Fuzzy-logic-based hybrid locomotion mode classification for an active pelvis orthosis: Preliminary results

• Published in: 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) Vol. 2015; pp. 3893 - 3896
• Main Authors: Kebin Yuan, Parri, Andrea, Tingfang Yan, Long Wang, Munih, Marko, Vitiello, Nicola, Qining Wang
• Format: Conference Proceeding Journal Article
• Language: English
• Published: United States IEEE 01.01.2015
• Subjects: Accuracy; Delays; Foot; Fuzzy Logic; Hip; Hip Joint - physiology; Humans; Joints; Leg - physiology; Legged locomotion; Locomotion; Orthotic Devices; Pelvis - physiology; Walking
• ISSN: 1094-687X; 1557-170X
• DOI: 10.1109/EMBC.2015.7319244

In this paper, we present a fuzzy-logic-based hybrid locomotion mode classification method for an active pelvis orthosis. Locomotion information measured by the onboard hip joint angle sensors and the pressure insoles is used to classify five locomotion modes, including two static modes (sitting, standing still), and three dynamic modes (level-ground walking, ascending stairs, and descending stairs). The proposed method classifies these two kinds of modes first by monitoring the variation of the relative hip joint angle between the two legs within a specific period. Static states are then classified by the time-based absolute hip joint angle. As for dynamic modes, a fuzzy-logic based method is proposed for the classification. Preliminary experimental results with three able-bodied subjects achieve an off-line classification accuracy higher than 99.49%.