# Modulation of gait dynamics post-stroke > **NIH NIH F32** · EMORY UNIVERSITY · 2024 · $81,306 ## Abstract PROJECT SUMMARY/ABSTRACT My career goal is to improve the personalization of stroke gait rehabilitation and develop novel rehabilitation technologies using neuromechanics-based data-driven modeling in conjunction with hypothesis-driven experimental design. The proposed research aims to understand how neural constraints impact stroke survivors’ ability to coordinate execution-level joint dynamics to flexibly modulate whole-body center-of-mass (COM) dynamics between slow inverted pendulum and fast spring-mass dynamics during walking; a task critical to achieving stable, efficient, and rapid movement. My preliminary data in a single individual suggest that COM dynamics are asymmetric post-stroke, but further characterization of joint coordination and COM dynamics is needed to understand their relationship with interindividual and inter-limb differences in post-stroke walking function and treatment responses. Two major methodological barriers to characterizing these relationships are a lack of 1) metrics and techniques to encode complex, individual-specific gait dynamics post-stroke, and 2) long time-series datasets containing diverse movement patterns needed to test neuromechanical hypotheses about gait. To address these challenges, I will work with Sponsor Ting and Co-Sponsor Berman to extend data- driven techniques developed in my doctoral research to identify COM dynamics and characterize their relationships to joint dynamics; with Sponsor Ting and Co-Sponsor Kesar I will design and collect new datasets from stroke survivors of diverse movement patterns using biofeedback during walking. Aim 1: Test whether interindividual and inter-limb differences in COM dynamics post-stroke are associated with walking speed. I will evaluate the similarity of baseline post-stroke COM dynamics to able-bodied (AB) adults and between paretic and non-paretic limbs. Further, I will examine whether the paretic-limb transitions from inverted pendulum to spring-mass dynamics at faster treadmill speeds, decreasing asymmetry in COM dynamics. Aim 2: Characterize reductions in stroke survivors’ ability to modulate joint dynamics to achieve desired COM dynamics. Using visual biofeedback to prescribe COM dynamics, I will test whether stroke survivors have reduced ability to emulate COM dynamics compared to AB adults and determine if joint dynamics characterize COM dynamics less accurately in stroke survivors than AB adults. Aim 3: Test whether sub-groups of individuals with similar COM and joint dynamics predict biofeedback responses more accurately than discrete metrics. I will test whether, across a range of biofeedback-prescribed COM dynamics, baseline COM and joint dynamics can classify changes in joint dynamics with biofeedback more accurately than discrete clinical or biomechanical variables. I will also have training in clinical trials by participating in Sponsor Kesar’s ongoing gait rehabilitation study. The proposed research and training will complement my doctoral s... ## Key facts - **NIH application ID:** 10835086 - **Project number:** 5F32HD108927-03 - **Recipient organization:** EMORY UNIVERSITY - **Principal Investigator:** Michael Charles Rosenberg - **Activity code:** F32 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $81,306 - **Award type:** 5 - **Project period:** 2022-06-01 → 2025-05-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10835086 ## Citation > US National Institutes of Health, RePORTER application 10835086, Modulation of gait dynamics post-stroke (5F32HD108927-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10835086. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*