Robot-aided assessment of lower extremity functions: a review.

Journal: Journal of neuroengineering and rehabilitation
Published Date:

Abstract

The assessment of sensorimotor functions is extremely important to understand the health status of a patient and its change over time. Assessments are necessary to plan and adjust the therapy in order to maximize the chances of individual recovery. Nowadays, however, assessments are seldom used in clinical practice due to administrative constraints or to inadequate validity, reliability and responsiveness. In clinical trials, more sensitive and reliable measurement scales could unmask changes in physiological variables that would not be visible with existing clinical scores.In the last decades robotic devices have become available for neurorehabilitation training in clinical centers. Besides training, robotic devices can overcome some of the limitations in traditional clinical assessments by providing more objective, sensitive, reliable and time-efficient measurements. However, it is necessary to understand the clinical needs to be able to develop novel robot-aided assessment methods that can be integrated in clinical practice.This paper aims at providing researchers and developers in the field of robotic neurorehabilitation with a comprehensive review of assessment methods for the lower extremities. Among the ICF domains, we included those related to lower extremities sensorimotor functions and walking; for each chapter we present and discuss existing assessments used in routine clinical practice and contrast those to state-of-the-art instrumented and robot-aided technologies. Based on the shortcomings of current assessments, on the identified clinical needs and on the opportunities offered by robotic devices, we propose future directions for research in rehabilitation robotics. The review and recommendations provided in this paper aim to guide the design of the next generation of robot-aided functional assessments, their validation and their translation to clinical practice.

Authors

  • Serena Maggioni
    Sensory-Motor Systems (SMS) Lab, Institute of Robotics and Intelligent Systems (IRIS), Department of Health Sciences and Technology (D-HEST), ETH Zürich, Zürich, Switzerland. serenam@ethz.ch.
  • Alejandro Melendez-Calderon
    Hocoma AG, Volketswil, Switzerland.
  • Edwin van Asseldonk
  • Verena Klamroth-Marganska
    Sensory-Motor Systems Lab, Department of Health Sciences and Technology ETH Zurich, Zurich, Switzerland; Balgrist University Hospital, University of Zurich, Zurich, Switzerland.
  • Lars Lünenburger
    Hocoma AG, Volketswil, Switzerland.
  • Robert Riener
    Sensory-Motor Systems Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.
  • Herman van der Kooij