Rehabilitation Engineering Research Center (RERC)

RERC Scientists Advance New Approaches for Neurological Recovery

Through coordinated advances in robotics, computational modeling, and neuromodulation, scientists in the RERC are advancing next-generation rehabilitation technologies. This federally funded program targets people who have experienced stroke, spinal cord injury, and multiple sclerosis.

By unlocking new levels of ambulation and functional freedom, our RERC research aims to help clinicians translate engineering advances into practical therapies that improve patient outcomes and enhance quality of life.

Activating Neural Pathways

These approaches increase brain and spinal cord excitability and act directly on the nervous system using advanced rehabilitation technologies, including wearable robotics, brain stimulation, and spinal stimulation.

Strengthening Brain-Body Communication

The goal is to strengthen communication between the brain, spinal cord, and muscles to improve walking ability, balance, and greater functional independence for individuals with neuromuscular impairments.

Targeting Specific Populations

Our work targets people who have experienced stroke, spinal cord injury, or multiple sclerosis. The research translates engineering innovation into practical rehabilitation strategies that support daily mobility and long-term recovery.

RERC research studies how robotics, brain stimulation, and user feedback can work together to improve walking, balance, and mobility after neurological injury while helping tailor rehabilitation technologies to individual patient needs.

Quiana Drummond study participant wearing the Wandercraft exoskeleton

Prescription of Robotic Exoskeletons to Patient-Specific Needs

This study compares several robotic exoskeletons used for gait training after stroke to determine how different device features match individual patient needs. Over more than 15 visits across six weeks, participants take part in structured walking sessions while researchers evaluate changes in their functional performance. The findings will guide clinicians in prescribing robotic exoskeletons and help tailor rehabilitation strategies to support walking recovery after stroke. Principal investigators: Karen Nolan, PhD, and Kiran Karunakaran, PhD .

Researcher and participant during a study session using brain stimulation equitment.

Combining Brain Stimulation with Robotic Balance Training

This clinical trial tests whether noninvasive brain stimulation can enhance robotic balance training after stroke. Researchers use each participant’s MRI to personalize stimulation targets and EEG to measure changes in brain activity during therapy. Over four months and 21 visits, participants complete structured training while scientists evaluate improvements in balance control and neural function. Principal investigator: Vikram Shenoy, PhD.

Healthy aging adults looking at keyboard

User and Clinician Experiences with Rehab Technology

This project gathers feedback from participants and clinicians involved in Kessler Foundation RERC studies. Through focus groups, researchers explore the benefits, limitations, and practical challenges of rehabilitation technologies designed to support walking and mobility. The insights help identify what works, what needs improvement, and how innovative technologies can better fit clinical workflows and user needs. Principal investigator: Peter Barrance, PhD.

The RERC’s development projects advance next-generation rehabilitation technologies prior to clinical research. Our scientists assess devices, algorithms, and stimulation systems to improve function and responsiveness to individual needs, preparing the next generation of tools.

Advancing Noninvasive Spinal Stimulation for Walking

Scientists are developing a multi-channel transcutaneous spinal stimulation system designed to improve walking in people with spinal cord injury. The device delivers targeted electrical stimulation through the skin to activate spinal networks involved in stepping. By expanding stimulation flexibility and precision, this technology aims to support functional ambulation while remaining noninvasive and clinically adaptable. Principal investigators: Gail Forrest, PhD, Susan Harkema, PhD, Peter Barrance, PhD, and Richard Foulds, PhD (NJIT).

AI- and Reinforcement-Learning for Exoskeleton Control in MS

This project uses artificial intelligence and deep reinforcement learning to create personalized control systems for lower-extremity robotic exoskeletons in people with multiple sclerosis. By continuously learning from an individual’s movement patterns, the controller adapts assistance in real time. The goal is smoother, more responsive robotic walking support that reflects disease variability and improves comfort, efficiency, and functional mobility. Principal investigators: Ghaith Androwis, PhD, Easter Selvan, PhD, and Alex Zhou, PhD (NJIT).

Study Spotlight

Epidural Spinal Cord Stimulation: Addressing Spasticity and Motor Function

This study aims to expand the knowledge and capacity for neuromodulation to improve the debilitating effects of severe spasticity (spasms, tonic muscle activity and/or clonus) in persons with spinal cord injury.

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