• DocumentCode
    602041
  • Title

    IADL assessment system based on EEG

  • Author

    Ren-Ying Fang ; Chi-Chun Hsia ; Jhing-Fa Wang

  • Author_Institution
    Dept. Electr. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
  • fYear
    2013
  • fDate
    12-16 March 2013
  • Firstpage
    243
  • Lastpage
    245
  • Abstract
    This paper aims to propose a system that used EEG to automatic measure human´s cognitive behavior ability, it can assist doctor long-term monitoring patients IADL (instrumental activities of daily living) abilities decline in daily life, and immediately give patient the care help they need, so it can save labor costs. For health care organization, the system can get more objective data to analyze. The system used a single channel wireless brainwave device that using Bluetooth connect PC device and capture subjects´ prefrontal brainwave to analysis. We use the improved adaptive PSR (Power Ratio) method as IADL assessment algorithm, according to different situations PSR can select the appropriate features to reduce unnecessary features and computational complexity, improve performance. Furthermore, the system used SVM as classifier and design fusion weights selection algorithm, the classifier selection based on different conditions in order to achieve optimum classification to get the best recognition rate. Our proposed system contains total 25 samples, including 15 male samples and 10 female samples for classifier training and testing, according to the experimental results show that the recognition rate can reach 68%, and the future, the system will collect more samples for training and algorithm modification to get better recognition results.
  • Keywords
    Bluetooth; cognition; electroencephalography; feature extraction; health care; medical signal processing; patient monitoring; support vector machines; Bluetooth; EEG; IADL assessment system; SVM; adaptive PSR; classifier; cognitive behavior; computational complexity; fusion weights selection algorithm; instrumental activities of daily living; patient monitoring; prefrontal brainwave; single channel wireless brainwave device; Alzheimer´s disease; Electroencephalography; Feature extraction; Magnetic resonance imaging; Support vector machines; Training; ANN; Cognitive behavior ability; IADL; PR; SVM; brainwave;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Orange Technologies (ICOT), 2013 International Conference on
  • Conference_Location
    Tainan
  • Print_ISBN
    978-1-4673-5934-4
  • Type

    conf

  • DOI
    10.1109/ICOT.2013.6521202
  • Filename
    6521202