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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
Summary
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
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