Performance-based robotic assistance during rhythmic arm exercises.
Rhythmic and discrete upper-limb movements are two fundamental motor primitives controlled by different neural pathways, at least partially. After stroke, both primitives can be impaired. Both conventional and robot-assisted therapies mainly train discrete functional movements like reaching and grasping. However, if the movements form two distinct neural and functional primitives, both should be trained to recover the complete motor repertoire. Recent studies show that rhythmic movements tend to be less impaired than discrete ones, so combining both movement types in therapy could support the execution of movements with a higher degree of impairment by movements that are performed more stably.



A new performance-based assistance method was developed to train rhythmic movements with a rehabilitation robot. The algorithm uses the assist-as-needed paradigm by independently assessing and assisting movement features of smoothness, velocity, and amplitude. The method relies on different building blocks: (i) an adaptive oscillator captures the main movement harmonic in state variables, (ii) custom metrics measure the movement performance regarding the three features, and (iii) adaptive forces assist the patient. The patient is encouraged to improve performance regarding these three features with assistance forces computed in parallel to each other. The method was tested with simulated jerky signals and a pilot experiment with two stroke patients, who were instructed to make circular movements with an end-effector robot with assistance during half of the trials.



Simulation data reveal sensitivity of the metrics for assessing the features while limiting interference between them. The assistance's effectiveness with stroke patients is established since it (i) adapts to the patient's real-time performance, (ii) improves patient motor performance, and (iii) does not lead the patient to slack. The smoothness assistance was by far the most used by both patients, while it provided no active mechanical work to the patient on average.



Our performance-based assistance method for training rhythmic movements is a viable candidate to complement robot-assisted upper-limb therapies for training a larger motor repertoire.
Université catholique de Louvain, Center for Research in Mechatronics, Institute of Mechanics, Materials and Civil Engineering, Place du Levant 2, Louvain-la-Neuve, 1348, Belgium. patricia.leconte@uclouvain.be.|Université catholique de Louvain, Louvain Bionics, Place du Levant 2, Louvain-la-Neuve, 1348, Belgium. patricia.leconte@uclouvain.be.
Patricia
P
Leconte
Université catholique de Louvain, Center for Research in Mechatronics, Institute of Mechanics, Materials and Civil Engineering, Place du Levant 2, Louvain-la-Neuve, 1348, Belgium.|Université catholique de Louvain, Institute of Neuroscience, Tour Pasteur - Avenue Mounier 53, Brussels, 1200, Belgium.|Université catholique de Louvain, Louvain Bionics, Place du Levant 2, Louvain-la-Neuve, 1348, Belgium.
Renaud
R
Ronsse
D000465:Algorithms; D001132:Arm / Q000503:physiopathology; D005081:Exercise Therapy / Q000295:instrumentation / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009068:Movement / Q000502:physiology; D012371:Robotics / Q000295:instrumentation / Q000379:methods*; D020521:Stroke / Q000503:physiopathology; D000071939:Stroke Rehabilitation / Q000295:instrumentation / Q000379:methods*; D034941:Upper Extremity / Q000503:physiopathology
Assist-as-needed; Neurorehabilitation; Performance-based assistance; Robotics