Diagnostic-based Design for Human Locomotion System

The authors have developed a diagnostic algorithm to facilitate the design and optimization of a human locomotion system. The analysis enables the kinematic gait characteristics of a human gait device to be adjusted in order to enable the mimicking of a range of gaits during motion, thus allowing patient-initiated patterns to be completed or refined. The algorithm may be used for a smart gait system to offer both passive training and locomotor training with optimal feedback about kinematics and forces. The diagnostic algorithm offers very good data acquisition capabilities to the gait system and thus, may help to improve the quality of data about pathological gait deviations during treadmill walking and also normal usual walking speeds. It may also provide objective data of outcome measures of change in individuals. This paper presents an innovative concept for designing a mechanical system capable of emulating the gait capabilities of a human subject. This may assist in the establishment of new means to deliver therapy to patients with gait disabilities.