Abstract
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).
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© 2015 Springer International Publishing Switzerland
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Melillo, P., Jovic, A., De Luca, N., Morgan, S.P., Pecchia, L. (2015). Automatic Prediction of Falls via Heart Rate Variability and Data Mining in Hypertensive Patients: The SHARE Project Experience. In: Lacković, I., Vasic, D. (eds) 6th European Conference of the International Federation for Medical and Biological Engineering. IFMBE Proceedings, vol 45. Springer, Cham. https://doi.org/10.1007/978-3-319-11128-5_11
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DOI: https://doi.org/10.1007/978-3-319-11128-5_11
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11127-8
Online ISBN: 978-3-319-11128-5
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