An Uncontrolled Manifold Analysis of Arm Joint Variability in Virtual Planar Position and Orientation Telemanipulation

Buzzi, Jacopo; Momi, Elena De; Nisky, Ilana

doi:10.1109/tbme.2018.2842458

Cited by 19 publications

(20 citation statements)

References 56 publications

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“…This was in contrast to what is known about adaptation to a visuomotor rotation with continuous visual feedback in point-to-point movements: the adaptation is typically fast [47], but it is usually almost fully compensated [8, 22]. Early works found hints of separate mechanisms for the control of orientation compared to translation [29, 30, 33, 48, 49], and our results provide additional support for the idea of separate control of orientation and translation. However, we set the performance error of success at 15°; thus it could be expected that participants would adapt to no more than 45°, which was indeed the case (see S1 Appendix A for details).…”

Section: Discussionmentioning

confidence: 90%

Orientation control strategies and adaptation to a visuomotor perturbation in rotational hand movements

Zruya

Nisky

2022

Preprint

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Computational approaches to biological motor control are used to discover the building blocks of human motor behavior. Models explaining features of human hand movements have been studied thoroughly, yet only a few studies attempted to explain the control of the orientation of the hand; instead, they mainly focus on the control of hand translation, predominantly in a single plane. In this study, we aimed to establish a basic understanding of the way humans control the orientation of their hands. We developed a quaternion-based score that quantifies the geodicity of rotational hand movements and evaluated it experimentally. In the first experiment participants performed a simple orientation-matching task with a robotic manipulator. We found that rotations are generally performed by following a geodesic in the quaternion hypersphere, which suggests that, similarly to translation, the orientation of the hand is centrally controlled. We also established a baseline for the study of human response to perturbed visual feedback of the orientation of the hand. In the subsequent second experiment we studied the adaptation of participants to visuomotor rotation that is applied on the hand's rotation, and the transfer of the adaptation to a different initial orientation. We observed partial adaptation to the perturbation. The patterns of the transfer of the adaptation to a different initial orientation were consistent with the representation of the orientation in extrinsic coordinates. The results of the two experiments raise questions regarding the nature of central control of hand orientation. Discussion and intuitions from these results can be of benefit for many applications that involve fine manipulation of rigid bodies, such as teleoperation and neurorehabilitation.

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Section: Discussionmentioning

confidence: 90%

Orientation control strategies and adaptation to a visuomotor perturbation in rotational hand movements

Zruya

Nisky

2022

Preprint

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“…One more reason for the large variability is the human movement variability, which allows to successfully perform a given task with different trajectories. Generally, variability is unavoidable in the motor system, and is even considered a virtue of the sensorimotor system (Touwen, 1993;Todorov and Jordan, 2002;Faisal et al, 2008;Stergiou and Decker, 2011;Kaipust et al, 2012;Nisky et al, 2014a;Buzzi et al, 2019). With repetitions of the task, the decrease in trajectory consistency and force consistency metrics showed that the within-participant variability in consecutive trials was lower at the late stage of the experiment.…”

Section: Discussionmentioning

confidence: 99%

Surgeon-Centered Analysis of Robot-Assisted Needle Driving Under Different Force Feedback Conditions

2020

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Robotic assisted minimally invasive surgery (RAMIS) systems present many advantages to the surgeon and patient over open and standard laparoscopic surgery. However, haptic feedback, which is crucial for the success of many surgical procedures, is still an open challenge in RAMIS. Understanding the way that haptic feedback affects performance and learning can be useful in the development of haptic feedback algorithms and teleoperation control systems. In this study, we examined the performance and learning of inexperienced participants under different haptic feedback conditions in a task of surgical needle driving via a soft homogeneous deformable object-an artificial tissue. We designed an experimental setup to characterize their movement trajectories and the forces that they applied on the artificial tissue. Participants first performed the task in an open condition, with a standard surgical needle holder, followed by teleoperation in one of three feedback conditions: (1) no haptic feedback, (2) haptic feedback based on position exchange, and (3) haptic feedback based on direct recording from a force sensor, and then again with the open needle holder. To quantify the effect of different force feedback conditions on the quality of needle driving, we developed novel metrics that assess the kinematics of needle driving and the tissue interaction forces, and we combined our novel metrics with classical metrics. We analyzed the final teleoperated performance in each condition, the improvement during teleoperation, and the aftereffect of teleoperation on the performance when using the open needle driver. We found that there is no significant difference in the final performance and in the aftereffect between the 3 conditions. Only the two conditions with force feedback presented statistically significant improvement during teleoperation in several of the metrics, but when we compared directly between the improvements in the three different feedback conditions none of the effects reached statistical significance. We discuss possible explanations for the relative similarity in performance. We conclude that we developed several new metrics for the quality of surgical needle driving, but even with these detailed metrics, the advantage of state of the art force feedback methods to tasks that require interaction with homogeneous soft tissue is questionable.

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“…For instance, researchers have discussed ergonomics assessment and safetybased factors such as joint overloading [22,37], the separation distance between the robot and human [76], and muscular 1 https://optitrack.com/ fatigue [48]. In teleoperation estimated posture has been used to directly control a remote robot [6,42,63]. The idea of estimating the 3D posture of a human teleoperator only from the trajectory of the leader robot was introduced concurrently in our previous work [71] and by Rahal et al in [51].…”

Section: Posture Estimation In Human-robot Interactionmentioning

confidence: 99%

Occlusion-Robust Multi-Sensory Posture Estimation in Physical Human-Robot Interaction

Yazdani¹,

Novin²,

Hermans³

2022

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and NVIDIA, USA 3D posture estimation is important in analyzing and improving ergonomics in physical human-robot interaction and reducing the risk of musculoskeletal disorders. Vision-based posture estimation approaches are prone to sensor and model errors, as well as occlusion, while posture estimation solely from the interacting robot's trajectory suffers from ambiguous solutions. To benefit from the advantages of both approaches and improve upon their drawbacks, we introduce a low-cost, non-intrusive, and occlusion-robust multi-sensory 3D postural estimation algorithm in physical human-robot interaction. We use 2D postures from OpenPose over a single camera, and the trajectory of the interacting robot while the human performs a task. We model the problem as a partially-observable dynamical system and we infer the 3D posture via a particle filter. We present our work in teleoperation, but it can be generalized to other applications of physical human-robot interaction. We show that our multi-sensory system resolves human kinematic redundancy better than posture estimation solely using OpenPose or posture estimation solely using the robot's trajectory. This will increase the accuracy of estimated postures compared to the gold-standard motion capture postures. Moreover, our approach also performs better than other single sensory methods when postural assessment using RULA assessment tool.

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An Uncontrolled Manifold Analysis of Arm Joint Variability in Virtual Planar Position and Orientation Telemanipulation

Cited by 19 publications

References 56 publications

Orientation control strategies and adaptation to a visuomotor perturbation in rotational hand movements

Orientation control strategies and adaptation to a visuomotor perturbation in rotational hand movements

Surgeon-Centered Analysis of Robot-Assisted Needle Driving Under Different Force Feedback Conditions

Occlusion-Robust Multi-Sensory Posture Estimation in Physical Human-Robot Interaction

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