title: Empirical mode decomposition applied to tissue artifact removal from respiratory signal.
abstract: Estimation of respiration commonly employs piezoelectric sensors secured to rib cage and abdominal belts. However, these respiratory signals are often contaminated by tissue artifact. This paper presents a signal decomposition technique for tissue artifact removal in respiratory signals, based on empirical mode decomposition (EMD). After introducing the theoretical foundation, this method is performed on three synthetic signals, and performance of tissue artifact removal using EMD is compared with low-pass filter and independent component analysis (ICA) techniques. A simulation study and experimental results show that EMD can effectively remove tissue artifact in respiratory signals.
authors.affiliation: Electromechanical Systems Laboratory, University of Massachusetts-Amherst, MA 01003, USA.
authors.forename: Shaopeng
authors.initials: S
authors.lastname: Liu
authors.forename: Qingbo
authors.initials: Q
authors.lastname: He
authors.forename: Robert X
authors.initials: RX
authors.lastname: Gao
authors.forename: Patty
authors.initials: P
authors.lastname: Freedson
mesh_terms: D000328:Adult; D000465:Algorithms; D016477:Artifacts; D003198:Computer Simulation; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D008297:Male; D015233:Models, Statistical; D011659:Pulmonary Gas Exchange; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*; D012984:Software; D013382:Subtraction Technique; D013997:Time Factors