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
Link To Document :
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