No abstract

Pneumatics is one of the few actuation principles that can be used in an MR environment, since it can produce high forces without affecting imaging quality. However, pneumatic control is challenging, due to the air high compliance and cylinders non-linearities. Furthermore, the system's properties may change for each subject. Here, we present novel control strategies that adapt to the subject's individual anatomy and needs while performing accurate periodic gait-like movements with an MRI compatible pneumatically driven robot. In subject-passive mode, an iterative learning controller (ILC) was implemented to reduce the system's periodic disturbances. To allow the subjects to intend the task by themselves, a zeroforce controller minimized the interaction forces between subject and robot. To assist patients who may be too weak, an assist-as-needed controller that adapts the assistance based on online measurement of the subject's performance was designed. The controllers were experimentally tested. The ILC successfully learned to reduce the variability and tracking errors. The zero-force controller allowed subjects to step in a transparent environment. The assist-as-needed controller adapted the assistance based on individual needs, while still challenged the subjects to perform the task. The presented controllers can provide accurate pneumatic control in MR environments to allow assessments of brain activation.

The goal of robotic therapy is to provoke motor plasticity via the application of robotic training strategies. Although robotic haptic guidance is the commonly used motor-training strategy to reduce performance errors while training, research on motor learning has emphasized that errors are a fundamental neural signal that drives motor adaptation. Thus, researchers have proposed robotic therapy algorithms that amplify movement errors rather than decrease them. Studying the particular brain regions involved in learning under different training strategies might help tailoring motor training conditions to the anatomical location of a focal brain insult. In this paper, we evaluate the brain regions involved in locomotion adaptation when training with three different conditions: without robotic guidance, with a random-varying force disturbance, and with repulsive forces proportional to errors. We performed an fMRI pilot study with four healthy subjects who stepped in an fMRI compatible walking robotic device. Subjects were instructed to actively synchronize their left leg with respect to their right leg (passively guided by the robot) while their left leg was affected by any of the three conditions. We observed activation in areas known to be involved in error processing. Although we found that all conditions required the similar cortical network to fulfill the task, we observed a tendency towards more activity in the motor/sensory network as more "challenged" the subjects were.

The strong magnetic fields and limited space make it challenging to design the actuation for mechatronic systems intended to work in MRI environments. Hydraulic and pneumatic actuators can be made MRI-compatible and are promising solutions to drive robotic devices inside MRI environments. In this paper, two comparable haptic interface devices, one with hydrodynamic and another with pneumatic actuation, were developed to control one-degree-of-freedom translational movements of a user performing functionalMRI(fMRI) tasks. The cylinders were made of MRI-compatible materials. Pressure sensors and control valves were placed far away from the end-effector in the scanner, connected via long transmission lines. It has been demonstrated that both manipulandum systems were MRI-compatible and yielded no artifacts to fMRI images in a 3-T scanner. Position and impedance controllers achieved passive as well as active subject movements. With the hydrodynamic system we have achieved smoother movements, higher position control accuracy, and improved robustness against force disturbances than with the pneumatic system. In contrast, the pneumatic system was back-drivable, showed faster dynamics with relatively low pressure, and allowed force control. Furthermore, it is easier to maintain and does not cause hygienic problems after leakages. In general, pneumatic actuation is more favorable for fast or force-controlled MRI-compatible applications, whereas hydrodynamic actuation is recommended for applications that require higher position accuracy, or slow and smooth movements. Abstract-The strong magnetic fields and limited space make it challenging to design the actuation for mechatronic systems intended to work in MRI environments. Hydraulic and pneumatic actuators can be made MRI-compatible and are promising solutions to drive robotic devices inside MRI environments. In this paper, two comparable haptic interface devices, one with hydrodynamic and another with pneumatic actuation, were developed to control one-degree-of-freedom translational movements of a user performing functional MRI (fMRI) tasks. The cylinders were made of MRI-compatible materials. Pressure sensors and control valves were placed far away from the end-effector in the scanner, connected via long transmission lines. It has been demonstrated that both manipulandum systems were MRI-compatible and yielded no artifacts to fMRI images in a 3-T scanner. Position and impedance controllers achieved passive as well as active subject movements. With the hydrodynamic system we have achieved smoother movements, higher position control accuracy, and improved robustness against force disturbances than with the pneumatic system. In contrast, the pneumatic system was back-drivable, showed faster dynamics with relatively low pressure, and allowed force control. Furthermore, it is easier to maintain and does not cause hygienic problems after leakages. In general, pneumatic actuation is more favorable for fast or force-controlled MRI-compatible applications, whereas hydrodynamic a...