A Smart Mobile App to Encourage Kicking Movements in Infants At Risk of Cerebral Palsy

Undergraduate #106
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

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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, ayanna.howard@ece.gatech.edu

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.