|
Abstract
|
|
|---|---|
| The medical diagnosis system described in this chapter uses underlying knowledge in the isokinetics domain, gathered by combining the expertise of a physician specialized in isokinetics techniques and data mining techniques applied to a set of existing data. An isokinetics machine is basically a physical support on which patients exercise one of their joints, in this case the knee, according to different ranges of movement and at a constant speed. The data on muscle strength supplied by the machine are processed by an expert system that has built-in knowledge elicited from an expert in isokinetics. It cleans and pre-processes the data and conducts an intelligent analysis of the parameters and morphology of the isokinetics curves. Data mining methods based on the discovery of sequential patterns, which identify similarities and differences among exercises, were applied to the processed information to characterize injuries and discover populationspecific reference patterns. The results achieved by this system were validated against an expert and a novice physiotherapist. We found that the system and the expert made a similar number of mistakes and much fewer than the novice. The results were applied to an environment for elite athletes. | |
|
International
|
Si |
|
|
|
|
Book Edition
|
0 |
|
Book Publishing
|
Nova Science Publishers, Inc. |
|
ISBN
|
9781600216886 |
|
Series
|
0 |
|
Book title
|
Systems Research Trends |
|
From page
|
113 |
|
To page
|
137 |