title: Automated Detection of Stereotypical Motor Movements in Autism Spectrum Disorder Using Recurrence Quantification Analysis.
abstract: A number of recent studies using accelerometer features as input to machine learning classifiers show promising results for automatically detecting stereotypical motor movements (SMM) in individuals with Autism Spectrum Disorder (ASD). However, replicating these results across different types of accelerometers and their position on the body still remains a challenge. We introduce a new set of features in this domain based on recurrence plot and quantification analyses that are orientation invariant and able to capture non-linear dynamics of SMM. Applying these features to an existing published data set containing acceleration data, we achieve up to 9% average increase in accuracy compared to current state-of-the-art published results. Furthermore, we provide evidence that a single torso sensor can automatically detect multiple types of SMM in ASD, and that our approach allows recognition of SMM with high accuracy in individuals when using a person-independent classifier.
authors.affiliation: Holst Centre, IMEC Eindhoven, Netherlands.
authors.forename: Ulf
authors.initials: U
authors.lastname: Großekathöfer
authors.affiliation: Janssen Research & Development Beerse, Belgium.
authors.forename: Nikolay V
authors.initials: NV
authors.lastname: Manyakov
authors.affiliation: Holst Centre, IMEC Eindhoven, Netherlands.
authors.forename: Vojkan
authors.initials: V
authors.lastname: Mihajlović
authors.affiliation: Janssen Research & Development Titusville, NJ, USA.
authors.forename: Gahan
authors.initials: G
authors.lastname: Pandina
authors.affiliation: Janssen Research & Development Spring House, PA, USA.
authors.forename: Andrew
authors.initials: A
authors.lastname: Skalkin
authors.affiliation: Janssen Research & Development Titusville, NJ, USA.
authors.forename: Seth
authors.initials: S
authors.lastname: Ness
authors.affiliation: Janssen Research & Development Titusville, NJ, USA.
authors.forename: Abigail
authors.initials: A
authors.lastname: Bangerter
authors.affiliation: Department of Health Sciences, Northeastern University Boston, MA, USA.
authors.forename: Matthew S
authors.initials: MS
authors.lastname: Goodwin
keywords: ASD; autism; recurrence analysis; recurrence plots; repetitive behavior; stereotypical motor movement