11/21/2025
By Visalakshi Chockalingam

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."

Date: Wednesday, December 10, 2025
Time: 9.30 – 10.30 a.m.
Location: Falmouth 302 Conference Room and via Teams
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Committee:

  • Lara Thompson, Professor of Biomedical Engineering, UMass Lowell (Advisor and Chair)
  • Walfre Franco, Associate Professor and Chair of Biomedical Engineering, UMass Lowell
  • Yi-Ning Wu, Associate Professor of Physical Therapy and Kinesiology, 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 via muscle synergy analyses and inverse dynamics.

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. Conventional clinical assessments, including the Sport Concussion Assessment Tool-5th edition (SCAT5), 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. Here, the level of damage due to the concussion will be quantified via subjective clinical tools, as well as through eye-tracking via the VR headset (a new, but objective, method) a quantitative assessment tool, providing precise measures of gaze and visual attention. Surface electromyography (sEMG), motion capture, and forceplate data will be collected 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 (NMF), 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, as well as eye movement information, 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.