Movement stereotypies represent one of the most disruptive classes of stereotypical behaviors occurring in children with an ASD. Engagement in these behaviors can lead to social stigmatization, and can complicate social interaction. Unfortunately, the lack of accurate and timely measures of these behaviors has slowed the development of interventions to reduce or prevent stereotypical motor movements. The current proposal will evaluate the use of wireless accelerometers and pattern recognition software to automatically detect two of the most common, high-frequency stereotypical motor movements (body-rocking and hand-flapping) in children with an ASD in real-time. The system that will be tested uses small, noninvasive wireless and wearable sensors that can be easily suited to individuals with ASD. Significance: Obtaining detailed and accurate information on the occurrence, type of movement frequency, duration, and setting events associated with movement stereotypy is critical to understanding and treating this potentially disruptive behavior. Reliable recording of movement stereotypies will enable researchers to study what functional relations may exist between these behaviors and specific antecedents and consequences. These measures can facilitate efficacy studies of behavioral and pharmacologic interventions intended to decrease the incidence or severity of this behavior.