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Exoskeletons have the potential to improve outcomes for rehabilitation clients. For these devices to be effective, rehabilitation professionals and end users must be involved throughout the design process, so the devices meet the broad needs of users. In this article, we present a model to guide the design of rehabilitation devices. This model is user-centered and focuses on users’ functional, expressive, aesthetic, and accessibility needs (FEA2) for devices.We then summarize the results of the first studies evaluating the feasibility and effectiveness of the Playskin Lift soft exoskeleton for pediatric populations utilized for intervention in the natural environment. The exoskeleton was feasible for daily use by families in the natural environment. For infants and toddlers with physical disabilities, the exoskeleton assisted reaching and play performance within a single session when it was worn and improved independent reaching function and play activity after months of daily intervention with the exoskeleton. 

Textile pneumatic actuators were developed to provide full assistance to lift the arm of a model of an 11-year-old male beyond 120 degrees of shoulder abduction. Two fabrics and a variety of sealing techniques, methods of attachment, and actuator shapes were comparatively evaluated using textile and functional tests. The results identified that both fabrics and one of the three sealing techniques were effective for creating air-tight, functional actuators. Actuators were more effective when the bands attaching them were closer to the axilla. Rectangular and wing-shaped actuators, both lifting the model of an 11-year-old male’s arm above 120 degrees of abduction, were more effective than Y-shaped actuators. Multiple designs and materials may be acceptable for building textile pneumatic actuators to lift the full weight of a child’s arm. Compared to traditional hard robots, soft assistive robots offer key potential benefits related to comfort, aesthetics, weight, bulk, and cost. 

Many children have an upper extremity disability leaving them unable to explore the environment around them. Hard exoskeletons can provide support to lift a child’s arms up against gravity, but these devices are generally large and obtrusive leading to low adherence. Children often prefer to have limited arm function rather than wearing such a device. Our lab has previously designed a passive soft exoskeleton to lift children’s arms, but this did not allow for user control and was limited in the length and weight of arm it could support. Building off of this research, we have created the preliminary design for a user-controlled pneumatic soft exoskeleton that may allow users to independently raise and lower their arms. 

Differential privacy has emerged as a popular model to provably limit privacy risks associated with a given data release. However releasing high dimensional synthetic data under differential privacy remains a challenging problem. In this paper, we study the problem of releasing synthetic data in the form of a high dimensional histogram under the constraint of differential privacy.We develop an $(\epsilon, \delta)$-differentially private categorical data synthesizer called \emph{Stability Based Hashed Gibbs Sampler} (SBHG). SBHG works by combining a stability based sparse histogram estimation algorithm with Gibbs sampling and feature selection to approximate the empirical joint distribution of a discrete dataset. SBHG offers a competitive alternative to state-of-the art synthetic data generators while preserving the sparsity structure of the original dataset, which leads to improved statistical utility as illustrated on simulated data. Finally, to study the utility of the resulting synthetic data sets generated by SBHG, we also perform logistic regression using the synthetic datasets and compare the classification accuracy with those from using the original dataset.