|Technological Innovations in Data Collection|
|Monday, May 26, 2014|
|9:00 AM–9:50 AM |
|W183a (McCormick Place Convention Center)|
|Chair: Andre Maharaj (Florida International University)|
Utilizing an Automated Motion Sensor System to Record and Analyze Modeled Replications of Stereotypy
|ANDRE MAHARAJ (Florida International University), Anibal Gutierrez Jr. (Florida International University), Steven Cadavid (Cadavid Concepts)|
Repetitive or stereotypic physical behaviors are frequently detected in children with Autism Spectrum Disorder (ASD). These behaviors do not appear to be either reactionary or maintained by environmental consequences. While traditional methods of measuring stereotypy have utilized paper and pencil techniques, the Kinect sensor from Microsoft provides an impartial automated system via which these movements may be detected. Software designed to record and export the sensor data was used to analyze the modeled performance of body rocking from side-to-side and front-to-back, as well as hand flapping, with the aim of identifying behavior patterns relevant to children with ASD. A standard configuration of each behavior was selected, with a predetermined threshold value, and a dynamic time warping algorithm was applied to identify relevant patterns. The data obtained indicated that the system correctly identified 90% of side-to-side rocking, 90% of hand flapping and 100% of front-to-back rocking, with a highly restrictive threshold value of 20 degrees along the x, y and z axes, respectively. The results imply a proof of concept, demonstrating the possibility of an accessible automated solution to the monitoring and identification of physical stereotypic behavior.
CANCELLED: Can Mobile Technology Effectively Record Skills and Behavioral Data In A One-On-One and Group Settings?
|Domain: Applied Research|
|BARRY KATZ (Operant Systems, Inc.)|
The recording, reporting and the management of session data of program targets and instances of inappropriate behaviors are the bane of a behavior analyst's existence. On average the behavior analyst manages between 20-25 programs and 2-5 behaviors for each student a day. What method and procedure is best suited to collect skills acquisition and behavior management data both in a one-on-one as well as group setting? The research question will compare a paper based to a mobile solution and determine which is more effective in managing the data collection process involved in planning, observing, recording, analyzing and modifying a student's plan. A multiple baseline design will be used to assess the training procedures outlined by TeachMe Skills. Finally, social validity measures will be taken to compare staff members' satisfaction with each method.