An investigation into the temperature distribution resulting from cutting of compact bone using a reciprocating bone saw

Surgical procedures such as osteotomy and hip replacement involve the cutting of bone with the aid of various manual and powered cutting instruments including manual and powered bone saws. The basic mechanics of bone sawing processes are consistent with most other material sawing processes such as for wood or metal. Frictional rubbing between the blade of the saw and the bone results in the generation of localised heating of the cut bone. Research studies have been carried out which consider the design of the bone saw which deals with specifics of the saw teeth geometry and research which examines the effect of drilling operations on heating of the bone has shown that elevated temperatures will occur from frictional overheating. This overheating in localised areas is known to have an impact on the rate of healing of the bone post operation and the sharpness life of the blade. The purpose of this study was to measure the temperature at three zones at fixed intervals of 3mm, 6mm, and 9mm away from the cutting zone. It should be noted that it was the first time that this measurement technique was used to measure the temperature gradient through the bone specimen thereby establishing the extent to which clinicians are experiencing thermal injury during sawing of bone while using a reciprocating saw. The effect of various cutting feed rate on temperature elevation was also investigated in this research. The results showed that there will be a region of bone at least 9mm either side of the cutting blade experiencing thermal injury as temperatures in this region exceeded the threshold temperature of 44°C for necrosis (cell death).

Development of a semi-automatic self learning pattern recognition system for the control of electronic boards

This project was funded under the Applied Research Grants Scheme administered by Enterprise Ireland. The project was a partnership between Galway - Mayo Institute of Technology and an industrial company, Tyco/Mallinckrodt Galway. The project aimed to develop a semi - automatic, self - learning pattern recognition system capable of detecting defects on the printed circuits boards such as component vacancy, component misalignment, component orientation, component error, and component weld. The research was conducted in three directions: image acquisition, image filtering/recognition and software development. Image acquisition studied the process of forming and digitizing images and some fundamental aspects regarding the human visual perception. The importance of choosing the right camera and illumination system for a certain type of problem has been highlighted. Probably the most important step towards image recognition is image filtering, The filters are used to correct and enhance images in order to prepare them for recognition. Convolution, histogram equalisation, filters based on Boolean mathematics, noise reduction, edge detection, geometrical filters, cross-correlation filters and image compression are some examples of the filters that have been studied and successfully implemented in the software application. The software application developed during the research is customized in order to meet the requirements of the industrial partner. The application is able to analyze pictures, perform the filtering, build libraries, process images and generate log files. It incorporates most of the filters studied and together with the illumination system and the camera it provides a fully integrated framework able to analyze defects on printed circuit boards.