title: Statistical Analyses of Femur Parameters for Designing Anatomical Plates.
abstract: Femur parameters are key prerequisites for scientifically designing anatomical plates. Meanwhile, individual differences in femurs present a challenge to design well-fitting anatomical plates. Therefore, to design anatomical plates more scientifically, analyses of femur parameters with statistical methods were performed in this study. The specific steps were as follows. First, taking eight anatomical femur parameters as variables, 100 femur samples were classified into three classes with factor analysis and Q-type cluster analysis. Second, based on the mean parameter values of the three classes of femurs, three sizes of average anatomical plates corresponding to the three classes of femurs were designed. Finally, based on Bayes discriminant analysis, a new femur could be assigned to the proper class. Thereafter, the average anatomical plate suitable for that new femur was selected from the three available sizes of plates. Experimental results showed that the classification of femurs was quite reasonable based on the anatomical aspects of the femurs. For instance, three sizes of condylar buttress plates were designed. Meanwhile, 20 new femurs are judged to which classes the femurs belong. Thereafter, suitable condylar buttress plates were determined and selected.
authors.affiliation: College of Internet of Things Engineering, Hohai University, Changzhou, China; Changzhou City Key Lab of Orthopaedic Implants Digital Technology, Changzhou, China.
authors.forename: Lin
authors.identifier: 0000-0001-6894-6474
authors.initials: L
authors.lastname: Wang
authors.affiliation: College of Internet of Things Engineering, Hohai University, Changzhou, China; Changzhou City Key Lab of Orthopaedic Implants Digital Technology, Changzhou, China.
authors.forename: Kunjin
authors.identifier: 0000-0001-9436-6457
authors.initials: K
authors.lastname: He
authors.affiliation: College of Internet of Things Engineering, Hohai University, Changzhou, China; Changzhou City Key Lab of Orthopaedic Implants Digital Technology, Changzhou, China.
authors.forename: Zhengming
authors.identifier: 0000-0002-5763-1503
authors.initials: Z
authors.lastname: Chen
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D001860:Bone Plates; D016000:Cluster Analysis; D016002:Discriminant Analysis; D005269:Femur / Q000033:anatomy & histology*; D064368:Healthy Volunteers; D006801:Humans; D007091:Image Processing, Computer-Assisted; D021621:Imaging, Three-Dimensional; D008953:Models, Anatomic; D015233:Models, Statistical; D011474:Prosthesis Design / Q000379:methods*; D012984:Software; D013314:Stress, Mechanical