Robotic rehabilitation exoskeletons are particularly valuable in therapy because they leverage robotic devices' unique potential for accurate and repeatable movements, and quantitative measurement in position and force domains. In addition to coordinated movement capabilities and functional workspace requirements such as range of motion (ROM) and torque required for ADL, a rehabilitation robot must possess quantitative measurement capabilities for evaluation, which requires high quality position sensing, good backdrivability, and backlash-free operation.

Through the use of functional magnetic resonance imaging (fMRI) in conjunction with a haptic device, it is possible to study changes in brain activity while a patient undergoes rehabilitation-like protocols. By measuring changes in brain activity of a patient undergoing neurorehabilitation during fMRI, optimal patient-specific therapy regimens might be obtained. This research aims to develop, characterize, and control a parallel three degrees of freedom magnetic resonance (MR) compatible haptic device, called the MR-SoftWrist, which can measure and support wrist movements during fMRI.

Providing minimal assistance to neurologically impaired individuals only becomes possible when the subject's functional capability is known.  In this research we introduce a minimal assist-as-needed (mAAN) controller which utilizes sensorless force estimation to determine subject inputs as a function of time, before providing a corresponding assistance with adjustable ultimate bounds on position error.