Automatic Prediction of Falls via Heart Rate Variability and Data Mining in Hypertensive Patients: The SHARE Project Experience (CROSBI ID 614189)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Melillo, Paolo ; Jović, Alan ; De Luca, Nicola ; Morgan, Stephen P ; Pecchia, Leandro
engleski
Automatic Prediction of Falls via Heart Rate Variability and Data Mining in Hypertensive Patients: The SHARE Project Experience
Accidental falls in elderly is a major problem. This paper presents the preliminary results of a retrospective study investigating association between Heart Rate Variability (HRV) measures and risk of falling, analyzing 168 clinical 24- hour ECG recording from hypertensive patients, 47 of them experienced at least one fall in the three months before/after the registration. Several HRV patterns, based on 68 linear and non-linear HRV measures, were analyzed in relation to falls using advanced statistical and data mining methods. The results demonstrated that there is a significant association between a depressed HRV and the risk of falling, suggesting that a depressed HRV could be a new independent risk factor for falls with an odds ratio of 5.12 (CI 95% 1.42-18.41 ; p<0.01).
heart rate variability (HRV); accidental falls; fall risk factors; falls prediction; data mining.
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Podaci o prilogu
42-45.
2014.
objavljeno
Podaci o matičnoj publikaciji
IFMBE Proceedings Volume 45
Lacković, Igor ; Vasić, Darko
International Federation of Medical and Biological Engineering (IFMBE)
978-3-319-11127-8
Podaci o skupu
6th European Conference of the International Federation for Medical and Biological Engineering
predavanje
07.09.2014-11.09.2014
Dubrovnik, Hrvatska