Damiano - Bulea - 2019

Functional and Applied Biomechanics Section, Rehabilitation Medicine Department
Mentor Name
Diane Damiano, Ph.D.
Thomas Bulea, Ph.D.
Mentor Telephone
(301) 451-7544
Laboratory And Project Description

Evaluating brain activity during functional tasks using noninvasive neuroimaging in healthy individuals and individuals with cerebral palsy

The primary focus of our research is to investigate mechanisms underlying normal and abnormal motor control and to design devices and/or interventions to improve motor function in children and adults with physical disabilities as a result of brain injuries. Our previous work has focused on the assessment and treatment of the peripheral consequences of brain injuries such as abnormal movement or muscle activation patterns. Our laboratory has a state-of-the-science motion capture system that precisely quantifies joint motion during walking or any motor task. This system can be integrated with surface electromyography (EMG) that provides information on which muscles are active and when. The development and refinement of technologies that can image the brain and record brain activity during functional tasks is a major advance in the fields of neurology and neuroscience. These technologies could provide new insights into mechanisms underlying movement disorders in children and adults with motor disorders. We utilize two non-invasive methods of assessing cortical activation patterns, electroencephalography (EEG) and Near Infrared Spectroscopy (NIRS) to record neuroimaging data that is synchronized with our biomechanics data. The primary goal of this project is to contribute to an ongoing study utilizing EEG in combination with motion capture and EMG to evaluate hand and arm function in children with cerebral palsy and a group of age-matched controls with typical development.  

This project will enable the student to:

  1. Learn the basics of 3D motion analysis with strong mentoring and assistance from a highly qualified group of scientists/engineers.
  2. Assist in clinical experiments involving collection of EEG, EMG, and motion capture data during performance of a range of reaching and grasping tasks.
  3. Learn and apply signal processing techniques to evaluate differences in cortical activity and biomechanical performance of the upper extremity tasks across subject groups.

The student will have the added advantage of being in an active laboratory that is exploring different types of movement pathologies, utilizing novel motion and balance assessments including virtual reality applications and muscle and joint imaging techniques, and conducting robotic development and testing for rehabilitation applications. We are located within the Clinical Center which is the world’s largest research hospital in the middle of the NIH campus.