title: Decomposition of Near-Infrared Spectroscopy Signals Using Oblique Subspace Projections: Applications in Brain Hemodynamic Monitoring.
abstract: Clinical data is comprised by a large number of synchronously collected biomedical signals that are measured at different locations. Deciphering the interrelationships of these signals can yield important information about their dependence providing some useful clinical diagnostic data. For instance, by computing the coupling between Near-Infrared Spectroscopy signals (NIRS) and systemic variables the status of the hemodynamic regulation mechanisms can be assessed. In this paper we introduce an algorithm for the decomposition of NIRS signals into additive components. The algorithm, SIgnal DEcomposition base on Obliques Subspace Projections (SIDE-ObSP), assumes that the measured NIRS signal is a linear combination of the systemic measurements, following the linear regression modely=Ax+ϵ. SIDE-ObSP decomposes the output such that, each component in the decomposition represents the sole linear influence of one corresponding regressor variable. This decomposition scheme aims at providing a better understanding of the relation between NIRS and systemic variables, and to provide a framework for the clinical interpretation of regression algorithms, thereby, facilitating their introduction into clinical practice. SIDE-ObSP combines oblique subspace projections (ObSP) with the structure of a mean average system in order to define adequate signal subspaces. To guarantee smoothness in the estimated regression parameters, as observed in normal physiological processes, we impose a Tikhonov regularization using a matrix differential operator. We evaluate the performance of SIDE-ObSP by using a synthetic dataset, and present two case studies in the field of cerebral hemodynamics monitoring using NIRS. In addition, we compare the performance of this method with other system identification techniques. In the first case study data from 20 neonates during the first 3 days of life was used, here SIDE-ObSP decoupled the influence of changes in arterial oxygen saturation from the NIRS measurements, facilitating the use of NIRS as a surrogate measure for cerebral blood flow (CBF). The second case study used data from a 3-years old infant under Extra Corporeal Membrane Oxygenation (ECMO), here SIDE-ObSP decomposed cerebral/peripheral tissue oxygenation, as a sum of the partial contributions from different systemic variables, facilitating the comparison between the effects of each systemic variable on the cerebral/peripheral hemodynamics.
authors.affiliation: Department of Electrical Engineering ESAT, STADIUS Center for Dynamical Systems, Signal Processing, and Data Analytics, KU LeuvenLeuven, Belgium; (iMinds Medical) Department Medical Information TechnologiesLeuven, Belgium.
authors.forename: Alexander
authors.initials: A
authors.lastname: Caicedo
authors.affiliation: Department of Electrical Engineering ESAT, STADIUS Center for Dynamical Systems, Signal Processing, and Data Analytics, KU LeuvenLeuven, Belgium; (iMinds Medical) Department Medical Information TechnologiesLeuven, Belgium.
authors.forename: Carolina
authors.initials: C
authors.lastname: Varon
authors.affiliation: Department of Electrical Engineering ESAT, STADIUS Center for Dynamical Systems, Signal Processing, and Data Analytics, KU LeuvenLeuven, Belgium; (iMinds Medical) Department Medical Information TechnologiesLeuven, Belgium.
authors.forename: Borbala
authors.initials: B
authors.lastname: Hunyadi
authors.affiliation: Biomedical Optics Research Laboratory, Department of Medical Physics and Bioengineering, University College London London, England.
authors.forename: Maria
authors.initials: M
authors.lastname: Papademetriou
authors.affiliation: Biomedical Optics Research Laboratory, Department of Medical Physics and Bioengineering, University College London London, England.
authors.forename: Ilias
authors.initials: I
authors.lastname: Tachtsidis
authors.affiliation: Department of Electrical Engineering ESAT, STADIUS Center for Dynamical Systems, Signal Processing, and Data Analytics, KU LeuvenLeuven, Belgium; (iMinds Medical) Department Medical Information TechnologiesLeuven, Belgium.
authors.forename: Sabine
authors.initials: S
authors.lastname: Van Huffel
keywords: NIRS; Tikhonov regularization; biomedical signal processing; brain hemodynamics; oblique subspace projections