The choices for analyzing cognitive load performance data are often problematic as they are task-dependent and do not generalize well. This makes research into task independent variables necessary. Complexity is one such measure that one can retrieve from normal cognitive load measurements. Using time series analysis techniques provides an efficient, less altered route to measurements that can account for multiple task dependent measures without being attached to the specific task. In this experiment, we present stimuli to participants based on occluded hand location to determine object recognition effectiveness. Maintaining a 65%- 75%-correct identification rate using a staircase procedure allowed for object recognition time and accuracy profile creation. Over the 18-inch hand movement, we observed a bi-modal distribution in reaction times with a "far hand effect" decreasing times at around 18-15 inches from the stimulus, increasing to a peak at 15-12 inches, and decreasing again as a participant moves his/her hand closer to the stimulus. Nonlinear time series analysis was performed on the data; more specifically I used wavelet transform modulus maxima to analyze a continuous wavelet transform created from the time series based off the effect hand location has on object perception.