Gait Training Support Based on Arm-Holding Mobile Robot

Abstract

Recently, needs of robot technology specialized for locomotive rehabilitation and gait assistance are expected increasingly. In gait and locomotive assistance, appropriate recognition of walking patterns and navigation are required; however, most of supporting devices are directly intervening in movements of lower limbs and therefore they let walking patterns be unnatural. In order to solve this problem, we propose a method to estimate walking patterns from movement of lower limb movements and force/contact interaction with upper libs. Step length and velocity can be measured from the movement of lower limbs by a laser-based sensor, and the dependency on the assistance can be measured from the upper limb by a force and tactile sensors, aiming in the optimal control of intervention in walking support for gait navigation. In this paper, we focus on a detection algorithm of walking patterns from the lower limbs.