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-We propose a new approach called as a peak time approach for faster detection of step initiation for the lower limb exoskeleton. As faster detection of step initiation is an important criterion in evaluating the lower limb exoskeleton, many studies have investigated approaches to detect step initiation faster, including using electromyography, the center of pressure, the heel-off time and the toe-off time. In this study, we will utilize vertical ground reaction force events to detect step initiation, and compare our approach with prior approaches. Additionally, we will predict the first step's heel strike time with vertical ground reaction force events from multiple regression equations to support our approach. The lower limb exoskeleton should assist the operator's movement much faster and more reliably with our approach.

Recognition of walking intention and assistance in the load-carrying driver’s walking capability are key challenging areas in lower limb exoskeletons. We present a lower limb exoskeleton called the unmanned technology research centre exoskeleton (UTRCEXO). It recognizes walking intention, including step initiation, step velocity (acceleration and deceleration), and step termination of drivers using only insole-type FSRs and three axis F/T sensors. UTRCEXO recognizes the driver’s intention of step initiation using insole-type FSRs and recognizes the intention of step velocity and step termination using three axis F/T sensors. UTRCEXO makes use of four DC motors, two at each knee and hip joint, to assist the driver. The the driver can carry a 20 kg payload comfortably with muscle activity reduction. In this paper, we evaluate muscle activity reduction in walking drivers equipped with UTRCEXO carrying a 20 kg payload.

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