Multi-purpose Robotic Training Strategies for Neurorehabilitation with Model Predictive Controllers

Özen, Özhan; Traversa, Flavio; Gadi, Sofiane; Bütler, Karin; Nef, Tobias; Marchal Crespo, Laura (29 July 2019). Multi-purpose Robotic Training Strategies for Neurorehabilitation with Model Predictive Controllers. IEEE International Conference on Rehabilitation Robotics (ICORR), pp. 754-759. IEEE 10.1109/ICORR.2019.8779396

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One of the main challenges in robotic neurorehabilitation is to understand how robots should physically interact with trainees to optimize motor leaning. There is evidence that motor exploration (i.e., the active exploration of new motor tasks) is crucial to boost motor learning. Furthermore, effectiveness of a robotic training strategy depends on several factors, such as task type and trainee’s skill level. We propose that Model Predictive Controllers (MPC) can satisfy many training/trainee’s needs simultaneously, while providing a safe environment without restricting trainees to a fixed trajectory. We designed two nonlinear MPCs to support training of a rich dynamic task (a pendulum task) with a delta robot. These MPCs differ from each other in terms of the application point of the intervention force: (i) to the virtual pendulum mass, and (ii) the virtual rod holding point, which corresponds to the robot end-effector. The effect of the MPCs on task performance, physical effort, motivation and sense of agency was evaluated in fourteen healthy participants. We found that the location of the applied controller force affects the task performance –i.e., the MPC that actuates on the pendulum mass significantly reduced performance errors and sense of agency during training, while the other MPC did not, probably due to low force saturation limits and slow optimization speed of the solver. Participants applied significantly more forces when training with the MPC that actuates on the pendulum holding point, probably because they reacted against the robotic assistance. Although MPCs look very promising for neurorehabilitation, further steps have to be taken to improve their technical limitations. Moreover, the effects of MPCs on motor learning should be evaluated.

Item Type:

Conference or Workshop Item (Paper)

Division/Institute:

10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - Motor Learning and Neurorehabilitation
10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research
10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - Gerontechnology and Rehabilitation

Graduate School:

Graduate School for Cellular and Biomedical Sciences (GCB)

UniBE Contributor:

Özen, Özhan; Gadi, Sofiane; Bütler, Karin; Nef, Tobias and Marchal Crespo, Laura

Subjects:

500 Science > 570 Life sciences; biology
600 Technology > 610 Medicine & health
600 Technology > 620 Engineering

ISSN:

1945-7901

ISBN:

978-1-7281-2755-2

Publisher:

IEEE

Funders:

[4] Swiss National Science Foundation
[159] Hasler Foundation

Projects:

[1183] OnLINE: Optimize motor Learning to Improve NEurorehabilitation

Language:

English

Submitter:

�zhan �zen

Date Deposited:

26 Aug 2019 09:55

Last Modified:

23 Oct 2019 15:33

Publisher DOI:

10.1109/ICORR.2019.8779396

BORIS DOI:

10.7892/boris.132283

URI:

https://boris.unibe.ch/id/eprint/132283

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