A Multiscale Approach to Axon and Nerve Stimulation Modeling: A Review.

Electrical nerve fiber stimulation is a technique widely used in prosthetics and rehabilitation, and its study from a computational point of view can be a useful instrument to support experimental tests. In the last years, there was an increasing interest in computational modeling of neural cells and numerical simulations on nerve fibers stimulation because of its usefulness in forecasting the effect of electrical current stimuli delivered to tissues through implanted electrodes, in the design of optimal stimulus waveforms based on the specific application (i.e., inducing limb movements, sensory feedback or physiological function restoring), and in the evaluation of the current stimuli properties according to the characteristics of the nerves surrounding tissue. Therefore, a review study on the main modeling and computational frameworks adopted to investigate peripheral nerve stimulation is an important instrument to support and drive future research works. To this aim, this paper deals with mathematical models of neural cells with a detailed description of ion channels and numerical simulations using finite element methods to describe the dynamics of electrical stimulation by implanted electrodes in peripheral nerve fibers. In particular, we evaluate different nerve cell models considering different ion channels present in neurons and provide a guideline on multiscale numerical simulations of electrical nerve fibers stimulation.

Hand motion analysis during robot-aided rehabilitation in chronic stroke.

A high percentage of post-stroke patients reports spasticity and no functional use of the upper limb. To adapt the therapy in the most patient-specific manner, it is of paramount importance to objectively assess motor improvement during rehabilitation therapy. In this paper, a quantitative evaluation of the results obtained by using a commercial exoskeletal glove for hand rehabilitation (i.e. Gloreha Sinfonia®) is performed. A camera-based calibration procedure for the bending sensors embedded in the Gloreha Sinfonia robotic glove for hand rehabilitation is introduced to retrieve the range of motion (i.e. the flexion angle excursion of the finger metacarpophalangeal joints) of the patients' hand. Once calibrated, the sensors embedded in the glove have been used to objectively assess the motor performance of chronic post-stroke patients that underwent a robotic treatment with the Gloreha Sinfonia glove. The preliminary results obtained on ten post-stroke patients demonstrated i) that the camera-based procedure permits to retrieve joints' angular values from bending sensors embedded in the glove ii) an improvement in motor performance.

Intraneural electrical stimulation of median nerve: a simulation study on sensory and motor fascicles.

Neuroprostheses can be an innovative solution to improve quality of life of upper limb amputees. In this framework, the recovery of sensory feedback is a property widely requested by amputee subjects. Neural prostheses are based on neural interfaces that allow delivering direct current stimuli to the nerve fibers. The study of the interaction between the nerve and the electrode is fundamental to investigate activation properties in the nerve. Furthermore, the results could provide useful insight into improve the design of the electrodes and to advance and ameliorate tactile sensations, elicited by these interfaces, obtaining tactile feedback more like natural sensations. This work aims at studying, by means of a FEM Neuron computational model, the axon fibers activation by means of neural stimulation provided through the intraneural electrodes DS-file. Three different types of stimulation waveforms (i.e. biphasic charge balanced stimulus with inter-pulse delay, biphasic charge balanced stimulus without inter-pulse delay, biphasic charge unbalanced stimulus with inter-pulse delay), three different nerve fascicles, i.e. two sensory and one motor fascicle, and ten distances from the electrode in the fascicles, are considered. The efficacy of the stimulation expressed as the percentage of activation of the fibers, and the safety, in terms of current intensity and used waveform, are studied in the previously described different conditions and the results are compared. The obtained results show that: i. stimulating a sensory fascicle with implanted active sites can activate a fascicle close to it, but not all the fascicles belonging to the same nerve. In fact, in the nerve considered in this study, a motor fascicle cannot be activated due to the values of the electrical potential which are too low to activate the fibers; ii. the current intensity necessary to activate fibers increases according to the distance from the source of the stimulus; iii. by using a biphasic charge unbalanced stimulus, the threshold to activate the fibers is lower than using the other tested waveforms. It is an important result because the stimulation is efficient and safer since current intensity is lower than the one used for the other two waveforms.

Application of the Tikhonov tomography method for the gas electron multiplier (GEM) system on experimental advanced superconducting tokamak.

A novel GEM (Gas Electron Multiplier) system has been installed on experimental advanced superconducting tokamak (EAST) which is used for collecting the line integral of the soft X-ray radiation (SXR) through a pinhole-collimated Beryllium window. The sightline of the 2-D GEM system is tangential to the toroidal field. To obtain the local SXR emission, the Tikhonov algorithm is applied for the imaging of the poloidal cross section emission in the vacuum vessel. In the meanwhile, the L-curve method is used to find an optimized solution of the regularization parameters. The tomography reliability has been tested with a known emission function where the error is also discussed. The tomography method has been coded as a graphic user interface for the fast analysis of GEM experimental data. The typical tomography results have been shown for the EAST shot (#79282) in this paper.

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.

Design and development of a sensorized cylindrical object for grasping assessment.

Aim of this work is to design and develop an instrumented cylindrical object equipped with force sensors, which is able to assess grasping performance of both human and robotic hands. The object is made of two concentric shells between which sixteen piezoresistive sensors have been located in order to measure the forces applied by the hand fingers during grasping. Furthermore, a magneto-inertial unit has been positioned inside the object for acquiring information about object orientation during manipulation. A wireless communication between the electronic boards, responsible for acquiring the data from the sensors, and a remote laptop has been guaranteed. The object has been conceived in such a way to be adopted for evaluating both power and precision grasps and for measuring the forces applied by each finger of the hand. In order to evaluate object performance, a finite element analysis for estimating the deformation of the external shell for different force values has been carried out. Moreover, to evaluate object sensitivity, a static analysis of the force transmitted by the external shell to the underlying sensors has been performed by varying the thickness of the shells. The obtained preliminary results have validated the feasibility of using the developed object for assessing grasping performed by human and robotic hands.

Development and preliminary testing of an instrumented object for force analysis during grasping.

This paper presents the design and realization of an instrumented object for force analysis during grasping. The object, with spherical shape, has been constructed with three contact areas in order to allow performing a tripod grasp. Force Sensing Resistor (FSR) sensors have been employed for normal force measurements, while an accelerometer has been used for slip detection. An electronic board for data acquisition has been embedded into the object, so that only the cables for power supply exit from it. Validation tests have been carried out for: (i) comparing the force measurements with a ground truth; (ii) assessing the capability of the accelerometer to detect slippage for different roughness values; (iii) evaluating object performance in grasp trials performed by a human subject.

Experimental validation of a reach-and grasp optimization algorithm inspired to human arm-hand control.

Taking inspiration from neurophysiological studies on synergies in the human grasping action, this paper tries to demonstrate that it is possible to find a general rule for performing a stable, human-like cylindrical grasp with a robotic hand. To this purpose, the theoretical formulation and the experimental validation of a reach-and-grasp algorithm for determining the optimal hand position and the optimal finger configuration for grasping a cylindrical object with known features are presented. The proposed algorithm is based on the minimization of an objective function expressed by the sum of the distances of the hand joints from the object surface. Algorithm effectiveness has preliminarily been tested by means of simulation trials. Experimental trials on a real arm-hand robotic system have then been carried out in order to validate the approach and evaluate algorithm performance.

Temperature dependence of exciton diffusion in conjugated polymers.

The temperature dependence of the exciton dynamics in a conjugated polymer is studied using time-resolved spectroscopy. Photoluminescence decays were measured in heterostructured samples containing a sharp polymer-fullerene interface, which acts as an exciton quenching wall. Using a 1D diffusion model, the exciton diffusion length and diffusion coefficient were extracted in the temperature range of 4-293 K. The exciton dynamics reveal two temperature regimes: in the range of 4-150 K, the exciton diffusion length (coefficient) of approximately 3 nm (approximately 1.5 x 10 (-4) cm2/s) is nearly temperature independent. Increasing the temperature up to 293 K leads to a gradual growth up to 4.5 nm (approximately 3.2 x 10 (-4) cm2/ s). This demonstrates that exciton diffusion in conjugated polymers is governed by two processes: an initial downhill migration toward lower energy states in the inhomogenously broadened density of states, followed by temperature activated hopping. The latter process is switched off below 150 K.