A Semantic Big Data Platform for Integrating Heterogeneous Wearable Data in Healthcare.
Advances supported by emerging wearable technologies in healthcare promise patients a provision of high quality of care. Wearable computing systems represent one of the most thrust areas used to transform traditional healthcare systems into active systems able to continuously monitor and control the...
| Publicado en: | Journal of Medical Systems Vol. 39; no. 12; pp. 1 - 9 |
|---|---|
| Autores principales: | , , , , |
| Formato: | pictorial tables/charts Journal Article |
| Publicado: |
Springer Nature
Dec2015
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=110463853&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 110463853 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Dec2015 vid: 39 iid: 12 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 110463853 110463853 110463853 10.1007/s10916-015-0344-x NLM26490143 110463853 ppf: 1 ppct: 8 formats: fmt: @attributes: type: P tig: atl: A Semantic Big Data Platform for Integrating Heterogeneous Wearable Data in Healthcare. aug: au: Mezghani, Emna Exposito, Ernesto Drira, Khalil Da Silveira, Marcos Pruski, Cédric affil: Luxembourg Institute of Science and Technology, 5, Avenue des Hauts-Fourneaux L-4362 Esch/Alzette Luxembourg sug: subj: Data Analytics Wearable Sensors Medical Care Monitoring, Physiologic Semantics Program Evaluation Program Implementation Computer Systems Ontologies Diabetes Mellitus Therapy Blood Glucose Monitoring ab: Advances supported by emerging wearable technologies in healthcare promise patients a provision of high quality of care. Wearable computing systems represent one of the most thrust areas used to transform traditional healthcare systems into active systems able to continuously monitor and control the patients' health in order to manage their care at an early stage. However, their proliferation creates challenges related to data management and integration. The diversity and variety of wearable data related to healthcare, their huge volume and their distribution make data processing and analytics more difficult. In this paper, we propose a generic semantic big data architecture based on the 'Knowledge as a Service' approach to cope with heterogeneity and scalability challenges. Our main contribution focuses on enriching the NIST Big Data model with semantics in order to smartly understand the collected data, and generate more accurate and valuable information by correlating scattered medical data stemming from multiple wearable devices or/and from other distributed data sources. We have implemented and evaluated a Wearable KaaS platform to smartly manage heterogeneous data coming from wearable devices in order to assist the physicians in supervising the patient health evolution and keep the patient up-to-date about his/her status. pubtype: Academic Journal doctype: pictorial tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|