Realization of human gait in virtual fluid environment on a robotic gait trainer for therapeutic purposes


Ertop T. E. , Yuksel T., KONUKSEVEN E. İ.

ROBOTICS AND AUTONOMOUS SYSTEMS, cilt.105, ss.59-68, 2018 (SCI İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 105
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1016/j.robot.2018.02.012
  • Dergi Adı: ROBOTICS AND AUTONOMOUS SYSTEMS
  • Sayfa Sayıları: ss.59-68

Özet

Patients with disorders such as spinal cord injury, cerebral palsy and stroke can perform full gait when assisted, which progressively helps them regain the ability to walk. A very common way to create assistive effects is aquatic therapy. Aquatic environment also creates resistive effects desired for strength building. In this study, realization of a virtual fluid environment on a robotic gait trainer is presented as an alternative method. A model was created to determine torques and forces acting on the human body while performing gait in a fluid environment. The developed model was implemented on a robotic gait trainer. By adjusting the virtual fluid model parameters, precise control over assistive and resistive effects during gait was achieved without enforcing any pre-defined gait pattern. The real-time gait phase information required by the fluid model to determine torques was provided with a developed algorithm which only uses kinematic gait data. Experiments with healthy subjects were done using the robotic gait trainer to verify the gait phase algorithm, and to compare gait characteristics obtained in virtual land and water environments with the literature. Additional experiments were performed with the robotic system to assess effects of changing fluid model parameters to healthy subject gait characteristics. The results show that force and torque effects of virtual fluid environment on robotic gait trainer were achieved. The gait phase algorithm was shown to provide smooth transition between phases. Also, significant changes in gait characteristics were observed by modifying fluid model parameters. (C) 2018 Elsevier B.V. All rights reserved.