Uncontrolled manifold analysis of arm joint angle variability during robotic teleoperation and freehand movement of surgeons and novices

Teleoperated robot-assisted surgery (RAS) is used to perform a wide variety of minimally invasive procedures. However, current understanding of the effect of robotic manipulation on the motor coordination of surgeons is limited. Recent studies in human motor control suggest that we optimize hand movement stability and task performance while minimizing control effort and improving robustness to unpredicted disturbances. To achieve this, the variability of joint angles and muscle activations is structured to reduce task-relevant variability and increase task-irrelevant variability. In this study, we determine whether teleoperation of a da Vinci Si surgical system in a nonclinical task of simple planar movements changes this structure of variability in experienced surgeons and novices. To answer this question, we employ the UnControlled manifold analysis that partitions users' joint angle variability into task-irrelevant and task-relevant manifolds. We show that experienced surgeons coordinate their joint angles to stabilize hand movements more than novices, and that the effect of teleoperation depends on experience - experts increase teleoperated stabilization relative to freehand whereas novices decrease it. We suggest that examining users' exploitation of the task-irrelevant manifold for stabilization of hand movements may be applied to: (1) evaluation and optimization of teleoperator design and control parameters, and (2) skill assessment and optimization of training in RAS.