Fast subsequence matching in time-series databases
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Discovering similar patterns in time series
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient Similarity Search In Sequence Databases
FODO '93 Proceedings of the 4th International Conference on Foundations of Data Organization and Algorithms
Analysis of Strength Data Based on Expert Knowledge
ISMDA '01 Proceedings of the Second International Symposium on Medical Data Analysis
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In this paper we describe the process of discovering underlying knowledge in a set of isokinetic tests (continuous time series) using data mining techniques. The methods used are based on the discovery of sequential patterns in time series and the search for similarities and differences among exercises. They were applied to the processed information in order to characterise injuries and discover reference models specific to populations. The discovered knowledge was evaluated against the expertise of a physician specialised in isokinetic techniques and applied in the I4 project (Intelligent Interpretation of Isokinetic Information).