03/19/2026
By Danielle Fretwell

The Francis College of Engineering, Department of Biomedical Engineering, invites you to attend a Doctoral Dissertation Proposal defense by Visalakshi Chockalingam on: "Neuromuscular Coordination and Posture Control in Concussed Athletes."

Candidate Name: Visalakshi Chockalingam
Degree: Doctoral
Defense Date: Thursday, March 26, 2026
Time: 11 a.m. - noon
Location: Falmouth 302

Committee:

  • Advisor: Lara Thompson, Ph.D., Professor of Biomedical Engineering, UMass Lowell
  • Walfre Franco, Ph.D., Associate Professor of Biomedical Engineering and Departmental Chair, UMass Lowell
  • Richard Nuckols, Ph.D., Assistant Professor of Mechanical & Industrial Engineering, UMass Lowell

Abstract:
Concussions are common in high-impact sports, such as ice hockey and soccer, often leading to motor control and balance impairments that can persist beyond acute, clinical recovery. Here, my proposed thesis research will investigate the effects of concussion on the neural control of movement predominantly via muscle synergy analyses.

Muscle synergies represent the coordinated activation of multiple muscles, by the central nervous system (CNS), to simplify motor control. By examining muscle synergies, my proposed research aims to identify characteristic patterns of postural and locomotor dysfunction following concussion. Athletes with and without a concussion history will perform standing (Aim 1), walking (Aim 2), and virtual reality (VR)-based balance tasks (Aim 3) that progressively increase in challenging their sensory systems. Here, the effects of damage due to the concussion will be quantified via subjective clinical tools, objective measures (tied to kinetics and kinematics). Conventional clinical assessments, intake form, the Balance Error Scoring System (BESS), and the Timed Up and Go test (TUG), rely on subjective scoring and may not capture underlying neuromuscular coordination deficits. Surface electromyography (sEMG), motion capture, and a forceplate will be used to collect data during standing and walking to quantify muscle activity, joint kinematics, and postural stability. Muscle synergy structures and activation timing will be extracted using non-negative matrix factorization (NNMF), providing insight into how neuromuscular coordination is organized and adapted. In addition, inverse muscle dynamics analyses will provide an estimation of internal joint torques and muscle forces, further linking observed movements to underlying biomechanical demands, and thus revealing compensatory strategies following concussion. Taken together, muscle synergy and inverse dynamics data enable a comprehensive characterization of sensorimotor coordination and multisensory integration deficits following concussion.

This research will generate objective, quantitative biomarkers of motor control integration in concussed athletes. Findings are expected to improve the sensitivity of concussion assessment, inform individualized rehabilitation strategies, and advance understanding of neural and biomechanical mechanisms underlying post-concussive motor deficits. Overall, the project aims have the potential to provide data-driven metrics to enhance athlete care and support recovery monitoring beyond currently used, conventional clinical assessments.