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Identification of sensory-motor control in reaching
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.
嫩B研究院 Project
Altering Post-Stroke Motor Recovery
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.
嫩B研究院 Project
Shirley Ryan 嫩B研究院 Psychologist Featured in PBS Next Avenue Story about Chronic Pain
Next Avenue, a digital PBS publication, recently featured Shirley Ryan 嫩B研究院 clinical psychologist?Claire Pedersen, PsyD, in a story about the?connection between chronic pain and anger — and how anger can have an impact on the perception, intensity and frequency of pain.
News
Forearm ExoNET
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?
嫩B研究院 Project
Eglove
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.
嫩B研究院 Project
Developing probability distribution models from upper extremity free exploration trials to evaluate motor deficits in stroke patients
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.
嫩B研究院 Project
Visual Feedback of Kinematic Chain in a Redundant Novel Task
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.
嫩B研究院 Project
Multimodal Haptic Feedback for Plantar Sensory Substitution
The purpose of this study is to test the use of a system that can read the pressure pattern on the foot and “map” that pattern to another part of the body (i.e., legs, arms, or back).
嫩B研究院 Project
A Guide to Rock Climbing After a Long Break
Rock climbing is a rigorous sport that is very demanding on the whole body. From the fingertips to the toes, large forces are constantly being placed on small structures, which can create a potential for injury.
Blog
Locomotor Function Following Transcutaneous Electrical Spinal Cord Stimulation in Individuals with Hemiplegic Stroke
Despite advances in stroke rehabilitation, more than two-thirds of the 7 million stroke survivors in the U.S. still struggle to walk independently in their communities. Most current therapies focus on stimulating the brain areas that control leg movement, yet many stroke survivors continue to face issues like poor coordination, spasticity, and muscle weakness. We propose a different approach—using electrical stimulation of the spinal cord to improve walking after stroke.
嫩B研究院 Project
Sensor Technology Applied in Rehabilitation for Stroke (STARS)
The goal of the STARS project is to develop machine-learning algorithms that quantify impairments and function that impact gait and balance, using datasets obtained from advanced wearable sensors in individuals with stroke.
嫩B研究院 Project
TrayBall: Using LookingGlass
This system is a very straightforward use of the looking glass display system combined with a tracking device called the Leap? tracking device. It tells the computer where your hands are, and then we ask the patient to do a bimanual task to move a virtual tray to different locations in space without letting a ball roll off.
嫩B研究院 Project