Can you build a minimally-actuated exo-robot as a wearable orthosis? Maybe one that is most simply built out of springs? It may not do everything, but what can you do? The secret is to allow networks of springs, and structural optimization algorithm that tells us how to build it.

Is it possible to use a network of springs to make up for what the muscles do during walking and hence assist gait? This study shows the potential of the ExoNET device to reproduce the torques generated by your muscles while you walk. We feel that this structural design can guide devices in the future and may lead to clinical tools that are lightweight, unintimidating, easy to use, and inexpensive.

Can you build a soft, exo-robot as a wearable orthosis to provide assistance during both rehabilitation and activities of daily living? Can this same device also be used as a therapeutic device by tuning to anti-assistance mode, providing more meaningful therapy to the user?

Body Computer Interface (BCI) is the idea that one can control a robot simply by thinking about it. In this study, we are laying the groundwork for further BCI and robotic development for individuals to control a hand opening device called the Electro encephalographic mediated glove (or Eglove) using an EEG cap connected to a motorized glove.

Sensory inputs such as vision, proprioception, and touch play a crucial role in post-stroke recovery. Our research delves into how these sensory contributions can be assessed to develop effective, personalized therapy strategies. Enhancing and tailoring sensory inputs to an individual’s needs allows us to explore how learning outcomes can be improved and errors reduced. Through synthetic simulations that combine muscular, visual, and proprioceptive inputs, we aim to understand better the complex processes involved in motor learning.

True behavioral restitution, a return to normal motor patterns with the affected limb post-stroke, requires the recruitment and restoration of the residual ipsilesional hemisphere/corticospinal tract (CST). Following stroke, the spontaneous recovery mechanism selectively and continuously uses a more optimized neural network for motor execution, depending on the degree of CST damage.

Stroke survivors vary greatly in their motor deficits and rehabilitative needs. Here, we gather unstructured upper limb movement data and seek to understand if there are patterns in their kinetics that reflect the underlying neuromuscular alterations. In doing so, we can improve our abilities to evaluate patients and design personalized rehab therapy.

This study utilizes a wearable data glove system that translates hand movements into signals that control a cursor on a screen. We examined how participants learn a redundant novel task, which can be completed through various solutions.

Women’s Health & Fitness Day is celebrated every year to promote the importance of health awareness and physical activity in women. In recognition, here is a roundup of articles about pelvic floor health, exercise, bone density and more by Shirley Ryan AbilityLab’s women’s health experts.

Megan lived with chronic pain for over 20 years. She participated in our four-week pain program to learn strategies and techniques to help navigate daily pain.

If you are looking to improve your running technique or performance, return to running following an injury or prevent injury, a visit to Shirley Ryan AbilityLab’s Running Performance Clinic may be the next step for you.