Authors:
Isabel Moscol
1
;
William Solórzano-Requejo
1
;
2
;
Carlos Ojeda
1
and
Ciro Rodríguez
3
Affiliations:
1
Department of Mechanical and Electrical Engineering, Universidad de Piura, Piura, Peru
;
2
ETSI Industriales, Universidad Politécnica de Madrid, Madrid, Spain
;
3
Department of Software Engineering, Universidad Nacional Mayor de San Marcos, Lima, Peru
Keyword(s):
Hip Arthroplasty, Biomaterials, Short Stems, FEA Software, Artificial Intelligence.
Abstract:
Hip replacement is one of the most successful surgical events that progressively more patients require because of the better life expectancy and increase in the average age of several countries. It further promoted the improvement of hip prosthesis lifespan in sciences such as materials, mechanics and, recently, computer science with artificial intelligence (AI). The present investigation aims to make a systematic review of the progress with recent developments and criteria to get optimal outcomes in the design and selection of hip implants, emphasizing femoral stem parameters for their relevance to the entire prosthesis performance. New software tools such as clustering, and a different finite element analysis (FEA) approach are introduced to speed up customized design processes without sacrificing accuracy. Clustering algorithms delimited the proximal femur properly according to its anatomical locations. Moreover, Altair SimSolid® software proved satisfactory accuracy compared to N
X® simulation values despite the complex morphology of the proximal femur with a maximum deviation of 12.94% and a simulation time of less than 30%.
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