Department of Software Technology
Vienna University of Technology
Experiments in Gait Pattern Classification with Neural Networks of Adaptive Architecture
Clinical gait analysis is an area aiming at the provision of support for
diagnoses and therapy considerations, the development of bio-feedback
systems, and the recognition of effects of multiple diseases and still
active compensation patterns during the healing process.
The data recorded with ground reaction force measurement platforms is a
convenient starting point for gait analysis.
We discuss the usage of raw data from such measurement platforms for gait
analysis and show how unsupervised artificial neural networks may be
employed for gait malfunction identification.
In this paper we provide our latest results in this line of research
by using Incremental Grid Growing and Growing Grid
networks for gait pattern classification.
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Comments: rauber@ifs.tuwien.ac.at