Human-Robot Upper Body Gesture Imitation Analysis for Autism Spectrum Disorders

Abstract

In this paper we combine robot control and data analysis techniques into a system aimed at early detection and treatment of autism. A humanoid robot - Zeno is used to perform interactive upper body gestures which the human subject can imitate or initiate. The result of interaction is recorded using a motion capture system, and the similarity of gestures performed by human and robot is measured using the Dynamic Time Warping algorithm. This measurement is proposed as a quantitative similarity measure to objectively analyze the quality of the imitation interaction between the human and the robot. In turn, the clinical hypothesis is that this will serve as a consistent quantitative measurement, and can be used to obtain information about the condition and possible improvement of children with autism spectrum disorders. Experimental results with a small set of child subjects are presented to illustrate our approach. © Springer International Publishing 2013.

Document Type

Conference Presentation

Publication Date

10-27-2013

Publication Title

International Conference on Social Robotics

ISSN

0302-9743

DOI

10.1007/978-3-319-02675-6_22

First Page

218

Last Page

228

Link to Full Text

Share

COinS