A Method for Extracting Temporal Parameters Based on Hidden Markov Models in Body Sensor Networks With Inertial Sensors

  title={A Method for Extracting Temporal Parameters Based on Hidden Markov Models in Body Sensor Networks With Inertial Sensors},
  author={Eric Guenterberg and Allen Yuqing Yang and Hassan Ghasemzadeh and Roozbeh Jafari and Ruzena Bajcsy and S. Shankar Sastry},
  journal={IEEE Transactions on Information Technology in Biomedicine},
Human movement models often divide movements into parts. In walking, the stride can be segmented into four different parts, and in golf and other sports, the swing is divided into sections based on the primary direction of motion. These parts are often divided based on key events, also called temporal parameters. When analyzing a movement, it is important to correctly locate these key events, and so automated techniques are needed. There exist many methods for dividing specific actions using… 

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  • Computer Science
    2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
  • 2011
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  • L. LeeW. Grimson
  • Computer Science
    Proceedings of Fifth IEEE International Conference on Automatic Face Gesture Recognition
  • 2002
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