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Stochastic modeling of wireless charged wearables for reliable health monitoring in hospital environments
dc.contributor.author | Mekikis, Prodromos Vasileios |
dc.contributor.author | Antonopoulos, Angelos |
dc.contributor.author | Kartsakli, Elli |
dc.contributor.author | Passas, Nikos |
dc.contributor.author | Alonso Zárate, Luis Gonzaga |
dc.contributor.author | Verikoukis, Christos |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions |
dc.date.accessioned | 2018-03-06T12:47:40Z |
dc.date.issued | 2017 |
dc.identifier.citation | Mekikis, P., Antonopoulos, A., Kartsakli, E., Passas, N., Alonso, L., Verikoukis, C. Stochastic modeling of wireless charged wearables for reliable health monitoring in hospital environments. A: IEEE International Conference on Communications. "2017 IEEE International Conference on Communications (ICC): 2017 IEEE International Conference on Communications (ICC) took place 21-25 May 2017 in Paris, France". Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 1-6. |
dc.identifier.isbn | 978-1-4673-8999-0 |
dc.identifier.uri | http://hdl.handle.net/2117/114854 |
dc.description.abstract | As wearables provide new health-related functionalities, they can be employed in hospitals to monitor patients and notify the medical personnel regarding their status. However, in order to be approved by the medical community, wearables need to have reliable communication and high lifetime. In such scenarios, it is important to know the probability of correct notification which is affected mainly by the deployment of the wireless wearables and their energy supply. Typically, rooms in hospitals host multiple people and, thus, a clustered communication model should be adopted for more trustworthy results. Moreover, by employing wireless charging, it is possible to provide an uninterrupted operation with high reliability. Therefore, in this paper, we study the aforementioned probability in a clustered network while the wearable devices are wirelessly charged. We provide an analytical model for the wearables' ability to inform quickly the medical personnel and discuss different trade-offs via extensive simulations. |
dc.format.extent | 6 p. |
dc.language.iso | eng |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) |
dc.subject | Àrees temàtiques de la UPC::Ciències de la salut |
dc.subject | Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica |
dc.subject.lcsh | Wearable technology |
dc.subject.lcsh | Wireless communication systems |
dc.subject.lcsh | Computational grids (Computer systems) |
dc.subject.other | Wearables |
dc.subject.other | Wireless Energy Harvesting |
dc.subject.other | Poisson Cluster Process |
dc.subject.other | Stochastic Geometry |
dc.subject.other | eHealth |
dc.title | Stochastic modeling of wireless charged wearables for reliable health monitoring in hospital environments |
dc.type | Conference report |
dc.subject.lemac | Comunicació sense fil, Sistemes de |
dc.subject.lemac | Computació distribuïda |
dc.contributor.group | Universitat Politècnica de Catalunya. WiComTec - Grup de recerca en Tecnologies i Comunicacions Sense Fils |
dc.identifier.doi | 10.1109/ICC.2017.7997412 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | http://ieeexplore.ieee.org/document/7997412/ |
dc.rights.access | Restricted access - publisher's policy |
local.identifier.drac | 21986700 |
dc.description.version | Postprint (published version) |
dc.date.lift | 10000-01-01 |
local.citation.author | Mekikis, P.; Antonopoulos, A.; Kartsakli, E.; Passas, N.; Alonso, L.; Verikoukis, C. |
local.citation.contributor | IEEE International Conference on Communications |
local.citation.publicationName | 2017 IEEE International Conference on Communications (ICC): 2017 IEEE International Conference on Communications (ICC) took place 21-25 May 2017 in Paris, France |
local.citation.startingPage | 1 |
local.citation.endingPage | 6 |