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
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