ABSTRACT
Robotic assistive devices are able to enhance physical stability and balance. Smart walkers, in particular, are also capable of offering cognitive support for individuals whom conventional walkers are unsuitable. However, visually impaired individuals often need additional sensorial assistance from those devices. This work proposes a smart walker with an admittance controller for guiding visually impaired individuals along a desired path. The controller uses as inputs the physical interaction between the user and the walker to provide haptic feedback hinting the path to be followed. Such controller is validated in a set of experiments with healthy individuals. At first, users were blindfolded during navigation to assess the capacity of the smart walker in providing guidance without visual input. Then, the blindfold is removed and the focus is on evaluating the human-robot interaction when the user had visual information during navigation. The results indicate that the admittance controller design and the design of the guidance path were factors impacting on the level of comfort reported by users. In addition, when the user was blindfolded, the linear velocity assumed lower values than when did not wear it, from a mean value of 0.19 m/s to 0.21 m/s.
Subject(s)
Self-Help Devices , Feedback , Humans , Locomotion , Walkers , WalkingABSTRACT
This work presents a multimodal cognitive interaction strategy aiming at walker-assisted rehabilitation therapies, with special focus on post-stroke patients. Such interaction strategy is based on monitoring user's gait and face orientation to command the displacement of the smart walker. Users are able to actively command the steering of the walker by changing their face orientation, while their lower limbs movement affect the walker's linear velocity. The proposed system is validated using a smart walker and the results obtained point to the feasibility of employing such cognitive interaction in rehabilitation therapies.
