title: Detection and Classification of Measurement Errors in Bioimpedance Spectroscopy.
abstract: Bioimpedance spectroscopy (BIS) measurement errors may be caused by parasitic stray capacitance, impedance mismatch, cross-talking or their very likely combination. An accurate detection and identification is of extreme importance for further analysis because in some cases and for some applications, certain measurement artifacts can be corrected, minimized or even avoided. In this paper we present a robust method to detect the presence of measurement artifacts and identify what kind of measurement error is present in BIS measurements. The method is based on supervised machine learning and uses a novel set of generalist features for measurement characterization in different immittance planes. Experimental validation has been carried out using a database of complex spectra BIS measurements obtained from different BIS applications and containing six different types of errors, as well as error-free measurements. The method obtained a low classification error (0.33%) and has shown good generalization. Since both the features and the classification schema are relatively simple, the implementation of this pre-processing task in the current hardware of bioimpedance spectrometers is possible.
authors.affiliation: R&D Department, Fonetic, 28037 Madrid, Spain.|Signal Theory and Communications Department, University of Alcala, Alcalá de Henares, Spain.
authors.forename: David
authors.identifier: http://orcid.org/0000-0001-7473-5083
authors.initials: D
authors.lastname: Ayllón
authors.affiliation: Signal Theory and Communications Department, University of Alcala, Alcalá de Henares, Spain.
authors.forename: Roberto
authors.initials: R
authors.lastname: Gil-Pita
authors.affiliation: Faculty of Care Science, Work Life and Social Welfare, University of Boras, Boras, Sweden.|School of Technology and Health, Royal Institute of Technology, Huddinge, Sweden.
authors.forename: Fernando
authors.initials: F
authors.lastname: Seoane
mesh_terms: D000465:Algorithms; D016477:Artifacts; D001823:Body Composition; D058266:Dielectric Spectroscopy / Q000379:methods; D025802:Electric Capacitance; D017097:Electric Impedance; D006801:Humans