Testing gait rehabilitation devices on humans can be a difficult task, due to the effects of the neurological controls of the human body. This thesis advances the use of a passive dynamic walker (PDW) tuned to have asymmetric gait patterns similar to those with physical impairments to test rehabilitation devices. A passive dynamic walker is a multipendulum system that has a stable gait pattern when walking down a slope without any energy inputs except the forces due to gravity. A PDW model is better suited for testing rehabilitation devices because it has been shown to resemble human gait and separates the human neurological controls from the purely dynamic aspects of walking. This research uses different asymmetric gait patterns based on an asymmetric PDW to aid in the design of current and future rehabilitation methods. There are four major parts to this research: (1) the derivation of the current nine mass PDW model, (2) the effects of changing the moment of inertia and center of mass on each leg, (3) the effects of having a leg that is longer than the other and adding masses on the opposite leg to generate a symmetric gait, and (4) the design of a theoretical prosthesis that will break the assumption that the knee on the prosthetic leg should be in the same location as the intact leg. The result of changing the moment of inertia and center of mass on each leg in the nine mass model showed that it is an improvement over the previously used five mass model. This is because the five mass model forces the center of mass to change with the moment of inertia, while the nine mass model allows these to be changed independently of each other. A theoretical prosthesis has been developed in this research that is is significantly lighter while maintaining a symmetric gait. This was accomplished by moving the knee of the prosthetic limb below the location of the intact knee.

In this work, a new deinterleaving algorithm that can be used as a part of an ESM system and its implementation by using an FPGA is studied. The function of the implemented algorithm is interpreting the complex electromagnetic military field in order to detect and determine different RADARs and their types by using incoming RADAR pulses and their PDWs. It is assumed that RADAR signals in the space are received clearly and PDW of each pulse is generated as an input to the implemented algorithm system. Clustering analysis and a new interpreting process is used to deinterleave the RADAR pulses. In order to implement the algorithm, FPGA is used for achieving a faster and more efficient system. Comparison of the new algorithm and the previous deinterleaving studies is done. The simulation results are shown and discussed in detail.

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