Predictive simulation based on dynamic optimization using musculoskeletal models is a powerful approach for studying human gait. Predictive musculoskeletal simulation may be used for a variety of applications from designing assistive devices to testing theories of motor control. However, the underlying cost function for the predictive optimization is unknown and is generally assumed a priori.
Shoes were invented to provide user comfort using rubber soles, despite marginal improvement in human mobility. Unlike shoes, current lower-limb exoskeletons use fixed stiffness springs to store and recycle energy to improve mobility.
Remote monitoring of gait performance offers possibilities for objective evaluation, and tackling impairment in motor ability, gait, and balance in populations such as elderly, stroke, multiple sclerosis, Parkinson’s, etc.
Discrete, rapid (i.e., ballistic like) muscle activation patterns have been observed in ankle muscles (i.e., plantar flexors and dorsiflexors) of able-bodied individuals during voluntary posture control.
Lower-limb amputees typically experience reduced mobility and higher metabolic rates than non-amputees. It may be possible to improve their mobility and metabolic rate with an optimized robotic prosthesis.
This paper presents a running control architecture for a powered knee and ankle prosthesis that enables a transfemoral amputee to run with a biomechanically appropriate running gait and to intentionally transition between a walking and running gait…