Andrés Eduardo Castro-Ospina

TL;DR: An approach for modeling cardiac pulses from electrocardiographic signals (ECG) using a modified van der Pol oscillator model (mvP) which, under a proper configuration, is capable of describing action potentials, and can be adapted for modeling a normal cardiac pulse.

TL;DR: This work introduces a new graph building strategy based on a compactly supported kernel technique that makes relevant pair-wise sample relationships by finding a sparse kernel matrix that codes the main sample connections.

TL;DR: This work proposes an algorithm for fingertip segmentation in thermal images of the hand by using a supervised index, and the results are compared against segmentations provided by humans.

TL;DR: The main objective of this paper is the analysis of the Improved Complementary Ensemble Empirical Mode Decomposition (ICEEMD) for feature extraction from physiological signals for emotions prediction and demonstrated the capability of ICEEMD decomposition for emotions analysis from physiology signals.

TL;DR: According to the cardiac murmur effects analyzed, the performance of the classifiers in cascade shown the best accuracy for human identification from ECG-S, minimizing the impact of variability generated on ECG -S by cardiac murmurs diseases.