title: Electronic recognition of hand hygiene technique and duration.
abstract: We captured 3-dimensional accelerometry data from the wrists of 116 healthcare professionals as they performed hand hygiene (HH). We then used these data to train a k-nearest-neighbors classifier to recognize specific aspects of HH technique (ie, fingertip scrub) and measure the duration of HH events.
authors.affiliation: Department of Computer Science, University of Iowa, Iowa City, Iowa.
authors.forename: Valerie
authors.initials: V
authors.lastname: Galluzzi
authors.forename: Ted
authors.initials: T
authors.lastname: Herman
authors.forename: D J
authors.initials: DJ
authors.lastname: Shumaker
authors.forename: D R
authors.initials: DR
authors.lastname: Macinga
authors.forename: J W
authors.initials: JW
authors.lastname: Arbogast
authors.forename: Elena M
authors.initials: EM
authors.lastname: Segre
authors.forename: Alberto M
authors.initials: AM
authors.lastname: Segre
authors.forename: Philip M
authors.initials: PM
authors.lastname: Polgreen
mesh_terms: D061725:Accelerometry / Q000295:instrumentation / Q000379:methods; D063373:Hand Hygiene / Q000379:methods / Q000706:statistics & numerical data; D006801:Humans; D015203:Reproducibility of Results; D013997:Time Factors; D014953:Wrist