CAREER: Neuromuscular Coordination (NeuroCoord)-Guided Human-Machine Interaction for Quantifying and Improving Motor Function after Stroke

University Of Houston, Houston TX

Investigators

Abstract

Stroke is a leading cause of long-term disability in the U.S. It negatively impacts the upper extremity (UE) function. A significant need for effective stroke rehabilitation for the UE remains, owing to the increase in an aging population and stroke survival rates. This Faculty Early Career Development Program (CAREER) project aims to create an adaptive neuromuscular coordination (NeuroCoord)-guided human-machine interaction platform for stroke rehabilitation. The platform will enable researchers to make objective assessments of motor impairment with the brain, muscular, and force data measured in the arm. The study will also allow researchers to design a new, individualized rehabilitation model to improve motor function in the UE after stroke. Successful completion of the project will benefit UE motor function by facilitating movement control as intended. Also, research activities and outcomes will be integrated into education and outreach programs for students and local community members. The investigator’s long-term goal in research is to develop a transformative rehabilitation framework, NeuroCoord-guided adaptive stroke rehabilitation. The framework targets the activation of new intermuscular coordination patterns, through physical interaction with the interface enabling researchers to make objective, multi-modal assessments of motor impairment and design an individualized rehabilitation model for improving motor functions after neurological injuries. This CAREER project will create an adaptive NeuroCoord-guided human-machine interaction platform for automated quantification of motor impairment and design a novel exercise to improve UE motor function after stroke. The Research Plan includes two objectives to develop two important building blocks of the NeuroCoord framework for stroke UE rehabilitation: (1) development and evaluation of a human-machine interaction platform for multi-modal (brain, muscular, and kinetic activity) quantification of motor impairment post-stroke under isometric and several movement conditions and (2) altering abnormal intermuscular coordination by an adaptive NeuroCoord-guided rehabilitation exercise. The project will provide the scientific foundation for designing a novel human-machine interaction platform for stroke rehabilitation, originally motivated by neuromuscular control principles. This human-machine interaction platform is based on the innovative integration of advanced brain imaging technology, a novel rehabilitation robotic device, electromyography, and machine learning principles. The application of the platform has the potential to advance the field’s knowledge for developing automated motor assessment methods with multi-modal signals incorporating changes in cortical organization, muscle coordination, and biomechanical force coupling after the therapeutic exercise. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.