Abstract

This paper presents the technological status of robot-assisted gait self-training under real clinical environment conditions. A successful rehabilitation after surgery in hip endoprosthetics comprises self-training of the lessons taught by physiotherapists. While doing this, immediate feedback to the patient about deviations from the expected physiological gait pattern during training is important. Hence, the Socially Assistive Robot (SAR) developed for this type of training employs task-specific, user-centered navigation and autonomous, real-time gait feature classification techniques to enrich the self-training through companionship and timely corrective feedback. The evaluation of the system took place during user tests in a hospital from the point of view of technical benchmarking, considering the therapists’ and patients’ point of view with regard to training motivation and from the point of view of initial findings on medical efficacy as a prerequisite from an economic perspective. In this paper, the following research questions were primarily considered: Does the level of technology achieved enable autonomous use in everyday clinical practice? Has the gait pattern of patients who used additional robot-assisted gait self-training for several days been changed or improved compared to patients without this training? How does the use of a SAR-based self-training robot affect the motivation of the patients?

Highlights

  • The independent and self-reliable training of patients independent of the therapist in the rehabilitation process is becoming increasingly important in times of scarce financial and human resources in public healthcare systems

  • In the project “Robot-assisted gait training in orthopedic rehabilitation” (ROGER, 2016–2019), a mobile Socially Assistive Robot (SAR)-based self-training robot was developed based on our preliminary work [1], which assists patients after orthopedic operations such as hip or knee replacement surgery in clinical aftercare with personalized gait exercises to restore a gait pattern that is as physiological as possible

  • In order to assess the state of development of a technology such as the SAR-based gait self-training discussed in this article, various aspects must be taken into account

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Summary

Introduction

The independent and self-reliable training of patients independent of the therapist in the rehabilitation process is becoming increasingly important in times of scarce financial and human resources in public healthcare systems. Self-training assisted by a training robot enables patients to exercise independently of the presence of a physiotherapist, and to receive recommendations for correction from the robot, including positive feedback. In this way, training errors are avoided and the progress of the therapy is strengthened. In the project “Robot-assisted gait training in orthopedic rehabilitation” (ROGER, 2016–2019), a mobile Socially Assistive Robot (SAR)-based self-training robot was developed based on our preliminary work [1], which assists patients after orthopedic operations Such as hip or knee replacement surgery in clinical aftercare with personalized gait exercises to restore a gait pattern that is as physiological as possible (see Figure 1). SAR-assisted gait training and supplements these with considerations of the above issues

Requirements
Methodological–Technical Aspects
User Perspective
Health Economic Aspects
Approaches from Science
Related Products on the Market
Mobile Gait Self-Training under Real Clinical Environment Conditions
Training Application
Robot Platforms Used
System Architectures for Both Robot Platforms
Technical Benchmarking
Product Prototype Platform
Research Platform
State of Development from the Users’ Point of View
State of Development from an Economic Perspective
Findings
Conclusions on the Questions of the Article and Outlook
Full Text
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