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Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Knowledge discovery in databases of biomechanical variables: application to the sit to stand motor task | Journal of NeuroEngineering and Rehabilitation BioMed Central Research Open Access Knowledge discovery in databases of biomechanical variables application to the sit to stand motor task Giuseppe Vannozzi 1 Ugo Della Croce2 Antonina Starita3 Francesco Benvenuti4 and Aurelio Cappozzo1 Address department of Human Movement and Sport Sciences University Institute for Movement Science Roma department of Biomedical Sciences University of Sassari Sassari Italy department of Informatics University of Pisa Pisa Italy and department of Rehabilitation AUSL 11 San Miniato Pisa Italy Email Giuseppe Vannozzi - vannozzi@iusm.it Ugo Della Croce - dellacroce@uniss.it Antonina Starita - starita@di.unipi.it Francesco Benvenuti - f.benvenuti@usl11.tos.it Aurelio Cappozzo - cappozzo@iusm.it Corresponding author Published 29 October 2004 Received 30 August 2004 Journal of NeuroEngineering and Rehabilitation 2004 1 7 doi 10.1186 1743-0003-1-7 Accepted 29 October 2004 This article is available from http www.jneuroengrehab.com content 1 1 7 2004 Vannozzi et al licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License http creativecommons.org licenses by 2.0 which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract Background The interpretation of data obtained in a movement analysis laboratory is a crucial issue in clinical contexts. Collection of such data in large databases might encourage the use of modern techniques of data mining to discover additional knowledge with automated methods. In order to maximise the size of the database simple and low-cost experimental set-ups are preferable. The aim of this study was to extract knowledge inherent in the sit-to-stand task as performed by healthy adults by searching relationships among measured and estimated biomechanical quantities. An automated method was applied to a large amount of data stored .
