LBCSI research projects

Metabolic and inborn factors of reproductive health, birth II
Research program P3-0124 (2014 - 2020); funded by the ARRS, Slovenian research agency; research partner: University Medical Center, Ljubljana, Slovenia.
The goal of the project is to develop a predictive model to assess the risk of preterm delivery. Using signal analysis of electromyogram of uterus during pregnancy, we try to estimate the risk for preterm delivery. Signal analysis include linear time- and frequency-domain techniques and non-linear techniques such as correlation dimension. We also try to separate sets of term and pre-term uterine EMG records by signal spectrum estimation using adaptive autoregressive method. We are developing a framework for dynamic creation of web-interfaces intended for easy setup and use by physicians.
Metabolic and inborn factors of reproductive health, birth II
Research program P3-0124 (2009 - 2014); funded by the ARRS, Slovenian research agency; research partner: University Medical Center, Ljubljana, Slovenia.
The goal of the project is to develop a predictive model to assess the risk of preterm delivery. Using signal analysis of electromyogram of uterus during pregnancy, we try to estimate the risk for preterm delivery. Signal analysis include linear time- and frequency-domain techniques and non-linear techniques such as correlation dimension. We also try to separate sets of term and pre-term uterine EMG records by signal spectrum estimation using adaptive autoregressive method. We are developing a framework for dynamic creation of web-interfaces intended for easy setup and use by physicians.
Metabolic and inborn factors of reproductive health, birth
Research program P3-0124 (2004 - 2009); funded by the Ministry of education, science and sport of the Republic Slovenia; research partner: University Medical Center, Ljubljana, Slovenia.
The goal of the project is to develop a predictive model to assess the risk of preterm delivery. Using signal analysis of electromyogram of uterus during pregnancy, we try to estimate the risk for preterm delivery. Signal analysis include linear time- and frequency-domain techniques and non-linear techniques such as: correlation dimension, computation of information-based similarity index and entropy analysis.
Maintaining, updating and distribution of the Long Term ST Database (LTST DB)
(2002-2007); research partners: Beth Israel Deaconess Medical Center, Boston, USA, and CNR Institute of Clinical Physiology, Pisa, Italy.
In the scope of the project of maintaining, updating and distribution of the Long Term ST Database (LTST DB) are planned these activities:
  • validating and correction of data files of existing records
  • adding new features to the database
  • adding new records to the database
  • distribution of physical media (CDs, DVDs) to the interested users.
Development of Long Term ST Database (LTST DB)

Project funded by the Medtronic, Inc., Mineapolis, USA, (1997-2002), and by the Zymed, Inc., Camarrilo, USA (1999-2002); research partners: Massachusetts Institute of Technology, Cambridge, USA, Beth Israel Deaconess Medical Center, Boston, USA, CNR Institute of Clinical Physiology, Pisa, Italy, University Medical Center, Ljubljana, Slovenia, and Department of Systems & Informatics, Firenze, Italy.

Automated detection of Transient ST-Segment Changes During Ambulatory ECG-Monitoring

U.S.-Slovenian Joint Project, Project #95-158 (1995-98); funded by the National Institutes of Health, USA, and the Slovenian Ministry of Science and Technology; research partner: Biomedical Engineering Center, Massachusetts Institute of Technology, Cambridge, USA.