Associate professor
Supervisor of Master's Candidates
E-Mail:
Date of Employment:2009-12-14
School/Department:信息学院
Education Level:博士研究生毕业
Business Address:厦门大学翔安校区西部片区6号楼(睿信楼)202室
Gender:Male
Contact Information:yunfengwu@xmu.edu.cn
Degree:Doctor of Engineering (D.Eng.)
Status:在职
Alma Mater:北京邮电大学
Discipline:生物医学工程
信号与信息处理
Academic Honor:
2013 Outstanding talents in the new century
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DOI number:10.1007/s11517-007-0278-7
Journal:Medical & Biological Engineering & Computing
Abstract:Externally detected vibroarthrographic (VAG) signals bear diagnostic information related to the roughness, softening, breakdown, or the state of lubrication of the articular cartilage surfaces of the knee joint. Analysis of VAG signals could provide quantitative indices for noninvasive diagnosis of articular cartilage breakdown and staging of osteoarthritis. We propose the use of statistical parameters of VAG signals, including the form factor involving the variance of the signal and its derivatives, skewness, kurtosis, and entropy, to classify VAG signals as normal or abnormal. With a database of 89 VAG signals, screening efficiency of up to 0.82 was achieved, in terms of the area under the receiver operating characteristics curve, using a neural network classifier based on radial basis functions.
Co-author:Y. F. Wu
First Author:R. M. Rangayyan*
Indexed by:Article
Volume:46
Issue:3
Page Number:223-232
Translation or Not:no
Date of Publication:2008-03-01
Included Journals:SCI
Links to published journals:https://doi.org/10.1007/s11517-007-0278-7