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Publications

Publications by Teresa Sarmento Henriques

2013

Information-based measure of disagreement for more than two observers: a useful tool to compare the degree of observer disagreement

Authors
Henriques, T; Antunes, L; Bernardes, J; Matias, M; Sato, D; Costa Santos, C;

Publication
BMC MEDICAL RESEARCH METHODOLOGY

Abstract
Background: Assessment of disagreement among multiple measurements for the same subject by different observers remains an important problem in medicine. Several measures have been applied to assess observer agreement. However, problems arise when comparing the degree of observer agreement among different methods, populations or circumstances. Methods: The recently introduced information-based measure of disagreement (IBMD) is a useful tool for comparing the degree of observer disagreement. Since the proposed IBMD assesses disagreement between two observers only, we generalized this measure to include more than two observers. Results: Two examples (one with real data and the other with hypothetical data) were employed to illustrate the utility of the proposed measure in comparing the degree of disagreement. Conclusion: The IBMD allows comparison of the disagreement in non-negative ratio scales across different populations and the generalization presents a solution to evaluate data with different number of observers for different cases, an important issue in real situations. A website for online calculation of IBMD and respective 95% confidence interval was additionally developed. The website is widely available to mathematicians, epidemiologists and physicians to facilitate easy application of this statistical strategy to their own data.

2015

Use of multiscale entropy to facilitate artifact detection in electroencephalographic signals

Authors
Mariani, S; Borges, AFT; Henriques, T; Goldberger, AL; Costa, MD;

Publication
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

Abstract
Electroencephalographic (EEG) signals present a myriad of challenges to analysis, beginning with the detection of artifacts. Prior approaches to noise detection have utilized multiple techniques, including visual methods, independent component analysis and wavelets. However, no single method is broadly accepted, inviting alternative ways to address this problem. Here, we introduce a novel approach based on a statistical physics method, multiscale entropy (MSE) analysis, which quantifies the complexity of a signal. We postulate that noise corrupted EEG signals have lower information content, and, therefore, reduced complexity compared with their noise free counterparts. We test the new method on an open-access database of EEG signals with and without added artifacts due to electrode motion. © 2015 IEEE.

2013

Entropy and compression: two measures of complexity

Authors
Henriques, T; Goncalves, H; Antunes, L; Matias, M; Bernardes, J; Costa Santos, C;

Publication
JOURNAL OF EVALUATION IN CLINICAL PRACTICE

Abstract
Rationale, aims and objectivesTraditional complexity measures are used to capture the amount of structured information present in a certain phenomenon. Several approaches developed to facilitate the characterization of complexity have been described in the related literature. Fetal heart rate (FHR) monitoring has been used and improved during the last decades. The importance of these studies lies on an attempt to predict the fetus outcome, but complexity measures are not yet established in clinical practice. In this study, we have focused on two conceptually different measures: Shannon entropy, a probabilistic approach, and Kolmogorov complexity, an algorithmic approach. The main aim of the current investigation was to show that approximation to Kolmogorov complexity through different compressors, although applied to a lesser extent, may be as useful as Shannon entropy calculated by approximation through different entropies, which has been successfully applied to different scientific areas. MethodsTo illustrate the applicability of both approaches, two entropy measures, approximate and sample entropy, and two compressors, paq8l and bzip2, were considered. These indices were applied to FHR tracings pertaining to a dataset composed of 48 delivered fetuses with umbilical artery blood (UAB) pH in the normal range (pH7.20), 10 delivered mildly acidemic fetuses and 10 moderate-to-severe acidemic fetuses. The complexity indices were computed on the initial and final segments of the last hour of labour, considering 5- and 10-minute segments. ResultsIn our sample set, both entropies and compressors were successfully utilized to distinguish fetuses at risk of hypoxia from healthy ones. Fetuses with lower UAB pH presented significantly lower entropy and compression indices, more markedly in the final segments. ConclusionsThe combination of these conceptually different measures appeared to present an improved approach in the characterization of different pathophysiological states, reinforcing the theory that entropies and compressors measure different complexity features. In view of these findings, we recommend a combination of the two approaches.

2015

Remembrance of time series past: simple chromatic method for visualizing trends in biomedical signals

Authors
Burykin, A; Mariani, S; Henriques, T; Silva, TF; Schnettler, WT; Costa, MD; Goldberger, AL;

Publication
PHYSIOLOGICAL MEASUREMENT

Abstract
Analysis of biomedical time series plays an essential role in clinical management and basic investigation. However, conventional monitors streaming data in real-time show only the most recent values, not referenced to past dynamics. We describe a chromatic approach to bring the 'memory' of the physiologic system's past behavior into the current display window. The method employs the estimated probability density function of a time series segment to colorize subsequent data points. For illustrative purposes, we selected open-access recordings of continuous: (1) fetal heart rate during the pre-partum period, and (2) heart rate and systemic blood pressure from a critical care patient during a spontaneous breathing trial. The colorized outputs highlight changes from the 'baseline' reference state, the latter defined as the mode value assumed by the signal, i.e. the maximum of its probability density function. A colorization method may facilitate the recognition of relevant features of time series, especially shifts in baseline dynamics and other trends (including transient and longer-term deviation from baseline values) which may not be as readily noticed using traditional displays. This method may be applicable in clinical monitoring (real-time or off-line) and in research settings. Prospective studies are needed to assess the utility of this approach.

2014

"Glucose-at-a-glance": New method to visualize the dynamics of continuous glucose monitoring data

Authors
Henriques, T; Munshi, MN; Segal, AR; Costa, MD; Goldberger, AL;

Publication
Journal of Diabetes Science and Technology

Abstract
The standard continuous glucose monitoring (CGM) output provides multiple graphical and numerical summaries. A useful adjunct would be a visualization tool that facilitates immediate assessment of both long- and short-term variability. We developed an algorithm based on the mathematical method of delay maps to display CGM signals in which the glucose value at time ti is plotted against its value at time ti+1. The data points are then color-coded based on their frequency of occurrence (density). Examples of this new visualization tool, along with the accompanying time series, are presented for selected patients with type 2 diabetes and non-diabetic controls over the age of 70 years. The method reveals differences in the structure of the glucose variability between subjects with a similar range of glucose values. We also observe that patients with comparable hemoglobin A1c (HbA1c) values may have very different delay maps, consistent with marked differences in the dynamics of glucose control. These differences are not accounted by the amplitude of the fluctuations. Furthermore, the delay maps allow for rapid recognition of hypo- and hyperglycemic periods over the full duration of monitoring or any subinterval. The glucose-at-a-glance visualization tool, based on colorized delay maps, provides a way to quickly assess the complex data acquired by CGM systems. This method yields dynamical information not contained in single summary statistics, such as HbA1c values, and may also serve as the basis for developing novel metrics of glycemic control. © 2014 Diabetes Technology Society.

2016

Multiscale Poincare plots for visualizing the structure of heartbeat time series

Authors
Henriques, TS; Mariani, S; Burykin, A; Rodrigues, F; Silva, TF; Goldberger, AL;

Publication
BMC MEDICAL INFORMATICS AND DECISION MAKING

Abstract
Background: Poincare delay maps are widely used in the analysis of cardiac interbeat interval (RR) dynamics. To facilitate visualization of the structure of these time series, we introduce multiscale Poincare (MSP) plots. Methods: Starting with the original RR time series, the method employs a coarse-graining procedure to create a family of time series, each of which represents the system's dynamics in a different time scale. Next, the Poincare plots are constructed for the original and the coarse-grained time series. Finally, as an optional adjunct, color can be added to each point to represent its normalized frequency. Results: We illustrate the MSP method on simulated Gaussian white and 1/f noise time series. The MSP plots of 1/f noise time series reveal relative conservation of the phase space area over multiple time scales, while those of white noise show a marked reduction in area. We also show how MSP plots can be used to illustrate the loss of complexity when heartbeat time series from healthy subjects are compared with those from patients with chronic (congestive) heart failure syndrome or with atrial fibrillation. Conclusions: This generalized multiscale approach to Poincare plots may be useful in visualizing other types of time series.

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