Abstract
A feature of time-series variability that may reveal underlying complex dynamics is the degree of 'convolutedness'. For multivariate series of m components, convolutedness can be defined as the propensity of the trail of the time-series samples to fill the m-dimensional space. This work proposes different convolutedness indices and compare them on synthesized and real physiological signals. The indices are based on length L and planar extension d of the trail in m dimensions. The classical ones are: the L/d ratio, and the Mandelbrot's fractal dimension (FD) of a curve: FDM =log(L)/log(d). In this work we also consider a correction of the Katz's estimator of FDM, i.e., FDKC =log(N)/(log(N)+log(d/L)), with N the number of samples; and FDMC, an estimator of FDM based on FDKC calculated over a shorter running window Nw
Original language | English |
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Title of host publication | 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 6024-6027 |
Number of pages | 4 |
ISBN (Print) | 9781424479290 |
DOIs | |
Publication status | Published - Nov 2 2014 |
Event | 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 - Chicago, United States Duration: Aug 26 2014 → Aug 30 2014 |
Other
Other | 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 |
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Country/Territory | United States |
City | Chicago |
Period | 8/26/14 → 8/30/14 |
ASJC Scopus subject areas
- Health Informatics
- Computer Science Applications
- Biomedical Engineering