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AuthorAl Disi, Mohammed
AuthorDjelouat, Hamza
AuthorKotroni, Christos
AuthorPolitis, Elena
AuthorAmira, Abbes
AuthorBensaali, Faycal
AuthorDimitrakopoulos, George
AuthorAlinier, Guillaume
Available date2022-12-29T07:34:42Z
Publication Date2018
Publication NameIEEE Access
ResourceScopus
URIhttp://dx.doi.org/10.1109/ACCESS.2018.2877679
URIhttp://hdl.handle.net/10576/37810
AbstractRemote health monitoring is becoming indispensable, though, Internet of Things (IoTs)-based solutions have many implementation challenges, including energy consumption at the sensing node, and delay and instability due to cloud computing. Compressive sensing (CS) has been explored as a method to extend the battery lifetime of medical wearable devices. However, it is usually associated with computational complexity at the decoding end, increasing the latency of the system. Meanwhile, mobile processors are becoming computationally stronger and more efficient. Heterogeneous multicore platforms (HMPs) offer a local processing solution that can alleviate the limitations of remote signal processing. This paper demonstrates the real-time performance of compressed ECG reconstruction on ARM's big.LITTLE HMP and the advantages they provide as the primary processing unit of the IoT architecture. It also investigates the efficacy of CS in minimizing power consumption of a wearable device under real-time and hardware constraints. Results show that both the orthogonal matching pursuit and subspace pursuit reconstruction algorithms can be executed on the platform in real time and yield optimum performance on a single A15 core at minimum frequency. The CS extends the battery life of wearable medical devices up to 15.4% considering ECGs suitable for wellness applications and up to 6.6% for clinical grade ECGs. Energy consumption at the gateway is largely due to an active internet connection; hence, processing the signals locally both mitigates system's latency and improves gateway's battery life. Many remote health solutions can benefit from an architecture centered around the use of HMPs, a step toward better remote health monitoring systems. 2013 IEEE.
SponsorThis work was supported by the National Priorities Research Program (NPRP) from the Qatar National Research Fund (a member of Qatar Foundation) under Grant 9-114-2-055. The statements made herein are solely the responsibility of the authors. The publication of this article was funded by the Qatar National Library.
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
Subjectcompressed sensing
Connected health
energy efficiency
heterogeneous multicore platforms
internet of things
mobile real-time health monitoring
multicore processing
remote monitoring
wearable sensors
TitleECG Signal Reconstruction on the IoT-Gateway and Efficacy of Compressive Sensing under Real-Time Constraints
TypeArticle
Pagination69130-69140
Volume Number6
dc.accessType Open Access


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