title: Linear regression models and k-means clustering for statistical analysis of fNIRS data.
abstract: We propose a new algorithm, based on a linear regression model, to statistically estimate the hemodynamic activations in fNIRS data sets. The main concern guiding the algorithm development was the minimization of assumptions and approximations made on the data set for the application of statistical tests. Further, we propose a K-means method to cluster fNIRS data (i.e. channels) as activated or not activated. The methods were validated both on simulated and in vivo fNIRS data. A time domain (TD) fNIRS technique was preferred because of its high performances in discriminating cortical activation and superficial physiological changes. However, the proposed method is also applicable to continuous wave or frequency domain fNIRS data sets.
authors.affiliation: MOX - Department of Mathematics, Politecnico di Milano, Milan, Italy ; first two authors contributed equally to this work.
authors.forename: Viola
authors.initials: V
authors.lastname: Bonomini
authors.affiliation: Dipartimento di Fisica, Politecnico di Milano, Milan, Italy ; first two authors contributed equally to this work.
authors.forename: Lucia
authors.initials: L
authors.lastname: Zucchelli
authors.affiliation: Dipartimento di Fisica, Politecnico di Milano, Milan, Italy.
authors.forename: Rebecca
authors.initials: R
authors.lastname: Re
authors.affiliation: Department of Mathematics "Federigo Enriques", Università degli Studi di Milano, Milan, Italy.
authors.forename: Francesca
authors.initials: F
authors.lastname: Ieva
authors.affiliation: Istituto di Fotonica e Nanotecnologie, CNR,Milan, Italy.
authors.forename: Lorenzo
authors.initials: L
authors.lastname: Spinelli
authors.affiliation: Dipartimento di Fisica, Politecnico di Milano, Milan, Italy.
authors.forename: Davide
authors.initials: D
authors.lastname: Contini
authors.affiliation: MOX - Department of Mathematics, Politecnico di Milano, Milan, Italy.
authors.forename: Anna
authors.initials: A
authors.lastname: Paganoni
authors.affiliation: Dipartimento di Fisica, Politecnico di Milano, Milan, Italy.
authors.forename: Alessandro
authors.initials: A
authors.lastname: Torricelli
keywords: (000.5490) Probability theory, stochastic processes, and statistics; (170.1470) Blood or tissue constituent monitoring; (170.2655) Functional monitoring and imaging; (170.6920) Time-resolved imaging