LAUSR

In this paper, a fuzzy logic-based artificial intelligence technique is delineated to optimize surface reconstruction parameters, initiating from raw point cloud data using contactless scanning of transtibial prosthetic socket. The prosthetic socket having a free-form surface is considered for reconstruction of an accurate and complete digital model, which is further crucial for subsequent design, analysis and production. The input factors considered for the socket surface reconstruction includes number of points, filtering, triangle counts and smoothing level. The experimental trials are performed using face-centered central composite design, and further experimental data are used to establish Mamdani fuzzy logic model to predict the surface standard deviation and required space in computer memory as the response parameters. The confirmation experiment results reveal that the fuzzy model shows good agreement of 96.53% with the experimental measured value. Based on the results, it is proved that established fuzzy model can be used for predicting the surface reconstruction parameters to improve the final accuracy of the transtibial prosthetic socket model. The results concluded that the fuzzy logic provides commendable results; in addition, it successfully predicts the effect of different parameters considered for surface reconstruction on surface accuracy and computer file size.