Search results for "Multiscale Entropy"
showing 5 items of 5 documents
Characterization of entropy measures against data loss: Application to EEG records
2012
This study is aimed at characterizing three signal entropy measures, Approximate Entropy (ApEn), Sample Entropy (SampEn) and Multiscale Entropy (MSE) over real EEG signals when a number of samples are randomly lost due to, for example, wireless data transmission. The experimental EEG database comprises two main signal groups: control EEGs and epileptic EEGs. Results show that both SampEn and ApEn enable a clear distinction between control and epileptic signals, but SampEn shows a more robust performance over a wide range of sample loss ratios. MSE exhibits a poor behavior for ratios over a 40% of sample loss. The EEG non-stationary and random trends are kept even when a great number of samp…
Multiscale Information Storage of Linear Long-Range Correlated Stochastic Processes
2019
Information storage, reflecting the capability of a dynamical system to keep predictable information during its evolution over time, is a key element of intrinsic distributed computation, useful for the description of the dynamical complexity of several physical and biological processes. Here we introduce a parametric approach which allows one to compute information storage across multiple timescales in stochastic processes displaying both short-term dynamics and long-range correlations (LRC). Our analysis is performed in the popular framework of multiscale entropy, whereby a time series is first "coarse grained" at the chosen timescale through low-pass filtering and downsampling, and then …
P 042 - Gait complexity quantified using inertial measurement units in children with cerebral palsy
2018
Abstract Children with cerebral palsy (CP) have gait impairments, and their gait is affected by concurrent tasks. We used inertial measurement units (IMU) to quantify CP-related gait complexity alterations, and identify effects of dual tasks on gait variability from 12 children with CP and 23 typically developed (TD) controls. The data were collected for normal and dual-tasks (motor; carrying a tray, cognitive; word naming) during walking. Step duration and adjusted multiscale entropy (MSE) index were computed. In overall, children with CP had shorter step duration and greater gait complexity than TD. Gait complexity was higher in vertical direction during the cognitive than normal and moto…
Vector Autoregressive Fractionally Integrated Models to Assess Multiscale Complexity in Cardiovascular and Respiratory Time Series
2020
Cardiovascular variability is the result of the activity of several physiological control mechanisms, which involve different variables and operate across multiple time scales encompassing short term dynamics and long range correlations. This study presents a new approach to assess the multiscale complexity of multivariate time series, based on linear parametric models incorporating autoregressive coefficients and fractional integration. The approach extends to the multivariate case recent works introducing a linear parametric representation of multiscale entropy, and is exploited to assess the complexity of cardiovascular and respiratory time series in healthy subjects studied during postu…
Multiscale Information Decomposition: Exact Computation for Multivariate Gaussian Processes
2017
Exploiting the theory of state space models, we derive the exact expressions of the information transfer, as well as redundant and synergistic transfer, for coupled Gaussian processes observed at multiple temporal scales. All of the terms, constituting the frameworks known as interaction information decomposition and partial information decomposition, can thus be analytically obtained for different time scales from the parameters of the VAR model that fits the processes. We report the application of the proposed methodology firstly to benchmark Gaussian systems, showing that this class of systems may generate patterns of information decomposition characterized by prevalently redundant or sy…