Thesis (MScEng (Mechanical and Mechatronic Engineering))--University of Stellenbosch, 2008. / A solution is sought for the measurement of human deep tendon reflexes as part of a comprehensive patient condition monitoring system for use in a telemedicine context. This study focused on the development, testing and performance evaluation of a prototype compact patellar tendon reflex measurement system that is able to provide a quantitative reflex evaluation for use by medical practitioners and in a telemedicine environment. A prototype system was developed that makes use of Xsens MTx orientation sensors, force-sensing resistors and an electromyogram (EMG) to measure the reflex response. Suitable parameters identified for analysis included the change in pitch, angular velocity and acceleration of the lower leg, the EMG response, the tendon impact, and various latencies associated with these measurements. Other information considered included the age, mass, and physical dimensions of the test subject. Clinical testing was performed to collect data to evaluate the system performance. Subjective reflex evaluations were conducted by three doctors according to a standard reflex grading scale using video recordings of the tests. Self-organizing maps and multi-layer feed-forward (MLFF) artificial neural networks (ANNs) were used to analyze the collected data with the aim of pattern identification, data classification and reflex grading prediction. It was found that the MLFF network delivered the correct reflex grading with an accuracy of 85%, which was of the same order as the rate of differences between the subjective reflex evaluations performed by the doctors (80%). Furthermore, analysis of the data suggested that certain parameters were not necessary for the autonomous evaluation, such as EMG data and the tendon impact. The use of ANNs to analyze a reflex measurement as proposed by this study offers an accurate, repeatable and concise representation of the reflex that is familiar to doctors and suitable for use in a general clinical setting or for telemedicine purposes.