Abstract
Background:
Osteotomies during rhinoplasty are usually based on surgeon's proprioception to determine the number, energy, and trajectory of impacts.
Objective:
The first objective was to detect the occurrence of fractures. The second objective was to determine when the thicker frontal bone was encountered by the osteotome.
Materials and Methods:
An instrumented hammer was used to measure the impact force during lateral osteotomies on nine human anatomic specimens. A prediction algorithm was developed using machine learning techniques, to detect the occurrence of fractures, and the proximity of the osteotome to the frontal bone.
Results:
The algorithm was able to predict the occurrence of fractures and the proximity to the frontal bone with a prediction rate of 83%, 91%, and 93% when allowing for an error of 0, 1, and 2 impacts, respectively. The location of the osteotome in the frontal bone was predicted with an error of 7.7%.
Conclusion:
An osteotomy hammer measuring the impact force when performing lateral osteotomies can predict the occurrence of fractures and the proximity to the frontal bone, providing the surgeon with instant feedback.
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Supplementary Material
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