01-20
Publication NameProceedings of the 2014 4th International Conference on Wireless Mobile Communication and Healthcare Transforming Healthcare Through Innovations in Mobile and Wireless Technologies Mobihealth 2014
Identifierhttp://dx.doi.org/10.1109/MOBIHEALTH.2014.7015953
CitationK. Heurtefeux, N. Mohsin, H. Menouar and N. AbuAli, "Prediction of time series using ARMA models in an energy-efficient body area network," 2014 4th International Conference on Wireless Mobile Communication and Healthcare - Transforming Healthcare Through Innovations in Mobile and Wireless Technologies (MOBIHEALTH), Athens, Greece, 2014, pp. 230-233, doi: 10.4108/Mobihealth33544.2014.7015953.
URIhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84925359258&origin=inward
URIhttp://hdl.handle.net/10576/67960
AbstractThis paper investigates the tradeoff between accuracy and complexity cost to predict electrocardiogram values using auto-regressive moving average (ARMA) models in a fully functional body area network (BAN) platform. The proposed BAN platform captures, processes, and wirelessly transmits six-degrees-of-freedom inertial and electrocardiogram data in a wearable, non-invasive form factor. To reduce the number of packets sent, ARMA models are used to predict electrocardiogram (ECG) values. However, in the context of wearable devices, where the computing and memory capabilities are limited, the prediction model should be both accurate and lightweight. To this end, the goodness of the ARMA parameters is quantified considering ECG signal, we compute Akaike Information Criterion (AIC) on more than 900000 ECG measures. Finally, a tradeoff is given accordingly to the hardware constraints.
SponsorThis work was made possible by NPRP grant #NPRP4-553–2-210 from the Qatar National Research Fund (a member of The Qatar Foundation). The statements made herein are solely the responsibility of the authors.
Languageen
PublisherIEEE
SubjectAkaike
Autoregressive moving average
Body area network
Energy efficiency
TitlePrediction of time series using ARMA models in an energy-efficient body area network
TypeConference
Pagination230-233
EISBN978-1-63190-014-3
dc.accessType Full Text


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