Visual Noise Linearly Influences Tracking Performance.

This study investigates the influence of visual noise on motor performance in three degrees of freedom (DoFs) tracking task including translation against gravity and rotation. Participants were asked to follow a moving target, visually degraded according to four different levels of noise, plus one no-noise condition. Each noise level was represented with ten target replicas normally distributed around the main target's pose with a specific standard deviation. Performance, in term of error between cursor and target, significantly decreased (p < 0.001) with the increase of the standard deviation of the visual noise, in all movement directions. The relation between the level of visual noise and the performance appears to be linear (R2 > 0.8) for each DoF separately, as well as when we combine the translations using the Euclidean norm.

Tele-Impedance Control Approach Using Wearable Sensors.

Tele-operational tasks often suffer from instability issues and limited reliability during unpredictable interactions. We propose a real-time control law reproducing the impedance and kinematic behaviour of a subject's arm (shoulder and elbow) on a remote avatar in a 2-DoF task. The human arm impedance and kinematics are estimated respectively from EMG and M-IMU data and then mapped into the avatar arm through an impedance control. Contrary to literature methods, our portable tele-impedance controller relies only on wearable sensors and enables an easy use in unstructured environments. The good performance (R2> 0.7) of the muscle model used to map on the robot the human stiffness of five healthy subjects indicates the possibility of applying the proposed algorithm for a tele-impedance control.

Human performance in three-hands tasks.

The successful completion of complex tasks like hanging a picture or laparoscopic surgery requires coordinated motion of more than two limbs. User-controlled supernumerary robotic limbs (SL) have been proposed to bypass the need for coordination with a partner in such tasks. However, neither the capability to control multiple limbs alone relative to collaborative control with partners, nor how that capability varies across different tasks, is well understood. In this work, we present an investigation of tasks requiring three-hands where the foot was used as an additional source of motor commands. We considered: (1) how does simultaneous control of three hands compare to a cooperating dyad; (2) how this relative performance was altered by the existence of constraints emanating from real or virtual physical connections (mechanical constraints) or from cognitive limits (cognitive constraints). It was found that a cooperating dyad outperformed a single user in all scenarios in terms of task score, path efficiency and motion smoothness. However, while the participants were able to reach more targets with increasing mechanical constraints/decreasing number of simultaneous goals, the relative difference in performance between a dyad and a participant performing trimanual activities decreased, suggesting further potential for SLs in this class of scenario.

Development and Validation of a Novel Calibration Methodology and Control Approach for Robot-Aided Transcranial Magnetic Stimulation (TMS).

OBJECTIVE: This article presents the development and validation of a new robotic system for Transcranial Magnetic Stimulation (TMS), characterized by a new control approach, and an ad-hoc calibration methodology, specifically devised for the TMS application. METHODS: The robotic TMS platform is composed of a 7 dof manipulator, controlled by an impedance control, and a camera-based neuronavigation system. The proposed calibration method was optimized on the workspace useful for the specific TMS application (spherical shell around the subject's head), and tested on three different hand-eye and robot-world calibration algorithms. The platform functionality was tested on six healthy subjects during a real TMS procedure, over the left primary motor cortex. RESULTS: employing our method significantly decreases ( ) the calibration error by 34% for the position and 19% for the orientation. The robotic TMS platform achieved greater orientation accuracy than the expert operators, significantly reducing orientation errors by 46% ( ). No significant differences were found in the position errors and in the amplitude of the motor evoked potentials (MEPs) between the robot-aided TMS and the expert operators. CONCLUSION: The proposed calibration represents a valid method to significantly reduce the calibration errors in robot-aided TMS applications. Results showed the efficacy of the proposed platform (including the control algorithm) in administering a real TMS procedure, achieving better coil positioning than expert operators, and similar results in terms of MEPs. SIGNIFICANCE: This article spotlights how to improve the performance of a robotic TMS platform, providing a reproducible and low-cost alternative to the few devices commercially available.

A virtual reality platform for multisensory integration studies.

A unique virtual reality platform for multisensory integration studies is presented. It allows to provide multimodal sensory stimuli (i.e. auditory, visual, tactile, etc.) ensuring temporal coherence, key factor in cross-modal integration. Four infrared cameras allow to real-time track the human motion and correspondingly control a virtual avatar. A user-friendly interface allows to manipulate a great variety of features (i.e. stimulus type, duration and distance from the participants' body, as well as avatar gender, height, arm pose, perspective, etc.) and to real-time provide quantitative measures of all the parameters. The platform has been validated on two healthy participants testing a reaction time task which combines tactile and visual stimuli, for the investigation of peripersonal space. Results proved the effectiveness of the proposed platform, showing a significant correlation (p=0.013) between the participant's hand distance from the visual stimulus and the reaction time to the tactile stimulus. More participants will be recruited to further investigate the other measures provided by the platform.

Evaluation of hand-eye and robot-world calibration algorithms for TMS application.

In this paper we compare three approaches to solve the hand-eye and robot-world calibration problem, for their application to a Transcranial Magnetic Stimulation (TMS) system. The selected approaches are: i) non-orthogonal approach (QR24); ii) stochastic global optimization (SGO); iii) quaternion-based (QUAT) method. Performance were evaluated in term of translation and rotation errors, and computational time. The experimental setup is composed of a 7 dof Panda robot (by Franka Emika GmbH) and a Polaris Vicra camera (by Northern Digital Inc) combined with the SofTaxic Optic software (by E.M.S. srl). The SGO method resulted to have the best performance, since it provides lowest errors and high stability over different datasets and number of calibration points. The only drawback is its computational time, which is higher than the other two, but this parameter is not relevant for TMS application. Over the different dataset used in our tests, the small workspace (sphere with radius of 0.05m) and a number of calibration points around 150 allow to achieve the best performance with the SGO method, with an average error of 0.83 ± 0.35mm for position and 0.22 ± 0.12deg for orientation.

A teleoperated control approach for anthropomorphic manipulator using magneto-inertial sensors.

In this paper we propose and validate a teleoperated control approach for an anthropomorphic redundant robotic manipulator, using magneto-inertial sensors (IMUs). The proposed method allows mapping the motion of the human arm (used as the master) on the robot end-effector (the slave). We record arm movements using IMU sensors, and calculate human forward kinematics to be mapped on robot movements. In order to solve robot kinematic redundancy, we implemented different algorithms for inverse kinematics that allows imposing anthropomorphism criteria on robot movements. The main objective is to let the user to control the robotic platform in an easy and intuitive manner by providing the control input freely moving his/her own arm and exploiting redundancy and anthropomorphism criteria in order to achieve human-like behaviour on the robot arm. Therefore, three inverse kinematics algorithms are implemented: Damped Least Squares (DLS), Elastic Potential (EP) and Augmented Jacobian (AJ). In order to evaluate the performance of the algorithms, four healthy subjects have been asked to control the motion of an anthropomorphic robot arm (i.e. the Kuka Light Weight Robot 4+) through four magneto-inertial sensors (i.e. Xsens Wireless Motion Tracking sensors - MTw) positioned on their arm. Anthropomorphism indices and position and orientation errors between the human hand pose and the robot end-effector pose were evaluated to assess the performance of our approach.