Discipline: Technology and Engineering
Subcategory: Computer Science & Information Systems
Janelle Boyd - Delaware State University
Co-Author(s): De’Aira Bryant, University of South Carolina, Columbia, SC Jgenisius Harris, Ayanna Howard, and Sergio García-Vergara, Georgia Institute of Technology, Atlanta, GA Michelle Smith, Rhodes College, Memphis, TN Yu-Ping Chen, Georgia State University, Atlanta, GA
Observations of spontaneous kicking patterns in infants has presented valuable insight into their development. At times, these kicking patterns can detect potential developmental delays in at-risk infants to support diagnosis and intervention. However, the prevalence of developmental disabilities has increased and a protocol for early diagnosis is still not widely available outside of direct clinical observations. This paper presents a mobile application that aims at providing a cost-effective and prompt method for detecting atypical kicking patterns in at-risk infants. The Infant Smart-Mobile uses a virtual infant-activated mobile, coupled with wearable sensors for monitoring infant leg movements. Furthermore, to test the feasibility of the technology, the Infant Smart-Mobile is evaluated with respect to data collected from a robotic humanoid designed to simulate kicking in a manner similar to that of an infant with atypical motor behavior. Moreover, we compare atypical kicking patterns to that of a typical kick, and discuss the potential of the application to be used in clinical and home-based intervention protocols.
Funder Acknowledgement(s): National Science Foundation Grant No. 0851643, CRA-W, CDC
Faculty Advisor: Ayanna Howard, email@example.com
Role: The project consisted of three main counterparts. The first part involved the design of a physical baby mobile that would adjust speed based off of the kicking pattern of the infant. The second part consisted of the creation of a virtual mobile that simulated the physical baby mobile. The last counterpart involved the design of a wearable sensor that would gather raw data used by both the physical and virtual mobile. With this in mind, I designed and implemented the Virtual Infant Smart-Mobile application utilizing Unity3D. Additionally, using data analysis, I designed a kicking assessment algorithm that could control how the virtual mobile responded to various kicking patterns simulated by the Aldebaran NAO.