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Analysis on Relation between Rehabilitation Training Movement and Muscle Activation using Weighted Association Rule Discovery  

Lee, Ah-Reum (Department of Healthcare Engineering, Graduate School, Chonbuk National University)
Piao, Youn-Jun (Chonbuk National University Automobile parts & mold technology Innovation Center, CATIC)
Kwon, Tae-Kyu (Center for healthcare technology development)
Kim, Jung-Ja (Division of Biomedical Engineering, Chonbuk National University)
Publication Information
Abstract
The precise analysis of exercise data for designing an effective rehabilitation system is very important as a feedback for planing the next exercising step. Many subjective and reliable research outcomes that were obtained by analysis and evaluation for the human motor ability by various methods of biomechanical experiments have been introduced. Most of them include quantitative analysis based on basic statistical methods, which are not practical enough for application to real clinical problems. In this situation, data mining technology can be a promising approach for clinical decision support system by discovering meaningful hidden rules and patterns from large volume of data obtained from the problem domain. In this research, in order to find relational rules between posture training type and muscle activation pattern, we investigated an application of the WAR(Weishted Association Rule) to the biomechanical data obtained mainly for evaluation of postural control ability. The discovered rules can be used as a quantitative prior knowledge for expert's decision making for rehabilitation plan. The discovered rules can be used as a more qualitative and useful priori knowledge for the rehabilitation and clinical expert's decision-making, and as a index for planning an optimal rehabilitation exercise model for a patient.
Keywords
Data mining; Weighted association rule discovery; Postral control; Rehabilitation training;
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