Locomotor Training in Subjects with Sensori‐Motor Deficits: An Overview of the Robotic Gait Orthosis Lokomat

Abstract

It is known that improvement in walking function can be achieved in patients suffering a movement disorder after stroke or spinal cord injury by providing intensive locomotor training. Rehabilitation robots allow for a longer and more intensive training than that achieved by conventional therapies. Robot assisted treadmill training also offers the ability to provide objective feedback within one training session and to monitor functional improvements over time. This article provides an overview of the technical features and reports the clinical data available for one of these systems known as "Lokomat". First, background information is given for the neural mechanisms of gait recovery. The basic technical approach of the Lokomat system is then described. Furthermore, new features are introduced including cooperative control strategies, assessment tools and augmented feedback. These features may be capable of further enhancing training intensity and patient participation. Findings from clinical studies are presented covering the feasibility as well as efficacy of Lokomat assisted treadmill training.

Cooperative Control Design for Robot-Assisted Balance During Gait

“…In the experiment, five non-impaired human subjects (3 m, 2 f, aged 26-60 y) walked on a treadmill, while the uprighting feed-forward controller assisted their balance. The Lokomat is a stationary exoskeleton, originally designed to assist hip and knee flexion/extension during treadmill gait, while constraining leg and pelvis motion to the sagittal plane [19]. Vertical translation is not actuated, but the weight of the exoskeleton is passively compensated by a spring mechanism.…”

“…We also show how such a control law can be implemented in a computationally efficient way when simplifying assumptions on the dynamics are made. Finally, we describe a simple experimental study on the Lokomat gait rehabilitation robot [19], to evaluate how humans interact with and perceive the assistance.…”

Effectively Quantifying the Performance of Lower-Limb Exoskeletons Over a Range of Walking Conditions

“…If exoskeletons are to become widely used devices outside of a clinical setting it is important that a suitable control paradigm is developed that, either implicitly or explicitly, applies assistance that accounts for these variables. Current control paradigms frequently use normalised kinematic trajectories (Riener et al, 2010), muscle amplification (Ferris and Lewis, 2009), or finite state controllers (Blaya and Herr, 2004). The respective issues with these paradigms are that the kinematic trajectory might not be appropriate for the user's task or their environment, the muscle firing patterns may be abnormal, and there are a large number of parameters to tune.…”

Identifying invariant gait metrics for exoskeleton assistance

“…If exoskeletons are to become widely used devices outside of a clinical setting it is important that a suitable control paradigm is developed that applies the correct assistance that is task and environment specific. Current control paradigms frequently use normalised kinematic trajectories [3], muscle amplification [4], or finite state controllers [5]. The respective issues with these paradigms are that the kinematic trajectory might not be appropriate for the user's task or their environment, the muscle firing patterns may be abnormal, and there are a large number of parameters to tune.…”