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Application of a Tactile Sensor for the Gait Phase Classification for an Exoskeleton

This paper presents the design and implementation of fuzzy logic control for human walking using lab-developed sensors and the second lower limb robotic exoskeleton (LLRE-II) to detect gait phases. A piezoresistive tactile sensor (PRTS) was developed and used to measure the foot pressure to predict human walking behavior. The proposed sensor with grid structures was then fabricated using polymer composites of multi-walled carbon nanotubes (MWCNTs) combined with polydimethylsiloxane (PDMS). The doping ratio and design of the grid structure of the sensors were optimized to achieve a good sensing range. The foot reactive forces measured by the four sensors were calculated and converted to force ratio factors to improve the performance of gait phase detection by the fuzzy logic control. Based on the sensor tests, the most stable doping ratio was fixed as 7 wt%, and the ratio of the grid structure (line width:line spacing:thickness) was 1:1:1. Sensors were set in the soles of the shoes on the foot pads of the exoskeleton, and the foot reactive forces were captured for analysis. The performance of the proposed algorithm for gait phase detection was verified experimentally. The results indicated that both regular and irregular walking could be detected by the proposed method.