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The development of interfaces linking the human nervous system with artificial devices is an important area of research and several groups are now addressing it. Interfaces represent the key enabling technology for the development of devices usable for the restoration of motor and sensory function in subjects affected by neurological disorders, injuries or amputations. For example, current hand prostheses use electromyographic (EMG) signals to extract volitional commands but this limits the possibility of controlling several degrees of freedom and of delivering sensory feedback. To achieve these goals, implantable neural interfaces are required. Among the candidate interfaces with the peripheral nervous system intra-neural electrodes seem to be an interesting solution due to their bandwidth and ability to access volition and deliver sensory feedback. However, several drawbacks have to be addressed in order to increase their usability. In this paper, experiments to address many of these issues are presented as part of the development of a new generation of intra-neural electrodes. The results showed seem to confirm that these new interfaces seem to have interesting properties and that they can represent a significant improvement of the state of the art. Extensive experiments will be carried out in the future to validate these results.

Background: In the past, several studies showed the existence of a synergistic behavior between elbow and shoulder joints during reaching movements in able-bodied subjects. The aim of this paper was to characterize the modifications of upper arm synergies during reaching induced by stroke., Methods: Ten able-bodied right-handed subjects, eight right-handed subjects with hemiparesis affecting the right (dominant) upper limb participated in the experiments. The kinematics of shoulder and elbow joints have been recorded in all the participants during selected reaching movements. From the eight-like plots characterizing the relationship between shoulder and elbow angular velocities, a topological parameter (named as C approximately ) representing the linear approximation of the synergy between the two angular velocities has been extracted., Findings: The results of these experiments showed that C approximately could be used as a figure of merit for the comparison of performance in able-bodied and hemiparetic persons. The hemiparetic subjects showed a significantly higher spreading of the values of C approximately for the different reaching movements when compared with the performance of able-bodied subjects., Interpretation: This work showed that hemiparesis modified upper arm synergies and could provide a protocol for the assessment of upper limb function. Moreover, important applications of this method could be found in the development of biomimetic algorithms for the control of upper extremities during reaching in humanoid robots, and in the design of customized "games" in neurorehabilitation procedures implemented by using robotic and mechatronic platforms.

Considerable scientific and technological efforts have been devoted to develop neuroprostheses and hybrid bionic systems that link the human nervous system with electronic or robotic prostheses, with the main aim of restoring motor and sensory functions in disabled patients. A number of neuroprostheses use interfaces with peripheral nerves or muscles for neuromuscular stimulation and signal recording. Herein, we provide a critical overview of the peripheral interfaces available and trace their use from research to clinical application in controlling artificial and robotic prostheses. The first section reviews the different types of non-invasive and invasive electrodes, which include surface and muscular electrodes that can record EMG signals from and stimulate the underlying or implanted muscles. Extraneural electrodes, such as cuff and epineurial electrodes, provide simultaneous interface with many axons in the nerve, whereas intrafascicular, penetrating, and regenerative electrodes may contact small groups of axons within a nerve fascicle. Biological, technological, and material science issues are also reviewed relative to the problems of electrode design and tissue injury. The last section reviews different strategies for the use of information recorded from peripheral interfaces and the current state of control neuroprostheses and hybrid bionic systems.

This paper presents two robot devices for use in the rehabilitation of upper limb movements and reports the quantitative parameters obtained to characterize the rate of improvement, thus allowing a precise monitoring of patient's recovery. A one degree of freedom (DoF) wrist manipulator and a two-DoF elbow-shoulder manipulator were designed using an admittance control strategy; if the patient could not move the handle, the devices completed the motor task. Two groups of chronic post-stroke patients (G1 n = 7, and G2 n = 9) were enrolled in a three week rehabilitation program including standard physical therapy (45 min daily) plus treatment by means of robot devices, respectively, for wrist and elbow-shoulder movements (40 min, twice daily). Both groups were evaluated by means of standard clinical assessment scales and a new robot measured evaluation metrics that included an active movement index quantifying the patient's ability to execute the assigned motor task without robot assistance, the mean velocity, and a movement accuracy index measuring the distance of the executed path from the theoretic one. After treatment, both groups improved their motor deficit and disability. In G1, there was a significant change in the clinical scale values (p < 0.05) and range of motion wrist extension (p < 0.02). G2 showed a significant change in clinical scales (p < 0.01), in strength (p < 0.05) and in the robot measured parameters (p < 0.01). The relationship between robot measured parameters and the clinical assessment scales showed a moderate and significant correlation (r > 0.53 p < 0.03). Our findings suggest that robot-aided neurorehabilitation may improve the motor outcome and disability of chronic post-stroke patients. The new robot measured parameters may provide useful information about the course of treatment and its effectiveness at discharge.

The main goal of this paper is to study the feasibility of a novel implantable micro-system able to record information about tendon sliding movements by using contactless measurement devices (magnetic sources and sensors). The system, named "Biomechatronic Position Transducer" (BPT), can be used for the implementation of advanced control strategies in neuroprostheses. After a preliminary analysis based on finite element model simulations, an experimental setup was developed in order to simulate the recording conditions (the sensors fixed to the bones and the magnetic sources placed on the tendons). In order to limit the number of implanted components of the system, a fuzzy Mamdani-like architecture was developed to extract the information from the raw data. The results confirm the possibility of using the presented approach for developing an implantable micro-sensor able to extract kinematic information useful for the control of neuroprostheses. Future works will go in the direction of integrating and testing the sensors and the electronic circuitry (to provide power supply and to record the data) during in vitro and in situ experiments.

The aim of the experiment was to study possible differences between the kinematic strategies for the "involuntary" arm lowering of hypnotized highly susceptible subjects (H-Highs) and for the voluntary movement of non-hypnotizable simulators (Sims) during suggestions of arm heaviness (Part I). In addition, a comparison between awake susceptible subjects (W-Highs) and H-Highs was carried out to clarify the specific role of the hypnotic state and hypnotizability (Part II). Subjects' absorption and attentional/imagery capabilities were evaluated through neuropsychological tests. Their arm movements were monitored three-dimensionally at hand, wrist and elbow level through a Polhemus Fastrack system. A final interview collected self-reports concerning the perception of movement involuntariness. Neuropsychological tests showed better "absorption" and imagery capabilities in Highs. In the interview, H-Highs perceived a higher involvement in the task and greater involuntariness and difficulties in contrasting the arm lowering than the Sims. Kinematic analysis showed significant differences between H-Highs and Sims for arm displacements along the vertical axis and on the horizontal plane. In fact, the former lowered the left arm earlier and to a greater degree than the right arm; on the horizontal plane, a forearm flexion was observed for H-Highs on the right side. On comparing W-Highs and H-Highs, hypnosis appeared to magnify the waking motor strategies, but also to induce specific changes, mainly concerning the horizontal plane. These results cannot be interpreted on the basis of "role playing" and socio-cognitive factors. They are believed to be due to a balance between the effectiveness of the frontal executive control towards the selection of behaviors and movement automaticity, which is in line with the neo-dissociation theory of hypnosis.

Objective: To design and test a protocol for the assessment of neck movements in patients affected by cervical dystonia by using an electromagnetic system. This approach could overcome the limits of the current assessment scales in this specific field., Background: Initial assessment and function recovery during treatments are diagnosed by the clinician using outcome scales which present many drawbacks in terms of easiness of use, sensitivity, and reliability., Design: A three-dimensional motion analysis system was used to record six different head movements., Methods: Six able-bodied subjects and 10 subjects affected by cervical dystonia participated in this study. For the different head movements three kinematic parameters (a symmetry index and two indexes related to the reduction of the range of motion) have been extracted in order to compare the performance of able-bodied and disabled persons., Results: The features selected allowed highlighting of the differences between able-bodied and disabled subjects for the degrees of freedom of the neck., Conclusions: Using a motion analysis system, three kinematic features were extracted from head movements. They seem to allow a more objective assessment of the disability and a more appropriated strategy for the management of patients affected by cervical dystonia.

Subjects highly (Highs) and low susceptible to hypnosis (Lows) show different imagery and attentional capabilities and also peculiar somatomotor, vegetative and electroencephalographic differences in basal and task conditions. Since attention is one of the main component of hypnotic susceptibility and also a relevant factor for postural control, the aim of the experiment was to study actual differences between Highs and Lows at the eyes closure during upright stance. Visual and motor imagery as well as attentional/disattentional capabilities were evaluated through psychological tests. Posture was monitored though Elite systems during upright stance with open and closed eyes. At the eyes closure, Highs and Lows exhibited a different body sway modulation. Possible different compensation mechanisms are suggested for the two groups and interactions between attentional/arousal systems responsible of hypnotic phenomenology and postural control are underlined.

This paper presents the design methods followed in order to overcome the limits of the current prosthetic hands. The prosthesis biomechatronic approach arises from the knowledge of the biological system, assumed validated by its natural evolution. Nevertheless, the state of the art of technology, actuators, sensors, electronics and software, forces some trade-off in the implementation of the prototypes. The current hand prototype constitutes the platform used to direct all efforts of the prosthesis designer to the final goal: the cybernetic hand directly connected to the nervous system.

In this paper, we presented a sensorized thumb based on a matrix of piezoresistive force sensors, with an acquisition unit and a special wearing support. The sensor was calibrated and then the device was tested during different tasks simulating activities of daily living performed by seven able-bodied subjects. By means of these experiments, we verified that the device proposed can be used to extract force information during grasp. In fact, the device was able to provide useful force information in the 98% of the trials with a good repeatability during all the different conditions. Moreover, we evaluated the patterns obtained during the different grasping tasks. The palmar grasps were performed in a similar manner, whereas the lateral pinch and the spherical volar grip were more different. This device can provide force information with good performance and acceptability and it can be used for force closed-loop control of hand neuroprostheses.

We developed an automated and objective method to measure posture and voluntary movements in patients with cervical dystonia using Fastrack, an electromagnetic system consisting of a stationary transmitter station and four sensors. The junction lines between the sensors attached to the head produced geometrical figures on which the corresponding aspects of the head were superimposed. The head position in the space was reconstructed and observed from axial, sagittal, and coronal planes. Four patients with cervical dystonia and 6 healthy subjects were studied. Each patient was representative of one of the typical patterns of cervical dystonia. The study allowed the authors to collect quantitative data on posture and range of motion of the head. This pilot study demonstrates the efficacy of the Fastrack system to objectively measure the head position in cervical dystonia patients.

In the recent past, many efforts have been carried out in order to evaluate the feasibility of implementing closed-loop controlled neuroprostheses based on the processing of sensory electroneurographic (ENG) signals. The success of these techniques mostly relies on the development of processing algorithms capable of extracting the necessary kinematic information from these signals. Soft-computing algorithms can be very useful when dealing with the complexity of the neuromuscular system because of their generalization ability and model-free structure. In this paper, these techniques were used to extract angular position information from the ENG signals recorded from muscle afferents in animal model using cuff electrodes. Specifically, a genetic algorithm-based dynamic nonsingleton fuzzy logic system (named GA-DNSFLS) was developed and tested on different types of angular trajectories (characterized by small or large angular excursions). In particular, two different Takagi-Sugeno-Kang (TSK)-like structures were used in the consequent part of the neuro-fuzzy model in order to verify which one could improve the generalization abilities (intrasubject and intersubject). The results showed that the GA-DNSFLS was able to reconstruct the trajectories giving interesting results in terms of correlation between the actual and the predicted trajectories for small excursion movements during intrasubject and intersubject tests. Particularly, one of the TSK models showed better results in terms of intersubject generalization. The simulations conducted with the large excursion movements led in some cases to interesting results but further experiments are necessary in order to analyze this point more in deep.

The aim of this paper was to analyse how the strategies implemented by the Central Nervous System to control the hand during grasping are modified under microgravity conditions. Two right-handed subjects carried out simple grasping tasks during parabolic flights. The trajectories of the fingers of the hand were recorded using a sensorised glove and processed in order to extract a variable (here indicated as K) which can indicated the degree of synergies existing among the fingers. The results showed that K was quite small during the trial at 1g while becoming significantly greater than 1 during the first parabolas. Then, the value k decreased to the values at 1 g after some parabolas. These results suggested a possible adaptation process of the manipulation abilities during the permanence at 0g conditions. Future extensive trials will be performed in order to confirm these preliminary results.

The human hand is a complex system, with a large number of degrees of freedom (DoFs), sensors embedded in its structure, actuators and tendons, and a complex hierarchical control. Despite this complexity, the efforts required to the user to carry out the different movements is quite small (albeit after an appropriate and lengthy training). On the contray, prosthetic hands are just a pale replication of the natural hand, with significantly reduced grasping capabilities and no sensory information delivered back to the user. Several attempts have been carried out to develop multifunctional prosthetic devices controlled by electromyographic (EMG) signals (myoelectric hands), harness (kinematic hands), dimensional changes in residual muscles, and so forth, but none ofthese methods permits the "natural" control of more than two DoFs. This article presents a review of the traditional methods used to control artificial hands by means of EMG signal, in both the clinical and research contexts, and introduces what could be the future developments in the control strategy of these devices.

Current prosthetic hands are basically simple grippers with one or two degrees of freedom, which barely restore the capability of the thumb-index pinch. Although most amputees consider this performance as acceptable for usual tasks, there is ample room for improvement by exploiting recent progresses in mechatronics design and technology. We are developing a novel prosthetic hand featured by multiple degrees of freedom, tactile sensing capabilities, and distributed control. Our main goal is to pursue an integrated design approach in order to fulfill critical requirements such as cosmetics, controllability, low weight, low energy consumption and noiselessness. This approach can be synthesized by the definition "biomechatronic design", which means developing mechatronic systems inspired by living beings and able to work harmoniously with them. This paper describes the first implementation of one single finger of a future biomechatronic hand. The finger has a modular design, which allows to obtain hands with different degrees of freedom and grasping capabilities. Current developments include the implementation of a hand comprising three fingers (opposing thumb, index and middle) and an embedded controller.

This paper is part of a project whose aim is the implementation of closed-loop control of ankle angular position during functional electrical stimulation (FES) assisted standing in paraplegic subjects using natural sensory information. In this paper, a neural fuzzy (NF) model is implemented to extract angular position information from the electroneurographic signals recorded from muscle afferents using cuff electrodes in an animal model. The NF model, named dynamic nonsingleton fuzzy logic system is a Mamdani-like fuzzy system, implemented in the framework of recurrent neural networks. The fuzzification procedure implemented was the nonsingleton technique which has been shown in previous works to be able to take into account the uncertainty in the data. The proposed algorithm was tested in different situations and was able to predict reasonably well the ankle angular trajectories especially for small excursions (as during standing) and when the stimulation sites are far from the registration sites. This suggests it may be possible to use activity from muscle afferents recorded with cuff electrodes for FES closed-loop control of ankle position during quite standing.

We evaluate the performance of a variety of neural and fuzzy networks for discrimination among three planar arm-pointing movements by means of electromyographic (EMG) signals, when learning is based on small-sized training sets. The aim of this work is to underline the importance that the sparse data problem has in designing pattern classifiers with good generalisation properties. The results indicate that one of the proposed fuzzy networks is more robust than the other classifiers when working with small training sets.

A modified adaptive Takagi-Sugeno (TS) fuzzy logic controller (FLC) is proposed that allows a simulated elbow-like biomechanical system to accurately track sigmoidal and sinusoidal trajectories in the sagittal plane. The work is a first effort towards the implementation of a system to restore elbow movements in quadriplegics using functional neuromuscular stimulation. The single-joint musculo-skeletal system is composed of a co-contractable pair of electrically stimulated muscles; the muscle model accounts for the increase in fatigue during the tracking exercise. In the proposed controller structure, a reinforcement learning scheme is used to accomplish the parameter tuning, and the parameter projection algorithm guarantees the system stability during the adaptation process. The controller performance is evaluated using computer simulation experiments and compared with the performance achievable when a standard proportional-integrative-derivative (PID) controller is employed for the same application. The modified adaptive TSFLC outperforms the PID controller in all tested situations, with a clear-cut advantage in the case of high-frequency sinusoidal trajectories (angular frequencies spanning the interval 8-12 rad s-1). The standard controller suffers from a dramatic increase in root mean square (RMS) tracking error above the value at 8 rad s-1, e.g. ERMS > or = 0.013, whereas the correlation coefficient between the actual and desired trajectory falls almost to zero, starting from the value rho approximately equal to 0.97 at 8 rad s-1. On the other hand, the adaptive TSFLC yields ERMS < or = 0.015, with rho > or = 0.78, over the whole range of tested angular frequencies.

In this paper, a hybrid approach is presented for discriminating a few upper limb movements by processing the electromyographic (EMG) signals from selected shoulder muscles. Statistical techniques, such as the Generalized Likelihood Ratio test, the Principal Component Analysis, autoregressive parametric modeling techniques and cepstral analysis techniques, combined with a fuzzy logic based classifier (the Abe-Lan network) are used to construct low-dimensional feature spaces with high classification rates. The experimental results show the ability of the algorithm to correctly classify all the EMG patterns related to the selected planar arm pointing movements. Moreover, the structure presented offers promise for real-time applications because of the low computation costs of the overall algorithm.

A class of implantable, regeneration-type neural interfaces (NI's) for mammalian peripheral nerve recording and stimulation were developed using different fabrication processes and integrating purposely designed components. A typical NI comprises three main components: 1) a microfabricated silicon die incorporating a microelectrode array on multiple through-holes, 2) a polymer guidance channel housing the die, and 3) a flexible flat cable connecting the die to an external electronic circuitry. The design and fabrication of the NI's were aimed at achieving long term, reliable implants by taking into careful account the biological, electrical, and mechanical requirements of the specific implant site. Different versions of the NI were fabricated and implanted between the severed ends of the sciatic nerve in a mammalian animal model (rabbit). Morphological and histological evidence showed that nerves regenerated through the NI's and electrophysiological results demonstrated the recovery of electrical functionality. Moreover, the NI's allowed stimulation of the regenerated nerve producing a visible leg/foot contraction. The NI's presented in this paper are being further improved in the authors' laboratories with the ultimate goal of allowing the control of nerve motor and sensory functions in future prosthetic devices.

The Generalized Likelihood Ratio (GLR) test is proposed for estimating the time instant of muscle contraction onset via electromyographic (EMG) signal processing. In contrast to commonly used threshold-based estimation methods, the proposed algorithm proves to be reasonably accurate even for low levels of EMG activity; the improved behaviour of the GLR test comes with just a modest increase in the computational complexity. A set of computer simulation experiments are presented, where the proposed algorithm and two different threshold-based estimators are studied; also, we discuss the results of analysing the EMG recordings of selected proximal muscles of the upper limb in a hemiparetic subject.