Modified Fuzzy Logic System Based Predictive Model for Cortical Bone Drilling Temperature

Abstract

Bone drilling is a widely used procedure in fracture treatments. During drilling, the temperature in the host site increases and leads to permanent thermal damage called osteonecrosis, which increases the healing time and weakens the implant stability. So, drilling with controlled temperature generation is a major challenge for surgeons. The present work aims to predict the bone drilling temperature using interval type-2 fuzzy logic systems (IT2FLS) for the first time. The developed fuzzy model predicts the temperature by accounting the drill bit geometry and the drilling parameters. The developed triangular and trapezoidal IT2FLS predict the temperature within a maximum error of 7%. Also, a comparative study is reported between the type-1 and type-2 membership functions. The proposed system helps to simplify the temperature modelling in surgical drilling process.

Keywords

• centre of sets type reduction
• interval type-2 fuzzy logic system
• footprint of uncertainty
• trapezoidal membership function