• DocumentCode
    3321496
  • Title

    Assessment of peripheral vascular occlusive disease using adaptive network-based fuzzy inference system

  • Author

    Lin, Chia-Hung ; Pan, Shih-Ming ; Du, Yi-Chun

  • Author_Institution
    Dept. of Electr. Eng., Kao-Yuan Univ., Kaohsiung, Taiwan
  • Volume
    2
  • fYear
    2010
  • fDate
    5-7 May 2010
  • Firstpage
    223
  • Lastpage
    226
  • Abstract
    This paper proposes the assessment of diabetic foot using adaptive network-based fuzzy inference system (ANFIS). Diabetic foot occurs due to peripheral vascular occlusive disease (PVOD) and leads to disable claudication and gangrene. According to previous study, the transit timing, shape waveforms, and normalized amplitudes of photoplethysmography (PPG) signals tend to increase with PVOD severity. An ANFIS is proposed to assess PVOD using the absolute bilateral differences of the timing parameters ΔPTTf, ΔPTTp, and ΔRT. For twenty subjects, including normal condition (Nor), lower-grade disease (LG), and higher-grade disease (HG) groups, the results will show high accuracy for PVOD assessment.
  • Keywords
    diseases; fuzzy reasoning; medical signal processing; plethysmography; adaptive network based fuzzy inference system; claudication; diabetic foot assessment; gangrene; peripheral vascular occlusive disease; photoplethysmography signals; Adaptive systems; Artificial neural networks; Diabetes; Diseases; Foot; Fuzzy neural networks; Fuzzy systems; Pulse shaping methods; Shape; Timing; Adaptive Network-based Fuzzy Inference System (ANFIS); Peripheral Vascular Occlusive Disease (PVOD); Photoplethysmography (PPG);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Communication Control and Automation (3CA), 2010 International Symposium on
  • Conference_Location
    Tainan
  • Print_ISBN
    978-1-4244-5565-2
  • Type

    conf

  • DOI
    10.1109/3CA.2010.5533565
  • Filename
    5533565