Design of a Golf Swing Injury Detection and Evaluation open service platform with Ontology-oriented clustering case-based reasoning mechanism

Technol Health Care. 2015:24 Suppl 1:S261-70. doi: 10.3233/THC-151083.

Abstract

Nowadays, people can easily use a smartphone to get wanted information and requested services. Hence, this study designs and proposes a Golf Swing Injury Detection and Evaluation open service platform with Ontology-oritened clustering case-based reasoning mechanism, which is called GoSIDE, based on Arduino and Open Service Gateway initative (OSGi). GoSIDE is a three-tier architecture, which is composed of Mobile Users, Application Servers and a Cloud-based Digital Convergence Server. A mobile user is with a smartphone and Kinect sensors to detect the user's Golf swing actions and to interact with iDTV. An application server is with Intelligent Golf Swing Posture Analysis Model (iGoSPAM) to check a user's Golf swing actions and to alter this user when he is with error actions. Cloud-based Digital Convergence Server is with Ontology-oriented Clustering Case-based Reasoning (CBR) for Quality of Experiences (OCC4QoE), which is designed to provide QoE services by QoE-based Ontology strategies, rules and events for this user. Furthermore, GoSIDE will automatically trigger OCC4QoE and deliver popular rules for a new user. Experiment results illustrate that GoSIDE can provide appropriate detections for Golfers. Finally, GoSIDE can be a reference model for researchers and engineers.

Keywords: Golf swing; Open service platform; case-based reasoning; ontology; quality of experience.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Athletic Injuries / prevention & control*
  • Biomechanical Phenomena
  • Cloud Computing
  • Golf*
  • Humans
  • Image Processing, Computer-Assisted
  • Movement / physiology*
  • Postural Balance
  • Posture
  • Remote Sensing Technology / methods
  • Smartphone*
  • User-Computer Interface