Human Gait Entrainment to Soft Robotic Hip Perturbation During Simulated Overground Walking.

Entraining human gait with a periodic mechanical perturbation has been proposed as a potentially effective strategy for gait rehabilitation, but the related studies have mostly depended on the use of a fixed-speed treadmill (FST) due to various practical constraints. However, imposing a constant treadmill speed on participants becomes a critical problem because this speed constraint prohibits the participants from adjusting the gait speed, resulting in significant alterations in natural biomechanics as the entrainment alters the stride frequency. In this study, we hypothesized that the use of a variable-speed treadmill (VST), which enables the participants to continuously adjust their speed, can improve the success rate of gait entrainment and preserve natural gait biomechanics. To test this hypothesis, we recruited 15 young and healthy adults and let them walk on a conventional FST and a self-paced VST while wearing a soft robotic hip exosuit, which applied hip flexion perturbations at various frequencies, ranging from the preferred walking frequency to a 30% increased value. Kinematics and kinetics of the participants' walking under the two treadmill conditions were measured on two separate days. Experimental results demonstrated a higher success rate of entrainment during VST walking compared to FST walking, particularly at faster perturbation frequencies. Furthermore, walking on VST facilitated the maintenance of natural biomechanics, such as stride length and normalized propulsive impulse, better than walking on FST. The observed improvement, primarily attributed to allowing an increase in walking speed following the increase in the perturbation frequency, suggests that using a self-paced VST is a viable method for exploiting the potentially beneficial therapeutic effects of entrainment in gait rehabilitation.

Introduction to a Twin Dual-Axis Robotic Platform for Studies of Lower Limb Biomechanics.

This paper presents a twin dual-axis robotic platform system which is designed for the characterization of postural balance under various environmental conditions and quantification of bilateral ankle mechanics in 2 degrees-of-freedom (DOF) during standing and walking. Methods: Validation experiments were conducted to evaluate performance of the system: 1) to apply accurate position perturbations under different loading conditions; 2) to simulate a range of stiffness-defined mechanical environments; and 3) to reliably quantify the joint impedance of mechanical systems. In addition, several human experiments were performed to demonstrate the system's applicability for various lower limb biomechanics studies. The first two experiments quantified postural balance on a compliance-controlled surface (passive perturbations) and under oscillatory perturbations with various frequencies and amplitudes (active perturbations). The second two experiments quantified bilateral ankle mechanics, specifically, ankle impedance in 2-DOF during standing and walking. The validation experiments showed high accuracy of the platform system to apply position perturbations, simulate a range of mechanical environments, and quantify the joint impedance. Results of the human experiments further demonstrated that the platform system is sensitive enough to detect differences in postural balance control under challenging environmental conditions as well as bilateral differences in 2-DOF ankle mechanics. This robotic platform system will allow us to better understand lower limb biomechanics during functional tasks, while also providing invaluable knowledge for the design and control of many robotic systems including robotic exoskeletons, prostheses and robot-assisted balance training programs. Clinical and Translational Impact Statement- Our robotic platform system serves as a tool to better understand the biomechanics of both healthy and neurologically impaired individuals and to develop assistive robotics and rehabilitation training programs using this information.