• DocumentCode
    2945773
  • Title

    A Framework for Golf Training Using Low-Cost Inertial Sensors

  • Author

    Burchfield, Ryan ; Venkatesan, S.

  • Author_Institution
    Comput. Eng. Program, Univ. of Texas at Dallas, Richardson, TX, USA
  • fYear
    2010
  • fDate
    7-9 June 2010
  • Firstpage
    267
  • Lastpage
    272
  • Abstract
    Body Sensor Networks are rapidly expanding to everyday applications due to recent advancements in Micro-Electro-Mechanical Systems (MEMS) sensing, wireless communication and power management technologies. We leverage these advancements to develop a framework for the use of MEMS inertial sensors as a low-cost putting coach for golf. Accurate putting requires substantial control and precision that is acquired via significant practice. Unfortunately, many golfers are not aware that they are practicing flawed mechanics. An electronic coach has the capability to point out these flawed movements before they become the norm. Our framework is the first step to an electronic coach and consists of a model for a putting swing, the design of a custom sensor platform and the implementation of signal processing functions to accurately estimate the trajectory of the golf club. Based upon our model we propose the use of sensor fusion algorithms to increase accuracy without increasing hardware demands. The accuracy of the system is experimentally evaluated using a controlled test platform.
  • Keywords
    Body sensor networks; Communication system control; Energy management; Management training; Microelectromechanical systems; Micromechanical devices; Power system management; Signal processing algorithms; Technology management; Wireless communication;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Body Sensor Networks (BSN), 2010 International Conference on
  • Conference_Location
    Singapore, Singapore
  • Print_ISBN
    978-1-4244-5817-2
  • Type

    conf

  • DOI
    10.1109/BSN.2010.46
  • Filename
    5504766