Capture, Quantify and Analyze Therapy Interactions

Abstract

Researchers at the University of Central Florida have designed a system that mental health professionals can use to capture and track quantifiable data about a child's development and behavior during therapy sessions. The Science of Play system works in real time, monitoring and measuring the play activity of a child and identifying patterns that may signal behavioral and mental disorders as well as developmental milestones. Play therapy is often used to evaluate disorders in children, but treatment plans are mostly based on adult observations, not from quantifiable evidence. Also, current technologies cannot synchronize the multi-modal, multi-channel data generated during play, or analyze the patterns found in one or more play sessions.

The new UCF system addresses the need for more comprehensive and substantive data by measuring activities such as the frequency, duration, and quality of play interactions and play patterns. Additionally, the Science of Play system can be used to create a big-data research base of information on the diagnoses of conditions such as autism, attention deficit hyperactivity disorder (ADHD) and anxiety. For example, the system could be used to determine the required length of play sessions per diagnosis and appropriate treatment models per diagnosis, thus enabling the development of more individualized treatment plans. Besides helping children, the invention can also assist educators, adult and family counselors, and even toy companies.

Technical Details

The Science of Play is a method and system for gathering behavioral, cognitive, language, observational, and physiological data through the use of synchronized cameras, sensors, devices and proprietary software. The system captures the physical, verbal and nonverbal interactions of a child's play therapy session and creates a digital transcript of the interactions. It also uses algorithms, data, and proprietary software to interpret the raw data collected and discern patterns of developmental or clinical interest.

In one example use of the invention, wireless, electronic tracking mechanisms (sensors) placed in different toys record a patient's interactions during play therapy. The system tracks and records the activity, including the duration, frequency and repetition of use per toy. The data, along with audio and video recordings, are synchronized and then converted into a digital transcript. Subsequent analysis with machine learning algorithms helps to identify previously unknown patterns in the patient's play behavior.

The invention adapts to a variety of settings, such as school classrooms, therapeutic playrooms, at-home playrooms, and training programs for teachers and counselors. It can also be used by toy companies to track the use, frequency and duration of toys.

Benefit

Market Application