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11	Assessment of blind source separation techniques for video-based cardiac pulse extraction Wedekind, Daniel, Trumpp, Alexander, Gaetjen, Frederik, Rasche, Stefan, Matschke, Klaus, Malberg, Hagen, Zaunseder, Sebastian 09 September 2019 (has links) Blind source separation (BSS) aims at separating useful signal content from distortions. In the contactless acquisition of vital signs by means of the camera-based photoplethysmogram (cbPPG), BSS has evolved the most widely used approach to extract the cardiac pulse. Despite its frequent application, there is no consensus about the optimal usage of BSS and its general benefit. This contribution investigates the performance of BSS to enhance the cardiac pulse from cbPPGs in dependency to varying input data characteristics. The BSS input conditions are controlled by an automated spatial preselection routine of regions of interest. Input data of different characteristics (wavelength, dominant frequency, and signal quality) from 18 postoperative cardiovascular patients are processed with standard BSS techniques, namely principal component analysis (PCA) and independent component analysis (ICA). The effect of BSS is assessed by the spectral signal-tonoise ratio (SNR) of the cardiac pulse. The preselection of cbPPGs, appears beneficial providing higher SNR compared to standard cbPPGs. Both, PCA and ICA yielded better outcomes by using monochrome inputs (green wavelength) instead of inputs of different wavelengths. PCA outperforms ICA for more homogeneous input signals. Moreover, for high input SNR, the application of ICA using standard contrast is likely to decrease the SNR. info:eu-repo/classification/ddc/530 ddc:530 info:eu-repo/classification/ddc/610 ddc:610
12	Improving Deep Representations by Incorporating Domain Knowledge and Modularization for Synthetic Aperture Radar and Physiological Data Agarwal, Tushar January 2022 (has links) No description available. Scientific Imaging Statistics Health Care Electrical Engineering Computer Engineering Computer Science Biomedical Engineering Remote Sensing Artificial Intelligence Machine Learning Deep Learning Data Augmentation Automatic Target Recognition Deep Generative Modeling Compressed sensing Super-Resolution Inverse-Problems Synthetic Aperture Radar Electrocardiogram Photoplethysmogram mHealth

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Assessment of blind source separation techniques for video-based cardiac pulse extraction

Improving Deep Representations by Incorporating Domain Knowledge and Modularization for Synthetic Aperture Radar and Physiological Data