Effects of Impedance Reduction of a Robot for Wrist Rehabilitation on Human Motor Strategies in Healthy Subjects during Pointing Tasks

Studies on human motor control demonstrated the existence of simplifying strategies (namely `Donders' law') adopted to deal with kinematically redundant motor tasks. In recent research we showed that Donders' law also holds for human wrist during pointing tasks, and that it is heavily perturbed when interacting with a highly back-drivable state-of-the-art rehabilitation robot. We hypothesized that this depends on the excessive mechanical impedance of the Pronation/Supination (PS) joint of the robot and in this work we analyzed the effects of its reduction. To this end we deployed a basic force control scheme, which minimizes human-robot interaction force. This resulted in a 70% reduction of the inertia in PS joint and in decrease of 81% and 78% of the interaction torques during 1-DOF and 3-DOFs tasks. To assess the effects on human motor strategies, pointing tasks were performed by three subjects with a lightweight handheld device, interacting with the robot using its standard PD control (setting impedance to zero) and with the force-controlled robot. We quantified Donders' law as 2-dimensional surfaces in the 3-dimensional configuration space of rotations. Results revealed that the subject-specific features of Donders' surfaces reappeared after the reduction of robot impedance obtained via the force control

Design and assembly of a magneto-inertial wearable device for ecological behavioural analysis of infants

There are recent evidence which show how brain development is strictly linked to the action. Movements shape and are, in turn, shaped by cortical and sub-cortical areas. In particular spontaneous movements of newborn infants matter for developing the capability of generating voluntary skill movements. Therefore studying spontaneous infants’ movements can be useful to understand the main developmental milestones achieved by humans from birth onward. This work focuses on the design and development of a mechatronic wearable device for ecological movement analysis called WAMS (Wrist and Ankle Movement Sensor). The design and assembling of the device is presented, as well as the communication protocol and the synchronization with other marker-based optical movement analysis systems

Inertial-Magnetic Sensors for Assessing Spatial Cognition in Infants

This paper describes a novel approach to the assessment of spatial cognition in children. In particular we present a wireless instrumented toy embedding magneto-inertial sensors for orientation tracking, specifically developed to assess the ability to insert objects into holes. To be used in naturalistic environments (e.g. daycares), we also describe an in-field calibration procedure based on a sequence of manual rotations, not relying on accurate motions or sophisticated equipment. The final accuracy of the proposed system, after the mentioned calibration procedure, is derived by direct comparison with a gold-standard motion tracking device. In particular, both systems are subjected to a sequence of ten single-axis rotations (approximately 90 deg, back and forth), about three different axes. The root-mean-square of the angular error between the two measurements (gold-standard vs. proposed systems) was evaluated for each trial. In particular, the average rms error is under 2 deg. This study indicates that a technological approach to ecological assessment of spatial cognition in infants is indeed feasible. As a consequence, prevention through screening of large number of infants is at reach

Design, Development and Scaling Analysis of a Variable Stiffness Magnetic Torsion Spring

In this paper we report on the design, modeling, experimental testing and scaling analysis of a novel MAgnetic Variable stiffnEess spRIng-Clutch (MAVERIC) device, which may be used as the elastic element of Variable Stiffness Actuators (VSAs). The device, comprising two co-axial diametrically magnetized hollow cylinders, has two degrees of freedom: a rotation of the two cylinders around the common axis and a relative translation along the same axis. For small rotations, the torque arising from the magnetic interaction of the two cylinders is almost linearly proportional to their relative rotation, as in mechanical torsion springs. In addition, the stiffness of the equivalent spring can be varied continuously from a maximum value down to exactly zero by changing the axial overlap of the two cylinders. In this way the proposed device can be used both as a clutch (i.e., perfectly compliant element) and as a variable stiffness torsion spring. A prototype, designed after magnetostatic FEM simulations, has been built and experimentally characterized. The developed MAVERIC has an experimentally determined maximum transmissible torque of 109.81mNm, while the calculated maximum stiffness is 110.2mNmrad−1. The amplitude of the torque-angle characteristic can be tuned linearly with a sensitivity of 12.63mNmmm−1 rad−1. Further simulations have been computed parameterizing the geometry and the number of pole pairs of the magnets. The maximum torque density reached for one pole pair is 47.21 · 103 Nm m−3, whereas for a fixed geometry similar to that of the developed prototype, the maximum torque is reached for seven pole pairs. Overall, compared to mechanical springs, MAVERIC has no fatigue or overloading issues. Compared to other magnetic couplers, torsion stiffness can be varied continuously from a maximum value down to exactly zero, when the device acts as a disengaged clutch, disconnecting the load from the actuator

A reinforcement learning model of reaching integrating kinematic and dynamic control in a simulated arm robot

Models proposed within the literature of motor control have polarised around two classes of controllers which differ in terms of controlled variables: the Force-Control Models(FCMs), based on dynamic control, and the Equilibrium-Point Models (EPMs), based on kinematic control. This paper proposes a bioinspired model which aims to exploit the strengths of the two classes of models. The model is tested with a 3D physical simulator of a 2DOF-controlled arm robot engaged in a reaching task which requires the production of curved trajectories to be solved. The model is based on an actor-critic reinforcementlearning algorithm which uses neural maps to represent both percepts and actions encoded as joint-angle desired equilibrium points (EPs), and a noise generator suitable for fine tuning the exploration/exploitation ratio. The tests of the model show how it is capable of exploiting the simplicity and speed of learning of EPMs as well as the flexibility of FCMs in generating curved trajectories. Overall, the model represents a first step towards the generation of models which exploit the strengths of both EPMs and FCMs and has the potential of being used as a new tool for investigating phenomena related to the organisation and learning of motor behaviour in organisms

Multimodal adaptive interfaces for 3D robot-mediated upper limb neuro-rehabilitation: An overview of bio-cooperative systems

n/

A modular telerehabilitation architecture for upper limb robotic therapy

Several factors may prevent post-stroke subjects from participating in rehabilitation protocols, for example, geographical location of rehabilitation centres, socioeconomic status, economic burden and lack of logistics surrounding transportation. Early supported discharge from hospitals with continued rehabilitation at home represents a well-defined regimen of post-stroke treatment. Information-based technologies coupled with robotics have promoted the development of new technologies for telerehabilitation. In this article, the design and development of a modular architecture for delivering upper limb robotic telerehabilitation with the CBM-Motus, a planar unilateral robotic machine that allows performing state-of-the-art rehabilitation tasks, have been presented. The proposed architecture allows a therapist to set a therapy session on his or her side and send it to the patient's side with a standardized communication protocol; the user interacts with the robot that provides an adaptive assistance during the rehabilitation tasks. Patient's performance is evaluated by means of performance indicators, which are also used to update robot behaviour during assistance. The implementation of the architecture is described and a set of validation tests on seven healthy subjects are presented. Results show the reliability of the novel architecture and the capability to be easily tailored to the user's needs with the chosen robotic device

Identification of Dynamic Parameters for Robots with Elastic Joints

This paper presents a novel method for identifying dynamic parameters of robot manipulators with elastic joints. A procedure based on the Lagrangianm formulation of the dynamic model is proposed. Each term is inspected to search for a linear relationship with the dynamic parameters, thus enabling the linearization of robot dynamic model. Hence, the torque vector is expressed as the product of a regressor matrix, suitably defined by the vector of dynamic parameters. A parametric identification based on a least-squares technique is applied to determine dynamic parameters of robots with elastic joints. The correctness of the proposed procedure has been tested in simulation on two robotic structures with elastic joints of different complexity, that is, a 2-degree-of-freedom (dof) and a 6-dof manipulator, controlled with a PD control in the joint space