Exploring the potential of using the foot sole pressure pattern to control step length in exoskeleton gait

Abstract

Semi-autonomous robotic exoskeletons enable paraplegics to walk again. The exoskeleton envelops the paraplegic’s waist, legs and feet. When the user gives the command to start walking, the exoskeleton’s robotic legs start a cyclic walking motion. The user, aided by crutches, follows this fixed cyclic motion, shifting their weight to the stance leg to allow the other leg to swing. A current challenge in exoskeleton development is to give the user more freedom and autonomy in the interaction with the exoskeleton. This study focuses on allowing the user to control step length in an intuitive manner. It is known from many previous studies found in literature, that during gait the center of pressure in the feet follows a distinctive pattern. Moreover, this pattern correlates with gait parameters such as step length. The goal of the current study is to explore the potential of using this pressure pattern to control step length in exoskeletons for paraplegics. The pressure pattern consists of three temporal parameters: the x- and y-coordinates of the center of pressure (CoP X and CoP Y) and the total force acting perpendicular to the sole (Fz). Preliminary experiments were performed, in which three participants traversed a walking track with steps indicated on the floor. Halfway the track step length transitioned from short to long or vice versa. To approximate exoskeleton gait subjects used crutches for balancing while walking. The participants wore sensor shoes that recorded the pressure pattern while they walked. Results indicate that the pressure pattern can be used to distinguish steady state long steps from steady state short steps. This was shown for both an extreme difference in step length, as well as for a moderate difference in step length. Respectively eight and five metrics were identified that showed a likely difference (no overlapping boxes in box plots) between these step groups for all three subjects. Examples of successful metrics include ”peak Fz value” and ”CoP X value at 0% of stance phase”. Only three of these metrics showed a likely difference between steady state steps and the transition step; i.e. it is harder but possible to gather from the pressure pattern, that a transition in step length is taking place. Results did not, however, indicate any potential in predicting an intended change in step length before the actual transition takes place. This makes the potential of controlling step length by manipulating the pressure pattern questionable but not out of the question. Testing with more participants would likely bring more clarity, as well as studying the capabilities of paraplegic exoskeleton users to manipulate the pressure pattern with upper body movements while walking.