Quantitative analysis of trajectory tracking characteristics for a functional human wrist under resistive loads

Functional neuromuscular stimulation (FNS) is electrical stimulation for muscle control. This ability has brought about a new advent in the field of prosthetics called neuroprosthetics. Neuroprosthetics consists of a wide field of devices that stimulate muscles or nerve tissue to either control part of the human body or to give it feedback. Strokes and spinal cord injuries cause a neural disconnect between the brain and the body. Recent research with FNS is exploring methods of bypassing this disconnect and allowing the affected person to control their body with just a thought. This same technology is also being used in robotic limbs that are controlled by thought and are capable of giving the wearer feedback about their environment. Researchers use control algorithms to convert brain signals into motion. With the development and testing of these control algorithms the question has arisen of how to determine when a controller is good enough. How should the neuroprosthetic perform? A standard is needed with which neuroprosthetic control can be measured. The purpose of this research is to measure standard engineering control metrics from functional human wrists in order to develop a standard for future neuroprosthetic design. Three different types of functions were presented to healthy human subjects for trajectory tracking exercises. These functions included step functions to measure transient responses, ramp functions to measure steady state responses, and periodic functions, which are most typical of normal activities of daily living. Varying loads were applied to the participants' wrists, and wrist position was measured. The data from these three experiments were used to measure standard engineering control metrics. From these control metrics statistical regression models were developed to provide a quantitative view of healthy human wrist control with a load applied to it.