DETERMINATION OF HUMAN GAIT PHASE BY ZERO‐MOMENT POINT

This paper discuss approach to gait phase determination via fuzzy inference. The stability criteria applied to biped robots, namely Zero Moment Point (ZMP) have been employed. Designed fuzzy inference system uses data about the ZMP position. Gait phase is the output of our fuzzy system. Simplified human body model is introduced for computation of ZMP. Both inter- and intra-subject phase identification are examined. The developed fuzzy-rules based system is exemplified to show capability of different subjects gait data generalization. Results of designed fuzzy IF-THEN rules based system show that the proposed method is suitable for this type of task. We designed system to identify gait phases, which could potentially help to assess the quality of walking. Although the method for studying ZMP in combination with fuzzy logic could contribute to the design of new prosthesis and the diagnosis of disorders, this issue has not been systematically studied in the past.