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Osaka, Japan
Oct. 18, 2005 to Oct. 21, 2005
ISBN: 0-7695-2419-2
pp: 164-169
Kristin Vadas , College of Computing and GVU Center; Georgia Institute of Technology Atlanta, GA 30332-0280 USA
Xuehai Bian , College of Computing and GVU Center; Georgia Institute of Technology Atlanta, GA 30332-0280 USA
Thad Starner , College of Computing and GVU Center; Georgia Institute of Technology Atlanta, GA 30332-0280 USA
Gregory D. Abowd , College of Computing and GVU Center; Georgia Institute of Technology Atlanta, GA 30332-0280 USA
ABSTRACT
<p>Children with autism often exhibit self-stimulatory (or "stimming") behaviors. We present an on-body sensing system for continuous recognition of stimming activity. By creating a system to recognize and monitor stimming behaviors, we hope to provide autism researchers with detailed, quantitative data. In this paper, we compare isolated and continuous recognition rates of emulated autistic stimming behaviors using hidden Markov models (HMMs). We achieved an overall system accuracy 68.57% in continuous recognition tests. However, the occurrence of stimming events can be detected with 100% accuracy by allowing minor frame-level insertion errors.</p>
INDEX TERMS
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CITATION
Kristin Vadas, Xuehai Bian, Thad Starner, Gregory D. Abowd, "Recognizing Mimicked Autistic Self-Stimulatory Behaviors Using HMMs", ISWC, 2005, 2012 16th International Symposium on Wearable Computers, 2012 16th International Symposium on Wearable Computers 2005, pp. 164-169, doi:10.1109/ISWC.2005.45
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