- -

Performance assessment of a closed-loop system for diabetes management

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Performance assessment of a closed-loop system for diabetes management

Mostrar el registro sencillo del ítem

Ficheros en el ítem

dc.contributor.author Martínez Millana, Antonio es_ES
dc.contributor.author Fico, G. es_ES
dc.contributor.author Fernández Llatas, Carlos es_ES
dc.contributor.author Traver Salcedo, Vicente es_ES
dc.date.accessioned 2016-06-13T07:11:59Z
dc.date.available 2016-06-13T07:11:59Z
dc.date.issued 2015-12
dc.identifier.issn 0140-0118
dc.identifier.uri http://hdl.handle.net/10251/65700
dc.description.abstract Telemedicine systems can play an important role in the management of diabetes, a chronic condition that is increasing worldwide. Evaluations on the consistency of information across these systems and on their performance in a real situation are still missing. This paper presents a remote monitoring system for diabetes management based on physiological sensors, mobile technologies and patient/ doctor applications over a service-oriented architecture that has been evaluated in an international trial (83,905 operation records). The proposed system integrates three types of running environments and data engines in a single serviceoriented architecture. This feature is used to assess key performance indicators comparing them with other type of architectures. Data sustainability across the applications has been evaluated showing better outcomes for full integrated sensors. At the same time, runtime performance of clients has been assessed spotting no differences regarding the operative environment es_ES
dc.description.sponsorship The authors wish to acknowledge the consortium of the METABO project (funded by the European Commission, Grant nr. 216270) for their commitment during concept development and trial execution. en_EN
dc.language Inglés es_ES
dc.publisher Springer Verlag (Germany) es_ES
dc.relation.ispartof Medical and Biological Engineering and Computing es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject MHealth es_ES
dc.subject SOA es_ES
dc.subject Diabetes es_ES
dc.subject Sensors es_ES
dc.subject Telemonitoring es_ES
dc.subject Performance es_ES
dc.subject KPI es_ES
dc.subject.classification TECNOLOGIA ELECTRONICA es_ES
dc.title Performance assessment of a closed-loop system for diabetes management es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s11517-015-1245-3
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/216270/EU/Controlling Chronic Diseases related to Metabolic Disorders/
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Universitario de Aplicaciones de las Tecnologías de la Información - Institut Universitari d'Aplicacions de les Tecnologies de la Informació es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica es_ES
dc.description.bibliographicCitation Martínez Millana, A.; Fico, G.; Fernández Llatas, C.; Traver Salcedo, V. (2015). Performance assessment of a closed-loop system for diabetes management. Medical and Biological Engineering and Computing. 53(12):1295-1303. doi:10.1007/s11517-015-1245-3 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.1007/s11517-015-1245-3 es_ES
dc.description.upvformatpinicio 1295 es_ES
dc.description.upvformatpfin 1303 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 53 es_ES
dc.description.issue 12 es_ES
dc.relation.senia 291455 es_ES
dc.description.references Bellazzi R, Larizza C, Montani A et al (2002) A telemedicine support dor diabetes management: the T-IDDM project. Comput Methods Programs Biomed 69:147–161 es_ES
dc.description.references Boloor K, Chirkova R, Salo T, Viniotis Y (2011) Analysis of response time percentile service level agreements in soa-based applications. IEEE global telecommunications conference (GLOBECOM 2011), dec. 2011, pp 1–6 es_ES
dc.description.references Cartwright M et al (2013) Effect of telehealth on quality of life and psychological outcomes over 12 months: nested study of patient reported outcomes in a pragmatic, cluster randomised controlled trial. BMJ 346:f653 es_ES
dc.description.references Chen I-Y et al (2008) Pervasive digital monitoring and transmission of pre-care patient biostatics with an OSGi, MOM and SOA based remote health care system. In: Proceedings of the 6th annual IEEE international conference on PerCom. Hong Kong es_ES
dc.description.references Fico G, Fioravanti A, Arredondo MT, Leuteritz JP, Guillén A, Fernandez D (2011) A user centered design approach for patient interfaces to a diabetes IT platform. Conf Proc IEEE Eng Med Biol Soc 2011:1169–1172 es_ES
dc.description.references Fioravanti A, Fico G, Arredondo MT, Salvi D, Villalar JL (2010) Integration of heterogeneous biomedical sensors into an ISO/IEEE 11073 compliant application. In: Engineering in medicine and biology society (EMBC), 2010 Annual international conference of the IEEE, pp 1049–1052 es_ES
dc.description.references García Saez G et al (2009) Architecture of a wireless personal assistant for telemedical diabetes care. Int J Med Inform 9(78):391–403 es_ES
dc.description.references Gómez EJ, Hernando ME et al (2008) The INCA system: a further step towards a telemedical artificial pancreas. IEEE Trans Inf Technol Biomed 12(4):470–479 es_ES
dc.description.references Harrison’s Principles of Internal Medicine (2011) McGraw-Hill. ISBN:978-0071748896. Ed. July 2011 es_ES
dc.description.references Ke X, Li W et al (2010) WCDMA KPI framework definition methods and applications. ICCET proceedings V4-471–V4-475 es_ES
dc.description.references Klonof D (2013) Twelve modern digital technologies that are transforming decision making for diabetes and all areas of health care. J Diabetes Sci Technol 7(2):291–295 es_ES
dc.description.references Lanzola G et al (2007) Going mobile with a multiaccess service for the management of diabetic patients. J Diabetes Sci Technol 1(5):730–737 es_ES
dc.description.references Ma C et al (2006) Empowering patients with essential information and communication support in the context of diabetes. Int J Med Inform 75(8):577–596 es_ES
dc.description.references Müller AJ, Knuth M, Nikolaus KS, Krivánek R, Küster F, Hasslacher C (2013) First clinical evaluation of a new percutaneous optical fiber glucose sensor for continuous glucose monitoring in diabetes. J Diabetes Sci Technol 7:13 es_ES
dc.description.references Nundy S et al (2012) Using mobile health to support chronic care model: developing an institutional model. Int J Telemed Appl 2012, Art Id 871925. doi: 10.1155/2012/871925 es_ES
dc.description.references Obstfelder A, Engeseth KH, Wynn R (2007) Characteristic of succesfully implemented telemedical applications. Implement Sci 2:25 es_ES
dc.description.references Pravin P et al (2012) A framework for the comparison of mobile patient monitoring systems. J Biomed Inf 45:544–556 es_ES
dc.description.references Reichel A, Rietzsch H, Ludwig B, Röthig K, Moritz A, Bornstein S (2013) Self-adjustment of insulin dose using graphically depicted self-monitoring of blood glucose measurements in patients with type 1 diabetes mellitus. J Diabetes Sci Technol 7(1):156–162 es_ES
dc.description.references Ryan D et al (2012) Clinical and cost effectiveness of mobile phone supported self-monitoring of asthma: multicenter randomized controlled trial. BMJ 344:e1756 es_ES
dc.description.references Schade DS et al (2005) To pump or not to pump. Diabetes Technol Therapeutics 7:845–848 es_ES
dc.description.references Stravroula G, Bartsocas CS et al (2010) SMARTDIAB: a communication and information technology approach for the intelligent monitoring, management and follow-up of type 1 diabetes patients. IEEE Trans Inf Technol Biomed 14(3):622–633 es_ES
dc.description.references The Diabetes Control and Complications Trial Research Group (1993) The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N Engl J Med 329(14):977–986 es_ES
dc.description.references Trief PM, Morin PC, Izquierdo R, Teresi JA, Eimicke JP, Goland R, Starren J, Shea S, Winstock RS (2006) Depression and glycaemic control in elderly etchnically diverse patients with diabetes: the IDEATel project. Diabetes Care 29(4):830–835 es_ES
dc.description.references van der Weegentres S et al (2013) The development of a mobile monitoring and feedback tool to stimulate physical activity of people with a chronic disease in primary care: a user-centered design. JMIR 1(2):e8 es_ES
dc.description.references Wakefield BJ et al (2014) Effect of home telemonitoring on glycemic and blood pressure control in primary care clinic patients with diabetes. Telemed e-Health 20(3):199–205. doi: 10.1089/tmj.2013.0151 es_ES
dc.description.references Winkler S et al (2011) A new telemonitoring system intended for chronic heart failure patients using mobile technology—Feasibility Study. Int J Cardiol 153:55–58 es_ES
dc.description.references Zhou YY, Kanter MH, Wang JJ, Garrido T (2010) Improved quality at kaiser permanente through e-mail between physicians and patients. Health Aff 29(7):1370–1375 es_ES


Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem