Generation of virus like particles for epizootic hemorrhagic disease virus

Epizootic hemorrhagic disease virus (EHDV) is a distinct species within the genus Orbivirus, within the family Reoviridae. The epizootic hemorrhagic disease virus genome comprises ten segments of linear, double stranded (ds) RNA, which are packaged within each virus particle. The EHDV virion has a three layered capsid-structure, generated by four major viral proteins: VP2 and VP5 (outer capsid layer); VP7 (intermediate, core-surface layer) and VP3 (innermost, sub-core layer). Although EHDV infects cattle sporadically, several outbreaks have recently occurred in this species in five Mediterranean countries, indicating a potential threat to the European cattle industry. EHDV is transmitted by biting midges of the genus Culicoides, which can travel long distances through wind-born movements (particularly over water), increasing the potential for viral spread in new areas/countries. Expression systems to generate self-assembled virus like particles (VLPs) by simultaneous expression of the major capsid-proteins, have been established for several viruses (including bluetongue virus). This study has developed expression systems for production of EHDV VLPs, for use as non-infectious antigens in both vaccinology and serology studies, avoiding the risk of genetic reassortment between vaccine and field strains and facilitating large scale antigen production. Genes encoding the four major-capsid proteins of a field strain of EHDV-6, were isolated and cloned into transfer vectors, to generate two recombinant baculoviruses. The expression of these viral genes was assessed in insect cells by monitoring the presence of specific viral mRNAs and by western blotting. Electron microscopy studies confirmed the formation and purification of assembled VLPs

Decoding of grasping information from neural signals recorded using peripheral intrafascicular interfaces

The restoration of complex hand functions by creating a novel bidirectional link between the nervous system and a dexterous hand prosthesis is currently pursued by several research groups. This connection must be fast, intuitive, with a high success rate and quite natural to allow an effective bidirectional flow of information between the user's nervous system and the smart artificial device. This goal can be achieved with several approaches and among them, the use of implantable interfaces connected with the peripheral nervous system, namely intrafascicular electrodes, is considered particularly interesting

Cognitive vision system for control of dexterous prosthetic hands: Experimental evaluation

<p>Abstract</p> <p>Background</p> <p>Dexterous prosthetic hands that were developed recently, such as SmartHand and i-LIMB, are highly sophisticated; they have individually controllable fingers and the thumb that is able to abduct/adduct. This flexibility allows implementation of many different grasping strategies, but also requires new control algorithms that can exploit the many degrees of freedom available. The current study presents and tests the operation of a new control method for dexterous prosthetic hands.</p> <p>Methods</p> <p>The central component of the proposed method is an autonomous controller comprising a vision system with rule-based reasoning mounted on a dexterous hand (CyberHand). The controller, termed cognitive vision system (CVS), mimics biological control and generates commands for prehension. The CVS was integrated into a hierarchical control structure: 1) the user triggers the system and controls the orientation of the hand; 2) a high-level controller automatically selects the grasp type and size; and 3) an embedded hand controller implements the selected grasp using closed-loop position/force control. The operation of the control system was tested in 13 healthy subjects who used Cyberhand, attached to the forearm, to grasp and transport 18 objects placed at two different distances.</p> <p>Results</p> <p>The system correctly estimated grasp type and size (nine commands in total) in about 84% of the trials. In an additional 6% of the trials, the grasp type and/or size were different from the optimal ones, but they were still good enough for the grasp to be successful. If the control task was simplified by decreasing the number of possible commands, the classification accuracy increased (e.g., 93% for guessing the grasp type only).</p> <p>Conclusions</p> <p>The original outcome of this research is a novel controller empowered by vision and reasoning and capable of high-level analysis (i.e., determining object properties) and autonomous decision making (i.e., selecting the grasp type and size). The automatic control eases the burden from the user and, as a result, the user can concentrate on what he/she does, not on how he/she should do it. The tests showed that the performance of the controller was satisfactory and that the users were able to operate the system with minimal prior training.</p

Principal components analysis based control of a multi-dof underactuated prosthetic hand

<p>Abstract</p> <p>Background</p> <p>Functionality, controllability and cosmetics are the key issues to be addressed in order to accomplish a successful functional substitution of the human hand by means of a prosthesis. Not only the prosthesis should duplicate the human hand in shape, functionality, sensorization, perception and sense of body-belonging, but it should also be controlled as the natural one, in the most intuitive and undemanding way. At present, prosthetic hands are controlled by means of non-invasive interfaces based on electromyography (EMG). Driving a multi degrees of freedom (DoF) hand for achieving hand dexterity implies to selectively modulate many different EMG signals in order to make each joint move independently, and this could require significant cognitive effort to the user.</p> <p>Methods</p> <p>A Principal Components Analysis (PCA) based algorithm is used to drive a 16 DoFs underactuated prosthetic hand prototype (called CyberHand) with a two dimensional control input, in order to perform the three prehensile forms mostly used in Activities of Daily Living (ADLs). Such Principal Components set has been derived directly from the artificial hand by collecting its sensory data while performing 50 different grasps, and subsequently used for control.</p> <p>Results</p> <p>Trials have shown that two independent input signals can be successfully used to control the posture of a real robotic hand and that correct grasps (in terms of involved fingers, stability and posture) may be achieved.</p> <p>Conclusions</p> <p>This work demonstrates the effectiveness of a bio-inspired system successfully conjugating the advantages of an underactuated, anthropomorphic hand with a PCA-based control strategy, and opens up promising possibilities for the development of an intuitively controllable hand prosthesis.</p

Real-time myoelectric control of a multi-fingered hand prosthesis using principal components analysis

<p>Abstract</p> <p>Background</p> <p>In spite of the advances made in the design of dexterous anthropomorphic hand prostheses, these sophisticated devices still lack adequate control interfaces which could allow amputees to operate them in an intuitive and close-to-natural way. In this study, an anthropomorphic five-fingered robotic hand, actuated by six motors, was used as a prosthetic hand emulator to assess the feasibility of a control approach based on Principal Components Analysis (PCA), specifically conceived to address this problem. Since it was demonstrated elsewhere that the first two principal components (PCs) can describe the whole hand configuration space sufficiently well, the controller here employed reverted the PCA algorithm and allowed to drive a multi-DoF hand by combining a two-differential channels EMG input with these two PCs. Hence, the novelty of this approach stood in the PCA application for solving the challenging problem of best mapping the EMG inputs into the degrees of freedom (DoFs) of the prosthesis.</p> <p>Methods</p> <p>A clinically viable two DoFs myoelectric controller, exploiting two differential channels, was developed and twelve able-bodied participants, divided in two groups, volunteered to control the hand in simple grasp trials, using forearm myoelectric signals. Task completion rates and times were measured. The first objective (assessed through one group of subjects) was to understand the effectiveness of the approach; i.e., whether it is possible to drive the hand in real-time, with reasonable performance, in different grasps, also taking advantage of the direct visual feedback of the moving hand. The second objective (assessed through a different group) was to investigate the intuitiveness, and therefore to assess statistical differences in the performance throughout three consecutive days.</p> <p>Results</p> <p>Subjects performed several grasp, transport and release trials with differently shaped objects, by operating the hand with the myoelectric PCA-based controller. Experimental trials showed that the simultaneous use of the two differential channels paradigm was successful.</p> <p>Conclusions</p> <p>This work demonstrates that the proposed two-DoFs myoelectric controller based on PCA allows to drive in real-time a prosthetic hand emulator into different prehensile patterns with excellent performance. These results open up promising possibilities for the development of intuitive, effective myoelectric hand controllers.</p

Microactuators for microrobots: a critical survey

The authors present a critical survey of some representative technologies which are candidates for the development of microactuators for microrobots. Since the field of 'microrobotics' is an entirely new one, some concepts and definitions are given first; in particular, a distinction between 'micromachines' and 'microrobots' is proposed. Then, a further classification is proposed between three different types of robots: the 'miniature' robot, the 'microrobot' and the 'nanorobot', and their expected performances and fields of applications are discussed. The need for developing dedicated miniature actuators and microactuators emerges clearly from this discussion, together with the main requirements for this class of 'new' actuators. Finally, some significant examples of implementation of microactuators are illustrated, and the main advantages and limitations of each technology are discussed

Non-traditional technologies for microfabrication

Although silicon planar technology has generated the field of micromechanics, it has been realized that this technology has intrinsic limitations for the fabrication of truly so micromechanisms. A number of alternative technologies based either on silicon or on different materials are presently investigated in order to overcome the limitations of planar silicon technology. This paper outlines the motivations for developing new microfabrication technologies, especially those that are considered as 'non-traditional' in the microelectronics domain, and the perspectives offered by this approach for fabricating miniature, micro and nanodevices. Four representative 'non-traditional' technologies are considered. LIGA process, micro electro-discharge machining (EDM), micro stereo lithography, and the combination of biological and artificial microfabricated structures ('hybrid' technologies)