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Recherche transversale
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2016-02-08 - Colloque/Article dans les actes avec comité de lecture - Anglais - 3 page(s)

Aileni Raluca Maria, Strungaru Rodica, Valderrama Carlos , "Data mining for autonomous wearable sensors used for elderly healthcare monitoring" in NESUS Symposium on Sustainable Ultrascale Computing Systems , 1, 37_39, Timisoara, Romania, 2016

  • Codes CREF : Sciences de l'ingénieur (DI2000), Techniques d'imagerie et traitement d'images (DI2770), Technologies de l'information et de la communication (TIC) (DI4730), Semi-conducteurs (DI2512), Electronique et électrotechnique (DI2411), Instrumentation médicale (DI2760), Conception assistée par ordinateur (DI1247), Electronique générale (DI2510), Electricité (DI1230)
  • Unités de recherche UMONS : Electronique et Microélectronique (F109)
  • Instituts UMONS : Institut de Recherche en Technologies de l’Information et Sciences de l’Informatique (InforTech), Institut NUMEDIART pour les Technologies des Arts Numériques (Numédiart)
  • Centres UMONS : Centre de Recherche en Technologie de l’Information (CRTI)

Abstract(s) :

(Anglais) The paper presents some aspects regarding data mining used modeling and prediction of the patients’ health state parameters. The proposed wearable device integrated by using wireless personal networks (WPNs) can sense, process and communicate vital signs through internet for healthcare monitoring. These WPNs are fitted for medical applications and offer continuous ambulatory health monitoring by using non-invasive methods. Generally, the body sensor network (BSN) for medical applications are based on big data fusion and cloud computing technologies (PaaS, SaaS - for data storage and sharing solutions). The big data fusion includes preprocessing (filter the noise), feature extraction (data abstraction), data fusion computation (modeling different information type and fusion), and data compression (reducing the information stored in memory and transmitted by the transceiver). The fusion between wearable wireless body sensor network (WWBSN), IoT and Cloud Computing will allow doctors, emergency stations or caregivers to track and receive data from BSNs about patients in different places. By using biomedical sensors can be studied the human behavior and physiology, the body's response physiologically and emotionally to various physical and mental diseases. The WWBSN can cover monitoring for cardiovascular, diabetic problems or mental disorders (Alzheimer).

Identifiants :
  • ISBN : 978-84-608-6309-0

Mots-clés :
  • (Anglais) data mining
  • (Anglais) elderly healthcare