Locomotion is of prime importance in enabling human beings to effectively respond

in space and time to meet different needs. Approximately 2 million Americans live

with an amputation with most of those amputations being of the lower limbs. To

advance current state-of-the-art lower limb prosthetic devices, it is necessary to adapt

performance at a level of intelligence seen in human walking. As such, this thesis

focuses on the mechanisms involved during human walking, while transitioning from

rigid to compliant surfaces such as from pavement to sand, grass or granular media.

Utilizing a unique tool, the Variable Stiffness Treadmill (VST), as the platform for

human walking, rigid to compliant surface transitions are simulated. The analysis of

muscular activation during the transition from rigid to different compliant surfaces

reveals specific anticipatory muscle activation that precedes stepping on a compliant

surface. There is also an indication of varying responses for different surface stiffness

levels. This response is observed across subjects. Results obtained are novel and

useful in establishing a framework for implementing control algorithm parameters to

improve powered ankle prosthesis. With this, it is possible for the prosthesis to adapt

to a new surface and therefore resulting in a more robust smart powered lower limb

prosthesis.