We are testing a new system for linking grants to scientists.
The funding information displayed below comes from the
NIH Research Portfolio Online Reporting Tools and the
NSF Award Database.
The grant data on this page is limited to grants awarded in the United States and is thus partial. It can nonetheless be used to understand how funding patterns influence mentorship networks and vice-versa, which has deep implications on how research is done.
You can help! If you notice any innacuracies, please
sign in and mark grants as correct or incorrect matches.
Sign in to see low-probability grants and correct any errors in linkage between grants and researchers.
High-probability grants
According to our matching algorithm, Craig P. McGowan is the likely recipient of the following grants.
Years |
Recipients |
Code |
Title / Keywords |
Matching score |
2006 — 2008 |
Mcgowan, Craig P |
F32Activity Code Description: To provide postdoctoral research training to individuals to broaden their scientific background and extend their potential for research in specified health-related areas. |
Individual Muscle Function in Human Walking @ University of Texas Austin
[unreadable] DESCRIPTION (provided by applicant): The goal of this project is to elucidate individual muscle function during human walking. Walking requires precise coordination of the neuromuscular and musculoskeletal systems. The complexity of these has made it difficult to determine the functional role of individual muscles. Understanding how individual muscles operate during normal healthy walking has important implications for understanding neuromuscular impairments and designing effective rehabilitation strategies. Specifically, this project seeks to achieve two aims; to determine the relative contribution of individual leg muscles to 1) body weight support and 2) forward propulsion during walking. To achieve these aims, a novel combination of experimental perturbation and detailed musculoskeletal modeling and computer simulation will be employed. Experimental designs will involve combinations of load carrying and applied forces to alter the external demand musculoskeletal system in a known way. Experimental data will incorporated in to the development of dynamic models and computer simulations matching the experimental conditions. Individual muscle function will be determined through electromyographic (EMG) analysis of experimental data and predictions from the simulations. [unreadable] [unreadable] [unreadable]
|
0.957 |