Toward Ubiquitous Lower Limb Exoskeleton Use in Children and Young Adults

Overview

People with cerebral palsy (CP), muscular dystrophy (MD), spina bifida, or spinal cord injury often have muscle weakness, and problems moving their arms and legs. The NIH designed a new brace device, called an exoskeleton, that is worn on the legs and helps people walk. This study is investigating new ways the exoskeleton can be used in multiple settings while performing different walking or movement tasks, which we call ubiquitous use. For example, we will ask you to walk on a treadmill at different speeds, walk up and down a ramp, or walk through an obstacle course. Optionally, the exoskeletons may also use functional electrical stimulation (FES), a system that sends electrical pulses to the muscle to help it move the limb.

STUDY DESCRIPTION: The following exploratory observational study is designed to create a framework that permits rapid development, piloting, and acute evaluation of pediatric exoskeleton control paradigms for daily, ubiquitous use across multiple settings. Most existing evaluations of pediatric exoskeleton control modes are limited to a flat walking task.The novelty of this study design is the translation of control modes to different functional tasks and comparisons between fixed and adaptive parameters across the tasks. Across all participants, three main control modes will be tested: assist, resist, and interleaved (alternating assist and resist). Control parameters will either be fixed for all tasks conducted or may adapt based on the motions of a given activity. Following informed consent and assent, screening, and calibration of control parameters, an acclimation period to the exoskeleton and control modes will occur. Each control mode will be tested across ubiquitous activities of daily living and outcomes will be compared to baseline (without wearing the exoskeleton). Our central hypothesis is that existing control paradigms that have been previously validated in walking can be successfully translated to improve knee extension deficiency and/or knee extensor muscle activity in multiple different functional mobility tasks. OBJECTIVES: * Primary Objectives: 1) To evaluate acute biomechanical and neuromuscular effects of pediatric exoskeleton control paradigms on knee extension deficiency across ubiquitous tasks and 2) Assess whether controller behavior and performance align with the intent of its prescribed design consistently across tasks. * Secondary objectives: 1) Measuring functional performance of tasks conducted with each control paradigm and 2) Characterizing muscle activation of knee extensors during each task. ENDPOINTS: Primary Endpoints: * To evaluate knee extension deficiency, we will use 1) Peak knee extension and 2) Range of knee angle excursion (difference between maximum extension and flexion). These endpoints will be measured and compared between each control strategy within each task during the assessment visit. * To characterize controller behavior and performance, we will use the root mean square error (RMSE) between the exoskeleton knee torque profile delivered in real-time and the ideal knee torque profile computed from the user s kinematics. This endpoint will be measured during each assessment visit. Secondary Endpoints: -To evaluate functional performance in: * self-selected speed treadmill walking, overground walking, stairs, and ramps, we will use gait speed, stride length, and number of gait cycles. * variable-speed treadmill walking, we will use cadence, stride length, and number of gait cycles. * Timed Up and Go and stairs, we will use the duration of the task. * the Standardized Walking Obstacle Course, we will use the time to traverse the environment. * the 6-Minute Walk Test, we will use the distance covered during the task. * the squat test, we will use the number of squats completed. These endpoints will be measured and compared between each control strategy used within each task during the assessment visit. To characterize muscle activation, we will use 1) peak knee extensor activation during the task and 2) area under the normalized EMG curve over the duration of the task. These endpoints will be measured and compared between each control strategy used within each task during the assessment visit.