Identifying chronic disease complications utilizing state of the art data fusion methodologies and signal processing algorithms

John Gialelis, Petros Chondros, Dimitrios Karadimas, Sofia Dima, Dimitrios Serpanos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

In this paper a methodology for identifying patient's chronic disease complications is proposed. This methodology consists of two steps: a. application of wavelet algorithms on ECG signal in order to extract specific features and b. fusion of the extracted information from the ECG signal with information from other sensors (i.e., body temperature, environment temperature, sweating index, etc.) in order to assess the health state of a monitoring patient. Therefore, the objective of this methodology is to derive semantically enriched information by discovering abnormalities at one hand detect associations and inter-dependencies among the signals at the other hand and finally highlight patterns and provide configuration rulesets for an intelligent local rule engine. The added value of the semantic enrichment process refers to the discovery of specific features and meaningful information with respect to the personalized needs of each patient.

Original languageEnglish
Title of host publicationWireless Mobile Communication and Healthcare - Second International ICST Conference, MobiHealth 2011, Revised Selected Papers
Pages256-263
Number of pages8
DOIs
Publication statusPublished - 31 Jul 2012
Event2nd International ICST Conference on Wireless Mobile Communication and Healthcare, MobiHealth 2011 - Kos Island, Greece
Duration: 5 Oct 20117 Oct 2011

Publication series

NameLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering
Volume83 LNICST
ISSN (Print)1867-8211

Other

Other2nd International ICST Conference on Wireless Mobile Communication and Healthcare, MobiHealth 2011
CountryGreece
CityKos Island
Period5/10/117/10/11

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Keywords

  • algorithms
  • data fusion
  • patient monitoring

ASJC Scopus subject areas

  • Computer Networks and Communications

Cite this

Gialelis, J., Chondros, P., Karadimas, D., Dima, S., & Serpanos, D. (2012). Identifying chronic disease complications utilizing state of the art data fusion methodologies and signal processing algorithms. In Wireless Mobile Communication and Healthcare - Second International ICST Conference, MobiHealth 2011, Revised Selected Papers (pp. 256-263). (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering; Vol. 83 LNICST). https://doi.org/10.1007/978-3-642-29734-2_35