Measuring Early Pre-symptomatic Changes in Locomotion of Rodent Models of Neurological and Neuromuscular Diseases

Neurological and neuromuscular diseases are usually difficult to diagnose at early stages. The aim of this Ph.D. dissertation is to detect neurological and neuromuscular diseases early by using a gait analysis system in laboratory rats. This includes diseases such as Amyotrophic Lateral Sclerosis, muscular injuries, and Parkinson's disease. Several preliminary experiments have been developed on rodents that have been used as animal models for human diseases. This work developed an effective noninvasive diagnostic methodology which can provide the probability that a rat is exposed to a disease that affects its locomotion. The gait analysis system measures ground reaction forces and associated time and frequency parameters when a rat walks on the sensor module. These measurements are used as input to a logistic regression model that assesses the probability that the animal model has a specific disease that affects its locomotion. All the models we have developed have achieved specificity and sensitivity values of at least 90%. This dissertation has the potential to have a significant impact on helping to diagnose diseases that affect locomotion early, which is currently very difficult to do effectively. This new methodology also has the potential to be instrumental in finding and validating new therapeutic procedures for the studied ailments