title: GNL-HybELS: an algorithm to classify and identify VOR responses simultaneously.
abstract: The Vestibulo-Ocular Reflex (VOR) stabilizes the images of the world on the retinae when the head is in motion. Basic daily activities such as walking or driving depend on the proper functioning of this reflex. For several decades, scientists have developed methods to model and identify this system mathematically. However, traditional methods cannot analyze VOR data comprehensively because they disregard pieces of data (fast phases) which biases estimated reflex dynamics. Here we propose, for the first time, an automated tool to analyze entire VOR responses (slow and fast phases), without apriori classification of nystagmus segments.
authors.affiliation: Biomedical Engineering department of McGill, University Montreal, Quebec H3A2B4 Canada. atiueh.ghoreyshi@mail.mcgill.ca
authors.forename: Atiyeh
authors.initials: A
authors.lastname: Ghoreyshi
authors.forename: Henrietta L
authors.initials: HL
authors.lastname: Galiana
mesh_terms: D000465:Algorithms; D001331:Automation; D001698:Biomedical Engineering / Q000379:methods; D003198:Computer Simulation; D004867:Equipment Design; D006801:Humans; D016018:Least-Squares Analysis; D015233:Models, Statistical; D008962:Models, Theoretical; D009474:Neurons / Q000378:metabolism; D009759:Nystagmus, Pathologic / Q000473:pathology; D025341:Principal Component Analysis; D012018:Reflex / Q000502:physiology; D012027:Reflex, Vestibulo-Ocular / Q000502:physiology*; D015203:Reproducibility of Results