On the Value of Estimating Human Arm Stiffness during Virtual Teleoperation with Robotic Manipulators

Teleoperated robotic systems are widely spreading in multiple different fields, from hazardous environments exploration to surgery. In teleoperation, users directly manipulate a master device to achieve task execution at the slave robot side; this interaction is fundamental to guarantee both system stability and task execution performance. In this work, we propose a non-disruptive method to study the arm endpoint stiffness. We evaluate how users exploit the kinetic redundancy of the arm to achieve stability and precision during the execution of different tasks with different master devices. Four users were asked to perform two planar trajectories following virtual tasks using both a serial and a parallel link master device. Users' arm kinematics and muscular activation were acquired and combined with a user-specific musculoskeletal model to estimate the joint stiffness. Using the arm kinematic Jacobian, the arm end-point stiffness was derived. The proposed non-disruptive method is capable of estimating the arm endpoint stiffness during the execution of virtual teleoperated tasks. The obtained results are in accordance with the existing literature in human motor control and show, throughout the tested trajectory, a modulation of the arm endpoint stiffness that is affected by task characteristics and hand speed and acceleration

Laparoscopic Tissue Retractor Based on Local Magnetic Actuation

Magnetic instruments for laparoscopic surgery have the potential to enhance triangulation and reduce invasiveness, as they can be rearranged inside the abdominal cavity and do not need a dedicated port during the procedure. Onboard actuators can be used to achieve a controlled and repeatable motion at the interface with the tissue. However, actuators that can fit through a single laparoscopic incision are very limited in power and do not allow performance of surgical tasks such as lifting an organ. In this study, we present a tissue retractor based on local magnetic actuation (LMA). This approach combines two pairs of magnets, one providing anchoring and the other transferring motion to an internal mechanism connected to a retracting lever. Design requirements were derived from clinical considerations, while finite element simulations and static modeling were used to select the permanent magnets, set the mechanism parameters, and predict the lifting and supporting capabilities of the tissue retractor. A three-tier validation was performed to assess the functionality of the device. First, the retracting performance was investigated via a benchtop experiment, by connecting an increasing load to the lever until failure occurred, and repeating this test for different intermagnetic distances. Then, the feasibility of liver resection was studied with an ex vivo experiment, using porcine hepatic tissue. Finally, the usability and the safety of the device were tested in vivo on an anesthetized porcine model. The developed retractor is 154 mm long, 12.5 mm in diameter, and weights 39.16 g. When abdominal wall thickness is 2 cm, the retractor is able to lift more than ten times its own weight. The model is able to predict the performance with a relative error of 9.06 ± 0.52%. Liver retraction trials demonstrate that the device can be inserted via laparoscopic access, does not require a dedicated port, and can perform organ retraction. The main limitation is the reduced mobility due to the length of the device. In designing robotic instrument for laparoscopic surgery, LMA can enable the transfer of a larger amount of mechanical power than what is possible to achieve by embedding actuators on board. This study shows the feasibility of implementing a tissue retractor based on this approach and provides an illustration of the main steps that should be followed in designing a LMA laparoscopic instrument

An uncontrolled manifold analysis of arm joint variability in virtual planar position and orientation tele-manipulation

Objective: In teleoperated robot-assisted tasks, the user interacts with manipulators to finely control remote tools. Manipulation of robotic devices, characterized by specific kinematic and dynamic proprieties, is a complex task for the human sensorimotor system due to the inherent biomechanical and neuronal redundancies that characterize the human arm and its control. We investigate how master devices with different kinematics structures and how different task constraints influence users capabilities in exploiting arm redundancy. Methods: A virtual teleoperation workbench was designed and the arm kinematics of seven users was acquired during the execution of two planar virtual tasks, involving either the control of position only or position-orientation of a tool. Using the UnControlled Manifold Analysis of arm joint variability we estimated the logarithmic ratio between task irrelevant and the task relevant manifolds (Rv). Results: The Rv values obtained in the position-orientation task were higher than in the position only task while no differences were found between the master devices. A modulation of Rv was found through the execution of the position task and a positive correlation was found between task performance and redundancy exploitation. Conclusion: Users exploited additional portions of arm redundancy when dealing with the tool orientation. The Rv modulation seems influenced by the task constraints and by the users possibility of reconfiguring the arm position. Significance: This work advances the general understanding of the exploitation of arm redundancy in complex tasks, and can improve the development of future robotic devices

A new handheld electromagnetic cortical stimulator for brain mapping during open skull neurosurgery: a feasibility study

Transcranial magnetic stimulations have provided invaluable tools for investigating nervous system functions in a preoperative context; in this paper we propose an innovative tool to extend the magnetic stimulation to an open skull context as a promising approach to map the brain cortex. The present gold standard for intraoperative functional mapping of the brain cortex, the direct brain stimulation, has a low spatial resolution and limited penetration and focusing capabilities. The magnetic stimulatory device that we present, is designed to overcome these limitations, while working with low currents and voltages. In the present work we propose an early study of feasibility, in which the possibility of exploiting a train of fast changing magnetic fields to reach the neuron's current thresholds is investigated. Measurements of electric field intensity at different distances from the coil, showed that the magnetic stimulator realized is capable of delivering an electric field on a loop of wire theoretically sufficient to evoke neuron's action potential, thus showing the approach' feasibility

Biomimetic adaptive impedance control in physical Human Robot Interaction

Human Robot Interaction has become a key point in the development of new robotic interfaces and controllers. In traditional control schemes for teleoperation, master devices are unaware of the user's arm dynamic characteristics, as well as of the complex motor control strategies adopted to perform the task. In this work, we propose a novel impedance controller to regulate the master device's dynamic properties based on the estimation of user's arm stiffness, with the aim of improving shared task performance. We developed a virtual planar reaching task, and we evaluated arm end-point stiffness's main axis changes in magnitude and direction using a non disruptive offline musculoskeletal model-based algorithm. Based on the stiffness modulation, the biomimetic variable impedance controller to adapt the master device's damping matrix. The direction of maximal damping was aligned with the estimated direction of maximal stiffness (Enhancing field), or to the perpendicular to the stiffness main axis (Isotropic field). The task performances under the biomimetic impedance controllers were tested and compared with the null damping condition. The results showed an increase in task performance, in terms of positional error and overshoots, with both biomimetic controllers. The analysis proved the potentiality of the biomimetic impedance modulation controller in terms of execution accuracy