title: ε-Tube regression: a new method for motion artifact reduction.
abstract: This paper introduces a new regression method, called ε-tube regression (ε-TR), for motion artifact reduction in physiological signals. It forms a tube arround the data which leads to an approximation that models only the motion artifact and not the target signal. Moreover, ε-TR prescribes the shape of the approximation using the available information about the motion artifact. The results show that ε-TR can effectively remove the motion artifacts from the impedance signal measured on the arms.
authors.affiliation: Department of Computer Science, Virginia Commonwealth University, Richmond, VA, USA. ansaris2@mymail.vcu.edu
authors.forename: Sardar
authors.initials: S
authors.lastname: Ansari
authors.forename: Kevin
authors.initials: K
authors.lastname: Ward
authors.forename: Kayvan
authors.initials: K
authors.lastname: Najarian
mesh_terms: D016477:Artifacts; D012044:Regression Analysis; D060388:Support Vector Machine