• DocumentCode
    1662078
  • Title

    Detecting wandering behavior based on GPS traces for elders with dementia

  • Author

    Qiang Lin ; Daqing Zhang ; Xiaodi Huang ; Hongbo Ni ; Xingshe Zhou

  • Author_Institution
    Shaanxi Key Lab. of Embedded Syst. Technol., Northwestern Polytech. Univ., Xi´an, China
  • fYear
    2012
  • Firstpage
    672
  • Lastpage
    677
  • Abstract
    Wandering is among the most frequent, problematic, and dangerous behaviors for elders with dementia. Frequent wanderers likely suffer falls and fractures, which affect the safety and quality of their lives. In order to monitor outdoor wandering of elderly people with dementia, this paper proposes a real-time method for wandering detection based on individuals´ GPS traces. By representing wandering traces as loops, the problem of wandering detection is transformed into detecting loops in elders´ mobility trajectories. Specifically, the raw GPS data is first preprocessed to remove noisy and crowded points by performing an online mean shift clustering. A novel method called θ_WD is then presented that is able to detect loop-like traces on the fly. The experimental results on the GPS datasets of several elders have show that the θ_WD method is effective and efficient in detecting wandering behaviors, in terms of detection performance (AUC > 0.99, and 90% detection rate with less than 5 % of the false alarm rate), as well as time complexity.
  • Keywords
    Global Positioning System; computational complexity; geriatrics; medical control systems; θ_WD; GPS datasets; GPS traces; elderly people; elders with dementia; falls; fractures; loop-like traces; mobility trajectories; online mean shift clustering; real-time method; time complexity; wandering behavior detection; wandering detection; Dementia; Global Positioning System; Lapping; Monitoring; Noise measurement; Safety; Vectors; GPS trace; dementia; elderly care; wandering behavior; wandering detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Automation Robotics & Vision (ICARCV), 2012 12th International Conference on
  • Conference_Location
    Guangzhou
  • Print_ISBN
    978-1-4673-1871-6
  • Electronic_ISBN
    978-1-4673-1870-9
  • Type

    conf

  • DOI
    10.1109/ICARCV.2012.6485238
  • Filename
    6485238