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GRACE: Geriatric Research in Ambulatory and Cognitive Excellence

Themes People Videos Talks Sponsors Publications Bibliography

Status: Completed

The GRACE program (http://collab.sam.pitt.edu/dev/grace) aims to connect neurological aging with mobility impairment in older adults through medical imaging, mathematical analysis and computational tools. The program goals are to: 1) Implement efficient automated procedures for correlating multiple mobility factors with cognitive measurements, 2) Develop new practical regression algorithms capable of handling very large databases of measurements, 3) Design novel visual paradigms for effective mining and communication of multidimensional and multicomponent correlations between observed ambulatory characteristics and cognitive measurements. GRACE connects in this effort the University of Pittsburgh Departments of Computer Science, Epidemiology, Mathematics and the Center for Simulation and Modeling.


Visual Exploration and Analysis
Biomedical Imaging and Visualization


Howard Aizenstein
Robert Boudreau
William Layton
Sriranjani Mandayam
Liz Marai
Adrian Maries
Caterina Rosano
Kim Wong
S. Levent Yilmaz


University of Pittsburgh Research Council's Multidisciplinary Small Grant Program (Grace)

NSF CAREER IIS-0952720 *old* (Tracking, Computational Modeling and Interdisciplinary Edu)

NSF CAREER IIS-1541277 *new* (Tracking, Computational Modeling and Interdisciplinary Edu)


Brain Gait Correlation
Brain/Gait Program - Brodmann Areas
Brain/Gait Program - AAL Atlas
GRACE: Geriatric Research in Ambulatory and Cognitive Excellence (SciVis\'13)
Grace 30 second pitch



GRACE - Visualization Brain/Gait October 2009
GRACE - a Numerical Analysis
Brain Gait Correlation





G.E. Marai, "Visual Scaffolding in Integrated Spatial and Nonspatial Visual Analysis", The Sixth International Eurovis workshop on Visual Analytics EuroVA’15, pp. 1--5, 2015. (pdf) (bibtex: Marai-2015-VSI).


N. Mays, C. Rosano, H.J. Aizenstein, R. Boudreau, G.E. Marai, A. Maries, W.J. Layton, F. Thomas, K. Yaffe, L.J. Launer. A.B. Newman, "Using iterated Tikhonov regularization with the L-curve method to Quantify the Correlation Between Neuroimaging and Gait Data", Journal of Computer Math, Vol. 0(0), pp. 1--27, 2014. In Review. (pdf) (bibtex: Mays-2014-UIT).


A. Maries, N. Mays, M. Olson Hunt, K.F. Wong, W. Layton, R. Boudreau, C. Rosano, G.E. Marai, "GRACE: A Visual Comparison Framework for Integrated Spatial and Non-Spatial Geriatric Data", IEEE Transactions on Visualization and Computer Graphics (Proceedings Scientific Visualization 2013), Vol. 19(12), pp. 1--10, Dec 2013. (pdf) (bibtex: Maries-2013-GAV).


A. Maries, S. Mandayam, C. Rosano, G.E. Marai, "Visual Analysis of Brain/Gait Correlations", IEEE Visualization 2011, Poster Abstracts with System Demonstration, pp. 1--2, 2011. (pdf) (bibtex: Maries-2011-VAO).