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11:00
15 mins
Performance-Based Adaptive Assistance for Robotic Gait Training
Simone Fricke, Cristina Bayón, Herman van der Kooij, Edwin van Asseldonk
Session: Neuromuscular – lower extremities 1
Session starts: Friday 25 January, 10:30
Presentation starts: 11:00
Room: Lecture room 536


Simone Fricke (Department of Biomechanical Engineering, University of Twente)
Cristina Bayón (Department of Biomechanical Engineering, University of Twente)
Herman van der Kooij (Department of Biomechanical Engineering, University of Twente)
Edwin van Asseldonk (Department of Biomechanical Engineering, University of Twente)


Abstract:
Robotic gait training can improve walking function after neurological conditions (e.g. stroke, SCI). However, the effect of robotic gait training might largely depend on how exactly therapy is provided. It is expected that robotic gait training is more effective if it is tailored to the patient’s needs and if the gait trainer only assists the user when it is really necessary (assist-as-needed, AAN). For the LOPES II gait trainer [1], the gait cycle is divided into different subtasks (weight shift, step length, step width, step height, stability during stance and prepositioning) and the physical therapist may separately adjust the assistance for these subtasks to only assist the user when it is needed. However, training can be effected by therapist’s subjective decisions and assistance often remains constant during a session. To address these issues, we developed an adaptive controller that automatically adjusts the amount of robotic assistance for the different subtasks of walking based on user’s performance [2]. In addition to using this controller as a therapeutic tool, it might also be used as a monitoring tool to evaluate progress during therapy. The new controller calculates the user’s performance for each subtask by comparing the measured joint angles to a reference trajectory at specific points of the gait cycle. The performance is averaged over the previous three steps and the robotic assistance is adjusted based on that performance. If the performance is better than a threshold plus a tolerance, the assistance decreases by 10%. If it is worse than the threshold minus the tolerance, the assistance increases by 10% and in other cases the assistance remains constant. Pilot experiments in stroke survivors and people with spinal cord injury showed the feasibility of the controller to provide appropriate support during walking, adapting the robotic assistance for each subtasks of walking. However, further experiments need to be performed to investigate the feasibility of the controller as a therapeutic and monitoring tool in people with walking impairments. REFERENCES [1] Meuleman J, Van Asseldonk E, Van Oort G, Rietman H, Van Der Kooij H. LOPES II -Design and Evaluation of an Admittance Controlled Gait Training Robot with Shadow-Leg Approach. IEEE Trans Neural Syst Rehabil Eng. 2016;24(3):352–63. [2] Bayón C, Fricke S, Rocon E, van der Kooij H, van Asseldonk E. Performance-Based Adaptive Assistance for Diverse Subtasks of Walking in a Robotic Gait Trainer: Description of a New Controller and Preliminary Results. In: IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob). 2018.