Classification of motor stereotypies in video

Joshua Fasching, Nicholas Walczak, Vassilios Morellas, Nikolaos Papanikolopoulos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations


Determining and detecting risk markers for mental illness remains a labor intensive process, requiring vast amounts of observations by clinical professionals. Motor stereotypies, which are defined as involuntary repetitive motor behaviors, invariant in form, that, to an observer, appear to serve no purpose, are a class of risk markers which are very amenable to video analysis. These behaviors are associated with mental illnesses such as Autism, Rett Syndrome, and other developmental disabilities. This paper investigates the application of innovative automated methods to recognize these subtle motor indicators. To train and test our methods, a dataset of actions resembling motor stereotypies was created by engaging the normally developing children at the University of Minnesota's Shirley G. Moore Laboratory School. Comparison to a publicly available dataset depicting a subset of behaviors is performed as well. This work demonstrates the applicability of various techniques in the behavioral science domain. The results show that these techniques can perform well on a difficult and challenging real-world scenario.

Original languageEnglish (US)
Title of host publicationIROS Hamburg 2015 - Conference Digest
Subtitle of host publicationIEEE/RSJ International Conference on Intelligent Robots and Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages7
ISBN (Electronic)9781479999941
StatePublished - Dec 11 2015
EventIEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2015 - Hamburg, Germany
Duration: Sep 28 2015Oct 2 2015

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866


OtherIEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2015

Bibliographical note

Publisher Copyright:
© 2015 IEEE.


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