Learning to walk with a wearable robot in 880 simple steps: a pilot study on motor adaptation.

BACKGROUND: Wearable robots have been shown to improve the efficiency of walking in diverse scenarios. However, it is unclear how much practice is needed to fully adapt to robotic assistance, and which neuromotor processes underly this adaptation. Familiarization strategies for novice users, robotic optimization techniques (e.g. human-in-the-loop), and meaningful comparative assessments depend on this understanding. METHODS: To better understand the process of motor adaptation to robotic assistance, we analyzed the energy expenditure, gait kinematics, stride times, and muscle activities of eight naïve unimpaired participants across three 20-min sessions of robot-assisted walking. Experimental outcomes were analyzed with linear mixed effect models and statistical parametric mapping techniques. RESULTS: Most of the participants' kinematic and muscular adaptation occurred within the first minute of assisted walking. After ten minutes, or 880 steps, the energetic benefits of assistance were realized (an average of 5.1% (SD 2.4%) reduction in energy expenditure compared to unassisted walking). Motor adaptation was likely driven by the formation of an internal model for feedforward motor control as evidenced by the reduction of burst-like muscle activity at the cyclic end of robotic assistance and an increase in arm-swing asymmetry previously associated with increased cognitive load. CONCLUSION: Humans appear to adapt to walking assistance from a wearable robot over 880 steps by forming an internal model for feedforward control. The observed adaptation to the wearable robot is well-described by existing three-stage models that start from a cognitive stage, continue with an associative stage, and end in autonomous task execution. Trial registration Not applicable.

User-driven walking assistance: first experimental results using the MyoSuit.

Wearable robots for the legs have been developed for gait rehabilitation training and as assistive devices. Most devices have been rigid exoskeletons designed to substitute the function of users who are completely paralyzed. While effective for this target group, exoskeletons limit their users' contributions to movements. Soft wearable robots have been suggested as an alternative that allows, and requires, active contributions from users with residual mobility.In this work, we first tested if the MyoSuit, a lightweight, lower-limb soft wearable robot, affected the walking kinematics of unimpaired users. Secondly, we evaluated the assistance delivered to a patient with a gait impairment.In our first study, 10 unimpaired participants walked on a treadmill at speeds between 0.5 and 1.3 m/s. We found that wearing the MyoSuit in its transparency mode did not affect the participants' walking kinematics (RMS difference of joint angles < 1.6°). Step length and the ratio of stance-to-stride duration were not affected when wearing the MyoSuit.In our case study with one spinal cord injured participant, the MyoSuit supported the participant to increase his 10 MWT walking speed from 0.36 to 0.52 m/s, a substantial clinically meaningful improvement.Our results show that the MyoSuit allows user-driven, kinematically unaltered walking and provides effective assistance. Systems like the MyoSuit are a promising technology to bridge the gap between rigid exoskeletons and unassisted ambulation.