Observatorio de I+D+i UPM

Memorias de investigación
ECG time series data mining for cardiovascular disease risk assessment
Research Areas
  • Information technology and adata processing
Chronic diseases require ongoing care to improve patients? quality of life. It demands large amount of investment from governments and companies including employee absenteeism, early retirement and social spend. Nowadays it is estimated that 12% of natural death occurs suddenly, in which 88% of them is related to cardiac origin. Indeed, cardiovascular diseases are the first cause of mortality in Spain with more than 123,000 cases and investments estimated in ?2 billon annually, representing 0.2% of gross domestic product (GDP). On one hand, the proportional incidence (per 1,000 habitants) of acute myocardial infarction is stable on population between 25 and 74 years. On the other hand, it is estimated increasing by 1.5% the number of heart attack because of the population aging. However, chronic cardiac disease can be fully or partially prevented. This work introduces time series data mining models for analyzing electrocardiograms (ECG) in order to identify heart attack pre-events and the probability of incidence. This information could support patients in searching proper treatment minutes before
Mark Rating
  • Director: Aurora Perez Perez (UPM)
  • Director: Juan Pedro Caraca-Valente Hernandez (UPM)
  • Autor: Allan de Brito Méndez Calderón
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Investigación en Tecnología Informática y de las Comunicaciones: CETTICO
S2i 2020 Observatorio de investigación @ UPM con la colaboración del Consejo Social UPM
Cofinanciación del MINECO en el marco del Programa INNCIDE 2011 (OTR-2011-0236)
Cofinanciación del MINECO en el marco del Programa INNPACTO (IPT-020000-2010-22)