An overview is presented on research conducted in our lab to quantify the underlying principles behind the recognition of temporal patterns. We have been developing a theory based upon pattern matching and time-series analysis, which allows us to model and understand how humans recognize familiar patterns evolving over time and how performance degrades with noise. While our studies are primarily scientific in nature, the work has application beyond the elucidation of psychological and physiological mechanisms. We illustrate an application of these ideas to computer-based human identification through gait analysis. This study also illustrates a novel approach to interdisciplinary research by integrating experimental psychology with that of engineering design.