title: Respiratory rate assessment from photoplethysmographic imaging.
abstract: We present a study investigating the suitability of a respiratory rate estimation algorithm applied to photoplethysmographic imaging on a mobile phone. The algorithm consists of a cascade of previously developed signal processing methods to detect features and extract respiratory induced variations in photoplethysmogram signals to estimate respiratory rate. With custom-built software on an Android phone (Camera Oximeter), contact photoplethysmographic imaging videos were recorded using the integrated camera from 19 healthy adults breathing spontaneously at respiratory rates between 6 and 40 breaths/min. Capnometry was simultaneously recorded to obtain reference respiratory rates. Two hundred and ninety-eight Camera Oximeter recordings were available for analysis. The algorithm detected 22 recordings with poor photoplethysmogram quality and 46 recordings with insufficient respiratory information. Of the 232 remaining recordings, a root mean square error of 5.9 breaths/min and a median absolute error of 2.3 breaths/min was obtained. The study showed that it is feasible to estimate respiratory rates by placing a finger on a mobile phone camera, but that it becomes increasingly challenging at respiratory rates higher than 20 breaths/min.
authors.forename: Walter
authors.initials: W
authors.lastname: Karlen
authors.forename: Ainara
authors.initials: A
authors.lastname: Garde
authors.forename: Dorothy
authors.initials: D
authors.lastname: Myers
authors.forename: Cornie
authors.initials: C
authors.lastname: Scheffer
authors.forename: J Mark
authors.initials: JM
authors.lastname: Ansermino
authors.forename: Guy A
authors.initials: GA
authors.lastname: Dumont
mesh_terms: D000328:Adult; D000465:Algorithms; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional; D008297:Male; D010092:Oximetry / Q000295:instrumentation; D017156:Photoplethysmography / Q000379:methods*; D056152:Respiratory Rate; D013997:Time Factors