The REIGN Lab’s research is focused on understanding the mechanisms of neuromuscular coordination in neurologically intact and impaired individuals (esp. stroke) and translating resultant scientific findings into developing novel neurorehabilitation strategies. We also assess the effects of the rehabilitation methods by using multi-modal approaches including brain imaging. Our multi-faceted work uses rehabilitation robotics, brain stimulation and neuromodulation, and electromyographic and kinematic quantification. We often collaborate with engineers, neuroscientists, and clinicians because of the multidisciplinary nature of the work. Below are the major research areas in the REIGN lab:



Developing myoelectric signal-guided neurorehabilitation strategies to improve motor function after stroke

The goal of stroke rehabilitation is to induce favorable neuroplasticity to improve patient movement function. At least two approaches can be used to achieve the goal. The first approach focuses on changing the patient’s kinematic coordination with the hope of beneficial changes in the patient’s neuromuscular coordination (e.g., “task-specific training” paradigm focusing on achieving desired kinematic trajectory). However, the second approach is more consistent with the assumption that if a patient’s neuromuscular coordination (i.e., the cause) can be normalized, then the patient’s kinematic coordination (i.e., the consequence) will be improved as well. We develop an adaptive, myoelectric signal-guided rehabilitative exercise platform, which aims to correct the composition of altered intermuscular coordination similar to normal in stroke to improve motor function in the human upper extremity.


Examining the effects of operant conditioning of motor evoked potential on intermuscular coordination after stroke

Stroke often leads to abnormal muscle coordination and impaired motor function of the upper extremity (UE), which affects the quality of life in people post-stroke. Decreased corticospinal excitability and connectivity after stroke, as well as disturbed supraspinal connections, result in three major UE motor impairments: muscle weakness, spasticity, and impaired intermuscular coordination including wrist control, which lead to movement disabilities. Currently available therapies aim to treat the former two, but relatively little has been done to improve intermuscular coordination. Thus, developing an intervention that improves corticospinal excitability and intermuscular coordination in the affected limb can enhance UE motor function recovery after stroke. Operant conditioning of a stimulus-triggered muscle response, which produces targeted plasticity in the targeted pathway AND produces wider beneficial plasticity in multiple spinal/supraspinal pathways, could be one of such methods. We explore the cortical representation of muscle coordination and examine the effects of operant conditioning of motor evoked potential on intermuscular coordination in the upper extremity after stroke.



Programming Console

Developing automatized quantification of motor impairment after stroke by using rehabilitation robotics

Neurorehabilitation would be enhanced by innovation in the objectivemeasurements of motor impairment. Functional motor assessment is an essential part of rehabilitation protocols after stroke. The conventional assessment of motor impairment in the upper extremity relies heavily on the observation of selected movements(or tasks) by a trained clinical specialist. The examples are the Brunnstrom recovery stage, FMA, and modified Ashworth scale. Even though this estimation intends to be repeatable (intra-operator) andobjective (inter-operator), the nature of visual inspection includes some degree of uncertainty due to subjectivity. The subjectivity may come from a variety of sources (ex. movement variability). Thus, there is significant interest in developing automated, computer-aided systems to achieve objective, quantitative motor impairment assessments. We develop automatized quantification of motor impairment by using rehabilitation robotics.