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There have been significant advances in the technologies for robot-assisted lower-limb rehabilitation in the last decade. However, the development of similar systems for children has been slow despite the fact that children with conditions such as cerebral palsy (CP), spina bifida (SB) and spinal cord injury (SCI) can benefit greatly from these technologies. Robotic assisted gait therapy (RAGT) has emerged as a way to increase gait training duration and intensity while decreasing the risk of injury to therapists. Robotic walking devices can be coupled with motion sensing, electromyography (EMG), scalp electroencephalography (EEG) or other noninvasive methods of acquiring information about the user’s intent to design Brain-Computer Interfaces (BCI) for neuromuscular rehabilitation and control of powered exoskeletons. For users with SCI, BCIs could provide a method of overground mobility closer to the natural process of the brain controlling the body’s movement during walking than mobility by wheelchair. For adults there are currently four FDA approved lower-limb exoskeletons that could be incorporated into such a BCI system, but there are no similar devices specifically designed for children, who present additional physical, neurological and cognitive developmental challenges. The current state of the art for pediatric RAGT relies on large clinical devices with high costs that limit accessibility. This can reduce the amount of therapy a child receives and slow rehabilitation progress. In many cases, lack of gait training can result in a reduction in the mobility, independence and overall quality of life for children with lower-limb disabilities. Thus, it is imperative to facilitate and accelerate the development of pediatric technologies for gait rehabilitation, including their regulatory path. In this paper an overview of the U.S. Food and Drug Administration (FDA) clearance/approval process is presented. An example device has been used to navigate important questions facing device developers focused on providing lower limb rehabilitation to children in home-based or other settings beyond the clinic. 

Neural decoding of human locomotion, including automated gait intention detection and continuous decoding of lower limb joint angles, has been of great interest in the field of Brain Machine Interface (BMI). However, neural decoding of gait in developing children has yet to be demonstrated. In this study, we collected physiological data (electroencephalography (EEG), electromyography (EMG)), and kinematic data from children performing different locomotion tasks. We also developed a state space estimation model to decode lower limb joint angles from scalp EEG. Fluctuations in the amplitude of slow cortical potentials of EEG in the delta band (0.1 – 3 Hz) were used for prediction. The decoding accuracies (Pearson’s r values) were promising (Hip: 0.71; Knee: 0.59; Ankle: 0.51). Our results demonstrate the feasibility of neural decoding of children walking and have implications for the development of a real-time closed-loop BMI system for the control of a pediatric exoskeleton. 

Powered exoskeletons for gait rehabilitation and mobility assistance are currently available for the adult population and hold great promise for children with mobility limiting conditions. Described here is the development and key features of a modular, lightweight and customizable powered exoskeleton for assist-as-needed overground walking and gait rehabilitation. The pediatric lower-extremity gait system (PLEGS) exoskeleton contains bilaterally active hip, knee and ankle joints and assist-as-needed shared control for young children with lower-limb disabilities such as those present in the Cerebral Palsy, Spina Bifida and Spinal Cord Injured populations. The system is comprised of six joint control modules, one at each hip, knee and ankle joint. The joint control module, features an actuator and motor driver, microcontroller, torque sensor to enable assist-as-needed control, inertial measurement unit and system monitoring sensors. Bench-testing results for the proposed joint control module are also presented and discussed.