• DocumentCode
    3661481
  • Title

    An HMM-based gait comparison: Using Alzheimer´s disease patients as examples

  • Author

    Wei-Hsin Wang;Hao-Li Wu;Pau-Choo Chung;Ming-Chyi Pai

  • Author_Institution
    Dept. of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan (R.O.C.)
  • fYear
    2015
  • fDate
    7/1/2015 12:00:00 AM
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The similarity comparisons between single-task walking and dual-task walking on Alzheimer´s disease (AD) patients has been commonly performed for cognitive declination measurement. This paper presents a personalized gait similarity measurement approach based on Hidden Markov model for the self-comparison between the single-task walking and dual-task walking. Compared with traditional approaches which use statistics parameters comparison on normal group and AD group, the proposed personalized HMM-based self-comparison approach can avoid the dilemma resulted from personal differences such as walking habits and physical conditions such as height and weight. In this paper, two groups, 42 AD patients and 64 healthy control (HC) people, participate the experiments. The results show the promising of the proposed approach in comparing the AD from the normal people.
  • Keywords
    "Hidden Markov models","Legged locomotion","Education"
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), 2015 International Joint Conference on
  • Electronic_ISBN
    2161-4407
  • Type

    conf

  • DOI
    10.1109/IJCNN.2015.7280795
  • Filename
    7280795