Recognition and decision-making algorithm in human locomotion based on the principles of fuzzy reasoning

The authors introduce a fuzzy rule-based algorithm to evaluate the activation patterns of muscles of the lower limb with respect to the gait phases during normal human walking. A relational matrix was established as a Cartesian product between the activation behaviors of muscles of the lower limb within the seven gait phases during normal walking. This relational matrix is an expression of the strength of association between the muscles and the gait phases. The resulting knowledge-base, therefore, depicts the relationship between the muscles in the respective gait phases during normal walking tasks. The cross-correlation between an input relational matrix and the knowledge base will provide a diagnostic assessment of the neurological state of the subject.