Paolo Ariano

Quantifying Forearm Muscle Activity during Wrist and Finger Movements by Means of Multi-Channel Electromyography

The study of hand and finger movement is an important topic with applications in prosthetics, rehabilitation, and ergonomics. Surface electromyography (sEMG) is the gold standard for the analysis of muscle activation. Previous studies investigated the optimal electrode number and positioning on the forearm to obtain information representative of muscle activation and robust to movements. However, the sEMG spatial distribution on the forearm during hand and finger movements and its changes due to different hand positions has never been quantified. The aim of this work is to quantify 1) the spatial localization of surface EMG activity of distinct forearm muscles during dynamic free movements of wrist and single fingers and 2) the effect of hand position on sEMG activity distribution. The subjects performed cyclic dynamic tasks involving the wrist and the fingers. The wrist tasks and the hand opening/closing task were performed with the hand in prone and neutral positions. A sensorized glove was used for kinematics recording. sEMG signals were acquired from the forearm muscles using a grid of 112 electrodes integrated into a stretchable textile sleeve. The areas of sEMG activity have been identified by a segmentation technique after a data dimensionality reduction step based on Non Negative Matrix Factorization applied to the EMG envelopes. The results show that 1) it is possible to identify distinct areas of sEMG activity on the forearm for different fingers; 2) hand position influences sEMG activity level and spatial distribution. This work gives new quantitative information about sEMG activity distribution on the forearm in healthy subjects and provides a basis for future works on the identification of optimal electrode configuration for sEMG based control of prostheses, exoskeletons, or orthoses. An example of use of this information for the optimization of the detection system for the estimation of joint kinematics from sEMG is reported.

A wireless address-event representation system for ATC-based multi-channel force wireless transmission

This paper extends Average Threshold Crossing (ATC) wireless transmission to a multi-channel case by using Address-Event Representation (AER) as the way to convey information. This is encoded in the timings of the transmitted packets which in turn carry the identifier of the event source. By integrating a Impulse RadioUltra Wide Band (IR-UWB) and choosing the proper protocol and modulation, we can aim to minimize the power consumption and provide error detection. The whole system, fully asynchronous, has been implemented in a full-custom chip; besides having multiple independent inputs, it can be configured both to deploy a multi-chip system (with a single receiver) and to optimize wireless transmission parameters. The paper concludes with additional theoretical simulations on the ATC scheme to justify further analyses for our specific application area which regards movement recognition.

Polymeric materials as artificial muscles: an overview

Purpose The accurate selection of materials and the fine tuning of their properties represent a fundamental aspect in the realization of new active systems able to produce actuating forces, such as artificial muscles. In this regard, exciting opportunities for the design of new advanced systems are offered by materials belonging to the emerging class of functional polymers: exploiting their actuation response, specific devices can be realized. Along this direction, materials showing either shape-memory effect (SME) or shape-change effect (SCE) have been the subject of extensive studies aimed at designing of actuators as artificial muscles. Here, we concisely review active polymers in terms of properties and main applications in artificial muscle design. Structure The main aspects related to material properties in both shape-memory polymers (SMPs) and electroactive polymers (EAPs) are reviewed, based on recent scientific literature. SME in thermally activated SMPs is presented by preliminarily providing a definition that encompasses the new theories regarding their fundamental properties. EAPs are briefly presented, describing the working mechanisms and highlighting the main properties and drawbacks, in view of their application as actuators. For both classes of materials, some key examples of effective application in artificial muscles are offered. Outlook The potential in polymer architecture design for the fabrication of actively moving systems is described to give a perspective on the main achievements and new research activities.

Proportional estimation of finger movements from high-density surface electromyography

BackgroundThe importance to restore the hand function following an injury/disease of the nervous system led to the development of novel rehabilitation interventions. Surface electromyography can be used to create a user-driven control of a rehabilitation robot, in which the subject needs to engage actively, by using spared voluntary activation to trigger the assistance of the robot.MethodsThe study investigated methods for the selective estimation of individual finger movements from high-density surface electromyographic signals (HD-sEMG) with minimal interference between movements of other fingers. Regression was evaluated in online and offline control tests with nine healthy subjects (per test) using a linear discriminant analysis classifier (LDA), a common spatial patterns proportional estimator (CSP-PE), and a thresholding (THR) algorithm. In all tests, the subjects performed an isometric force tracking task guided by a moving visual marker indicating the contraction type (flexion/extension), desired activation level and the finger that should be moved. The outcome measures were mean square error (nMSE) between the reference and generated trajectories normalized to the peak-to-peak value of the reference, the classification accuracy (CA), the mean amplitude of the false activations (MAFA) and, in the offline tests only, the Pearson correlation coefficient (PCORR).ResultsThe offline tests demonstrated that, for the reduced number of electrodes (≤24), the CSP-PE outperformed the LDA with higher precision of proportional estimation and less crosstalk between the movement classes (e.g., 8 electrodes, median MAFAu2009~u20090.6 vs. 1.1xa0%, median nMSEu2009~u20094.3 vs. 5.5xa0%). The LDA and the CSP-PE performed similarly in the online tests (median nMSEu2009<u20093.6xa0%, median MAFAu2009<u20090.7xa0%), but the CSP-PE provided a more stable performance across the tested conditions (less improvement between different sessions). Furthermore, THR, exploiting topographical information about the single finger activity from HD-sEMG, provided in many cases a regression accuracy similar to that of the pattern recognition techniques, but the performance was not consistent across subjects and fingers.ConclusionsThe CSP-PE is a method of choice for selective individual finger control with the limited number of electrodes (<24), whereas for the higher resolution of the recording, either method (CPS-PA or LDA) can be used with a similar performance. Despite the abundance of detection points, the simple THR showed to be significantly worse compared to both pattern recognition/regression methods. Nevertheless, THR is a simple method to apply (no training), and it could still give satisfactory performance in some subjects and/or simpler scenarios (e.g., control of selected fingers). These conclusions are important for guiding future developments towards the clinical application of the methods for individual finger control in rehabilitation robotics.

Coupling Resistive Switching Devices with Neurons: State of the Art and Perspectives

Here we provide the state-of-the-art of bioelectronic interfacing between biological neuronal systems and artificial components, focusing the attention on the potentiality offered by intrinsically neuromorphic synthetic devices based on Resistive Switching (RS). Neuromorphic engineering is outside the scopes of this Perspective. Instead, our focus is on those materials and devices featuring genuine physical effects that could be sought as non-linearity, plasticity, excitation, and extinction which could be directly and more naturally coupled with living biological systems. In view of important applications, such as prosthetics and future life augmentation, a cybernetic parallelism is traced, between biological and artificial systems. We will discuss how such intrinsic features could reduce the complexity of conditioning networks for a more natural direct connection between biological and synthetic worlds. Putting together living systems with RS devices could represent a feasible though innovative perspective for the future of bionics.

Commercial tactile sensors for hand exoskeletons: practical considerations for ultra-low cost and very-low complexity read-out

In the last two decades, wearable robots have emerged as human-oriented devices to complement, substitute or enhance human capabilities and, more specifically, empower or replace a human limb [1], [2]. Among the most complex and interesting limbs to assist, the hand represents perhaps the biggest challenge, because of its primary role in environment exploration, stimuli sensing and object manipulation [3]. Hence, the development of wearable and rehabilitative exoskeletons is increasingly attracting attention to help finger movements in free motion and assist the user with grasping. This paper shows that a simple underpowered digital oscillator electronic interface takes advantage of the capacitive variations in commercial piezoresistive transducers to sense applied pressure. Furthermore, thanks to the analysis of the static performance, practical considerations are drawn about the use of commercial sensors and a read out circuit (ROC) to be exploited in a control system for hand exoskeletons (Fig. 1).

Building the space scale or how to weigh a person with no gravity

Since the very beginning of space exploration, cosmonauts have suffered from weight losses which need to be particularly monitored during long term missions in space stations to insure their health and well being. In 1965-6 Thornton successfully built a device able to measure the body mass of cosmonauts in the micro-gravity space environment using passive linear spring-mass oscillators. Since then, space stations have been equipped with labs containing, among others, bulky devices like Thorntons. In this work we report recent advancements in computer vision algorithms allowing us to estimate the weight of a person within 4% error using 2D and 3D data extracted from a low-cost Kinect RGBD camera output.

Innovative Hand Exoskeleton Design for Extravehicular Activities in Space

Environmental conditions and pressurized spacesuits expose astronauts to problems of fatigue during lengthy extravehicular activities, with adverse impacts especially on the dexterity, force and endurance of the hands and arms. A state-of-the-art exploration in the field of hand exoskeletons revealed that available products are unsuitable for space applications because of their bulkiness and mass. This book proposes a novel approach to the development of hand exoskeletons, based on an innovative soft robotics concept that relies on the exploitation of electroactive polymers operating as sensors and actuators, on a combination of electromyography and mechanomyography for detection of the users will and on neural networks for control. The result is a design that should enhance astronauts performance during extravehicular activities. In summary, the advantages of the described approach are a low-weight, high-flexibility exoskeleton that allows for dexterity and compliance with the users will.

Actuators based on intrinsic conductive polymers/carbon nanoparticles nanocomposites

New polyaniline (PANi) synthesis was performed starting from non-toxic N-phenil-p-phenylenediamine (aniline dimer) using reverse addition of monomer to oxidizing agent, the synthesis allows to produce highly soluble PANi. Several types of doped PANi were prepared to be used on electromechanical active actuators. Different techniques were used to include carbon nanoparticles such as carbon nanotubes and graphene. Bimorph solid state ionic actuators were prepared with these novel nanocomposites using a variety of supporting polymers.

Object tracking with adaptive HOG detector and adaptive Rao-Blackwellised particle filter

Scenarios for a manned mission to the Moon or Mars call for astronaut teams to be accompanied by semiautonomous robots. A prerequisite for human-robot interaction is the capability of successfully tracking humans and objects in the environment. In this paper we present a system for real-time visual object tracking in 2D images for mobile robotic systems. The proposed algorithm is able to specialize to individual objects and to adapt to substantial changes in illumination and object appearance during tracking. The algorithm is composed by two main blocks: a detector based on Histogram of Oriented Gradient (HOG) descriptors and linear Support Vector Machines (SVM), and a tracker which is implemented by an adaptive Rao-Blackwellised particle filter (RBPF). The SVM is re-trained online on new samples taken from previous predicted positions. We use the effective sample size to decide when the classifier needs to be re-trained. Position hypotheses for the tracked object are the result of a clustering procedure applied on the set of particles. The algorithm has been tested on challenging video sequences presenting strong changes in object appearance, illumination, and occlusion. Experimental tests show that the presented method is able to achieve near real-time performances with a precision of about 7 pixels on standard video sequences of dimensions 320 × 240.