While the majority of gait research is focused on flat, level surfaces, in everyday life individuals must navigate diverse and changing terrain. Thus it is important to investigate gait patterns on multiple surfaces, which is why this dissertation concentrates on hill walking and running as well as the transitions between level and hills. To this end, it was necessary to create a versatile, kinematic-based event detection algorithm that was capable of detecting foot strike and toe off times for multiple gaits at various surface angles. Besides detailing the specific strategies used, we sought to understand how physiological and environmental factors influence the strategies that individuals choose. Many researchers have suggested that the preferred stride frequency (PSF) is determined by mechanical factors. However, this view ignores muscles which are the primary consumers of metabolic energy during running. Thus, we investigated the role of muscle activity in influencing the PSF during downhill running. (Abstract shortened by UMI.)