Recognizing Mimicked Autistic Self-Stimulatory Behaviors Using HMMs

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.

• Type: Conference
• Year: 2005
• Where: ISWC
• Authors: Tracy L. Westeyn, Kristin Vadas, Xuehai Bian, Thad Starner, Gregory D. Abowd
• Keywords: Continuous Recognition, Continuous Recognition Rates, ISWC 2005, Stimming Behaviors