Abstract
Adoption of exoskeletons for rehabilitation and locomotion outside the physical therapy clinic has been limited by relatively primitive methods for identifying and incorporating user intentions. Gait intention resolution varies from high-level goals (increase speed) to mid-level actions (increase stride length) to low-level joint behaviors (increase hip flexion). Onboard sensors only indirectly sense the human via the exoskeleton interface, but offer measurement consistency advantages over more direct methods. In this study, exoskeleton users, both able-bodied and having spinal cord injury, performed goal-level changes in gait speed to characterize joint- and action-level responses. Trials were completed in both trajectory-free and trajectory-based control modes, with both crutches and a walker. Results confirm statistically significant differences between the pre- and post-speed change joint-level measures of position and motor current. Coordination of joint-level changes resulted in significant differences in action-level measures (stride length and stride time). Users realized goal-level speed changes of as much as 0.30 and 0.19m/s in the trajectory-free and trajectory-based modes, respectively. Findings suggest that intent detection is possible for able-bodied and non-able-bodied users with onboard sensors alone. The intent signals depend on exoskeleton control settings, user ability, and gait phase, but do not differ with use of crutches or a walker. The characterization of these intent-related signals via onboard sensors enables more detailed intent recognition without the need for external sensors, which could benefit any control strategy that explicitly incorporates user intent.
Highlights
Exoskeletons have the potential to restore mobility and independence following neuro-muscular injury
There were no significant differences between pre- and post-command values of knee angle, knee current, hip angle, or hip current for the No Change command
For the Slow Down and Speed Up commands, post-command data exhibited significant differences compared to pre-command data at some point in the gait cycle for all joint measures in both control modes (Fig. 6 & Table 3)
Summary
Exoskeletons have the potential to restore mobility and independence following neuro-muscular injury. As an alternative to body-weight supported treadmill training, the exoskeleton’s trajectory tracking control system relieves the therapist’s burden to manipulate the user’s limbs and allows practice of repeatable overground locomotion patterns. For effective shared control with the user, though, the exoskeleton must recognize, interpret, and match the user’s intended movements. This work addresses the problem of distinguishing user-intent-related signals with the hypothesis that sensors onboard the exoskeleton exhibit. The associate editor coordinating the review of this manuscript and approving it for publication was Kang Li. distinguishable differences in response to a change in the user’s gait intent. At the lowest or joint level is the human’s intended motion for each joint independently, which might, for example, be measured via electromyographic (EMG) sensors on the muscles acting across the joint [1]. At the highest or goal level are behavioral objectives such as starting, stopping, or changing speeds [3]. ‘‘Intent’’ is not well-defined in the exoskeleton literature because it is unclear how much detail must be inferred about the human to qualify an exoskeleton’s control system as intent-aware
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