title: Analysis of daily oxygen saturation for detecting deterioration in the condition of COPD patients.
abstract: This study presents a novel threshold algorithm that is applied to daily self-measured SpO(2) data for management of COPD patients in remote patient monitoring to improve accuracy of detection of exacerbation. Conventional approaches based on a fixed threshold applied to a single SpO(2) reading result in high false alarm rates. We model the SpO(2) time series data as a combination of a trend and a stochastic component (residual) and use the standard deviation of residuals to identify exacerbations. Deterioration in the condition of a patient results in an increase in the standard deviation of the residual (σ(res)), from 2% or less when the patient is in a healthy condition to 4% or more when the condition deteriorates. We present results from retrospective analysis of SpO(2) data measured in patients with COPD as part of a long term project to monitor frail elderly, and compare results from the new approach with those from the conventional approach.
authors.forename: Hulya
authors.initials: H
authors.lastname: Gokalp
authors.forename: Malcolm
authors.initials: M
authors.lastname: Clarke
mesh_terms: D000368:Aged; D000465:Algorithms; D018450:Disease Progression; D006801:Humans; D010100:Oxygen / Q000378:metabolism*; D029424:Pulmonary Disease, Chronic Obstructive / Q000175:diagnosis* / Q000473:pathology*; D013997:Time Factors
chemical_list: D010100:Oxygen