@inproceedings{05906a6229ee473a897a60dbaeeb8fd4,
title = "Improving the efficacy of motion analysis as a clinical tool through artificial intelligence techniques",
abstract = "Technology supporting human motion analysis has advanced dramatically and yet its clinical application has not grown at the same pace. The issue of its clinical value is related to the length of time it takes to do an interpretation, the cost, and the quality of the interpretation. Techniques from artificial intelligence such as neural networks and knowledge-based systems can help overcome these limitations. Here, the authors give an overview of these techniques and describe current research efforts that apply these techniques in the field of human motion analysis.",
keywords = "Gait analysis, artificial intelligence, clinical application, decision support, motion analysis, multimedia, neural network",
author = "S. Simon and K. Johnson",
note = "Publisher Copyright: {\textcopyright} 2000 IEEE.; 22nd Annual International Conference on Shriners Pediatric Workshop/Symposium: A New Millennium of Discovery in Clinical Care and Motion Analysis Technology ; Conference date: 23-07-2000 Through 28-07-2000",
year = "2000",
doi = "10.1109/PG.2000.858871",
language = "English",
series = "Pediatric Gait: A New Millennium in Clinical Care and Motion Analysis Technology",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "23--29",
editor = "Harris, \{Gerald F.\} and Smith, \{Peter A.\}",
booktitle = "Pediatric Gait",
address = "United States",
}