Project Profile

The main results achieved so far consist of the research and implementation of a model based on advanced methods of artificial intelligence for the evaluation of the risk of falls and cardiovascular incidents in cardiology patients. The method is based on analysis of the heart beat obtained by electrocardiographic recording during long term monitoring, but with a total change of prospective with regard to the methods conventionally adopted in the clinic: it proposes indeed to make use of the mechanism which underlies "Heart Rate Variability". Heart rate variability, or rather the study of how cardiac frequency varies, has been shown as a "reliable measurer" of nervous system control (specifically the autonomic nervous system) on cardiac activity. For this reason, it is capable of giving us precious information on the health status of the individual and on his/her capacity to react to external events, which can be used to carry out evaluations by automatic systems.

In the field of the SHARE project, by adapting an artificial intelligence algorithm recently proposed in the scientific literature, an automatic system has been created capable of predicting cardiovascular incidents, identifying a subgroup of patients with a risk five times greater of developing, in the next twelve months, myocardial infarction, ictus and other cardiovascular incidents.

Furthermore, a model has been developed which allows the identification offallers, also from recordings of the electrocardiographic signal and heart rate variability analysis.

In the next few months, the project will arrange to create a different model which allows the identification of ophthalmology patients (with vision difficulties) at higher risk of falling, from clinical data and self-evaluation of the subjects. In this case too, the project is confident of creating a method which allows the identification of a subgroup of subjects with at least twice the risk of falling.

Finally, appropriate web and Android smartphone applications will be developed with the aim of making the proposed models usable both to specialists in the sector and to citizens who intend to use the results of such models.

Project presentations

• Go to project presentation  - Smart Health and Artificial intelligence for Risk Estimation - Social Innovation Day - 15 Aprile 2014
  
  
• Go to project presentation - Heart Rate Variability for automatic assessment of Congestive Heart Failure severity - Medicon 2013 Seville/Spain 25 - 28 September 2013
  
  
  
• Go to project presentation - Health Technology Assessment of home monitoring for patients suffering from heart failure Medicon 2013 Seville/Spain 25 - 28 September 2013
  
  
  

Scientific publications

• Heart rate variability and target organ damage in hypertensive patients
• BMC Cardiovascolar Disorder 2012
• Classification Tree for Risk Assessment in Patients Suffering From Congestive Heart Failure via Long-Term Heart Rate Variability
• IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS 2013