Clinical Features to Predict the Use of a sEMG Wearable Device (REMO®) for Hand Motor Training of Stroke Patients: A Cross-Sectional Cohort Study.

After stroke, upper limb motor impairment is one of the most common consequences that compromises the level of the autonomy of patients. In a neurorehabilitation setting, the implementation of wearable sensors provides new possibilities for enhancing hand motor recovery. In our study, we tested an innovative wearable (REMO®) that detected the residual surface-electromyography of forearm muscles to control a rehabilitative PC interface. The aim of this study was to define the clinical features of stroke survivors able to perform ten, five, or no hand movements for rehabilitation training. 117 stroke patients were tested: 65% of patients were able to control ten movements, 19% of patients could control nine to one movement, and 16% could control no movements. Results indicated that mild upper limb motor impairment (Fugl-Meyer Upper Extremity ≥ 18 points) predicted the control of ten movements and no flexor carpi muscle spasticity predicted the control of five movements. Finally, severe impairment of upper limb motor function (Fugl-Meyer Upper Extremity > 10 points) combined with no pain and no restrictions of upper limb joints predicted the control of at least one movement. In conclusion, the residual motor function, pain and joints restriction, and spasticity at the upper limb are the most important clinical features to use for a wearable REMO® for hand rehabilitation training.

Towards NIRS-based hand movement recognition.

This work reports on preliminary results about on hand movement recognition with Near InfraRed Spectroscopy (NIRS) and surface ElectroMyoGraphy (sEMG). Either basing on physical contact (touchscreens, data-gloves, etc.), vision techniques (Microsoft Kinect, Sony PlayStation Move, etc.), or other modalities, hand movement recognition is a pervasive function in today environment and it is at the base of many gaming, social, and medical applications. Albeit, in recent years, the use of muscle information extracted by sEMG has spread out from the medical applications to contaminate the consumer world, this technique still falls short when dealing with movements of the hand. We tested NIRS as a technique to get another point of view on the muscle phenomena and proved that, within a specific movements selection, NIRS can be used to recognize movements and return information regarding muscles at different depths. Furthermore, we propose here three different multimodal movement recognition approaches and compare their performances.

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.

Proportional estimation of finger movements from high-density surface electromyography.

BACKGROUND: The 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. METHODS: The 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). RESULTS: The 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 MAFA ~ 0.6 vs. 1.1 %, median nMSE ~ 4.3 vs. 5.5 %). The LDA and the CSP-PE performed similarly in the online tests (median nMSE < 3.6 %, median MAFA < 0.7 %), 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. CONCLUSIONS: The 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.

On optimal electrode configuration to estimate hand movements from forearm surface electromyography.

Understanding the movement of the hand from sEMG signals acquired on the forearm is key in the development of future prosthetics of the upper limb. Despite the technical advancement on this technique, state of the art of sEMG still relies strongly on optimal electrode placement which is typically performed by a specialist by mean of a heuristic search. Involving a specialist has few major disadvantages including high costs and relatively long schedules. This work searches an optimal electrode configuration which could reduce or avoid the intervention of a specialist. More than 200 different possible electrode configurations were assessed by means of the average recognition rate over 11 different movements of the hand, wrist, and fingers. It is shown that using two rows of 8 equally spaced electrodes around the circumference of the forearm could be an optimal trade-off solution to accomplish the task of recognizing hand movement (ARR = 92%) without the need for a specialist or very complex hardware.

Individual finger classification from surface EMG: Influence of electrode set.

The aim of this work was to minimize the number of channels, determining acceptable electrode locations and optimizing electrode-recording configurations to decode isometric flexion and extension of individual fingers. Nine healthy subjects performed cyclical isometric contractions activating individual fingers. During the experiment they tracked a moving visual marker indicating the contraction type (flexion/extension), desired activation level and the finger that should be employed. Surface electromyography (sEMG) signals were detected from the forearm muscles using a matrix of 192 channels (24 longitudinal columns and 8 transversal rows, 10 mm inter-electrode distance). The classification was evaluated in the context of a linear discriminant analysis (LDA) with different sets of EMG electrodes: A) one linear array of 8 electrodes, B) two arrays of 8 electrodes each, C) a set with one electrode on the barycenter of each sEMG activity area, D) all the recorded channels. The results showed that the classification accuracy depended on the electrode set (F=14.67, p<;0.001). The best reduction approaches were the barycenter calculation and the use of two linear arrays of electrodes, which performed similarly to each other (both > 82% of average success rate). Considering the computation time and electrode positioning, it is concluded that two arrays of 8 electrodes provide an optimal configuration to classify the isometric flexion and extension of individual fingers.

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.

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.

TRPC channels are involved in calcium-dependent migration and proliferation in immortalized GnRH neurons.

Gonadotropin-releasing hormone (GnRH)-secreting neurons are key regulators of the reproductive behaviour in vertebrates. These neurons show a peculiar migratory pattern during embryonic development, and its perturbations have profound impact on fertility and other related functional aspects. Changes in the intracellular calcium concentration, [Ca(2+)](i), induced by different extracellular signals, play a central role in the control of neuronal migration, but the available knowledge regarding GnRH neurons is still limited. Our goal was to investigate mechanisms that may be involved in the Ca(2+) dependence of the migratory behaviour in these neurons. We focused on the "classical" Transient Receptor Potential (TRPC) subfamily of Ca(2+)-permeable cation channels, recently shown to be involved in other aspects of neuronal development. Using GN11 cells, immortalized early stage GnRH neurons, we set to investigate Ca(2+) signals under basal conditions and in the presence of a well-established motogen, fetal calf serum (FCS), and the effect of pharmacological TRPC agonists and antagonists on Ca(2+) oscillations, cell motility and proliferation. We have found that a subpopulation of GN11 cells shows spontaneous Ca(2+) transients and that this activity is increased in the presence of serum. Quantitative real-time PCR showed that transcripts of some TRPC members are expressed in GN11 cells. Interestingly, pharmacological experiments with inhibitors, SKF-96365, lanthanum, anti-TRPC1 antibody, and activators, 1-oleil 2-acetyl-sn-glycerol, of TRPCs suggested that the activation of these channels can account for both the basal Ca(2+) oscillations and the increased activity in the presence of FCS. Moreover, functional studies using the same pharmacological tools supported their involvement in the control of motility and proliferation. Thus, our data provide evidence for the involvement of Ca(2+)-permeable channels of the TRPC subfamily in the control of functional properties of neurosecretory cells and neuronal motility.

Interaction of spherical silica nanoparticles with neuronal cells: size-dependent toxicity and perturbation of calcium homeostasis.

The effects of Stöber silica nanoparticles on neuronal survival, proliferation, and on the underlying perturbations in calcium homeostasis are investigated on the well-differentiated neuronal cell line GT1-7. The responses to nanoparticles 50 and 200 nm in diameter are compared. The 50-nm silica affects neuronal survival/proliferation in a dose-dependent way, by stimulating apoptotic processes. In contrast, the 200-nm silica does not show any toxic effect even at relatively high concentrations (292 µg mL−1). To identify the mechanisms underlying these effects, the changes in intracellular calcium concentration elicited by acute and chronic administration of the two silica nanoparticles are analyzed. The 50-nm silica at toxic concentrations generates huge and long-lasting increases in intracellular calcium, whereas the 200-nm silica only induces transient signals of much lower amplitude. These findings provide the first evidence that silica nanoparticles can induce toxic effects on neuronal cells in a size-dependent way, and that these effects are related to the degree of perturbation of calcium homeostasis.

A diamond-based biosensor for the recording of neuronal activity.

We have developed a device for recording the extracellular electrical activity of cultured neuronal networks based on a hydrogen terminated (H-terminated) conductive diamond. GT1-7 cells, a neuronal cell line showing spontaneous action potentials firing, could maintain their functional properties for days in culture when plated on the H-terminated diamond surface. The recorded extracellular electrical activity appeared in the form of well-resolved bursts of fast and slow biphasic signals with a mean duration of about 8ms for the fast and 60ms for the slow events. The time courses of these signals were in good agreement with those recorded by means of conventional microelectrode array (MEAs) and with the negative derivative of the action potentials intracellularly recorded with the patch clamp technique from single cells. Thus, although hydrophobic in nature, the conductive H-terminated diamond surface is able to reveal the spontaneous electrical activity of neurons mainly by capacitative coupling to the cell membrane. Having previously shown that the optical properties of H-terminated diamond allow to record cellular activity by means of fluorescent probes (Ariano, P., Baldelli, P., Carbone, E., Giardino, A., Lo Giudice, A., Lovisolo, D., Manfredotti, C., Novara, M., Sternschulte, H., Vittone, E., 2005. Diam. Relat. Mater. 14, 669-674), we now provide evidence for the feasibility of using diamond-based cellular biosensors for multiparametrical recordings of electrical activity from living cells.

Expression and localisation of TRPC channels in immortalised GnRH neurons.

Calcium-permeable cation channels of the transient receptor potential (TRP) superfamily are involved in agonist-induced calcium influx in several cell types. In this work we evaluated expression and localisation of classical TRP (TRPC) channels in two immortalised cell lines derived from the gonadotrophin releasing hormone (GnRH) neuroendocrine system, at different developmental stages: GT1-7 cells display many characteristics of mature hypothalamic GnRH neurons and are a suitable model to study neuritogenesis and neurosecretion, whereas GN11 cells retain a more immature phenotype with migratory activity. Immunoblotting analysis demonstrates that GN11 and GT1-7 cells differentially express several members of the TRPC family: TRPC1 and TRPC5 are expressed at high levels in GN11 cells, and TRPC4 is expressed at higher levels in GT1-7 cells. Immunocytochemical experiments show a widespread localisation for TRPC proteins in GN11 cells and a characteristic staining along neurites in GT1-7 cells. These data suggest that different TRPC proteins could play specific functional roles at different developmental stages of the GnRH system.

Temporal dynamics of neurite outgrowth promoted by basic fibroblast growth factor in chick ciliary ganglia.

Basic fibroblast growth factor (bFGF) is a potent and multifunctional neurotrophic factor that can influence neuronal survival and differentiation. It has been shown to modulate growth and orientation of neuritic processes both in intact organs and in neuronal cultures, with a wide spectrum of effects on different preparations. Here we report that it promotes neurite growth in developing parasympathetic neurons from the chick ciliary ganglion. We have used both organotypic cultures and dissociated neurons, and we have combined assessment of global neurite growth by immunocytochemical techniques with evaluation of dynamic parameters of single neurites via time-lapse microscopy. We show that laminin, a molecule of the extracellular matrix that has been associated with stimulation of neurite extension, has only a limited and short-lived effect on neurite outgrowth. In contrast, bFGF can promote global growth of the neuritic network both in whole ganglia and in dissociated cultures for times up to 48 hr, and this effect is related to an increase in the growth rate of single neurites. Moreover, the effect can be observed even in enriched neuronal cultures, pointing to a direct action of bFGF on neurons.

Calcium signals and the in vitro migration of chick ciliary ganglion cells.

We have studied calcium signals and their role in the migration of neuronal and nonneuronal cells of embryonic chick ciliary ganglion (CG). In vitro, neurons migrate in association with nonneuronal cells to form cellular aggregates. Changes in the modulus of the velocity of the neuron-nonneuronal cell complex were observed in response to treatments that increased or decreased intracellular calcium concentration. In addition, both cell types generated spontaneous calcium activity that was abolished by removal of extracellular calcium. Calcium signals in neurons could be characterized as either spikes or waves. Neuronal spikes were found to be related to action potential generation whereas neuronal waves were due to voltage-independent calcium influx. Nonneuronal cells generated calcium oscillations that were dependent on calcium release from intracellular stores and on voltage-independent calcium influx. Application of thimerosal, a compound that stimulates calcium mobilization from internal stores, increased: (1) the amplitude of spontaneous nonneuronal oscillations; (2) the area of migrating nonneuronal cells; and (3) the velocity of the neuronal-nonneuronal cell complex. We conclude that CG cell migration is a calcium dependent process and that nonneuronal cell calcium oscillations play a key role in the modulation of velocity.

Calcium signals activated by arachidonic acid in embryonic chick ciliary ganglion neurons.

Arachidonic acid (AA, 20:4) has been reported to modulate a variety of calcium-permeable ionic channels, both in the plasma membrane and in the endoplasmic reticulum. We have studied the effects of AA on calcium signaling in a well-characterized model of developing peripheral neurons, embryonic chick ciliary ganglion neurons in culture. When given at low non-micellar concentrations (5 microM), in the majority of cells AA directly activated a delayed and long-lasting increase in [Ca2+]i, involving both the cytoplasm and the nucleoplasm, that was completely reversed by abolition of extracellular calcium. Other fatty acids (FAs), either saturated like arachidic acid (20:0), or unsaturated like linoleic (18:2) and docosahexaenoic acid (22:6), shared its ability to activate calcium influx. This entry was not suppressed by voltage-dependent calcium channel inhibitors omega-conotoxin and nifedipine, by the voltage-independent calcium channel antagonist LOE-908, by pre-treatment with blockers of AA metabolic pathways or with pertussis toxin. The arachidonate-activated calcium pathway was permeable to Mn2+ and blocked by La3+, Gd3+ and Ni2+. In a neuronal subpopulation, AA at the same concentration was also able to elicit calcium release from thapsigargin-sensitive intracellular stores; we provide evidence that cytochrome P450 epoxygenase is involved in this process.

GDNF and bFGF are differentially involved in glial cell differentiation and neurite bundle formation in cultures from chick embryonic ciliary ganglia.

We have shown that the neurotrophic factors glial cell line-derived neurotrophic factor (GDNF) and basic fibroblast growth factor (bFGF) exert different effects on glial cells in cultures from chick embryo ciliary ganglia. bFGF acts as a mitogen on glial cells, and induces their aggregation to neuronal bodies; after 48 h of culture no glial cells could be observed along neurites. GDNF has no proliferative role; in contrast, it promotes the expression of the differentiative marker O4 and the association of glial cell bodies to neurites to form robust bundles.

In vitro analysis of neuron-glial cell interactions during cellular migration.

We used time-lapse microscopy to study the in vitro migration of neuronal cells from developing chick ciliary ganglion. These cells, when dissociated and cultured in a chemically defined medium, are able to migrate and to associate into clusters. We focused our attention on the study of the distribution of neuronal velocity components. Quantitative analysis of cell trajectories allowed us to demonstrate that, in many cells, velocities are well described by the Langevin equation, when deterministic components of the forces acting on the cells are taken into account. We also have shown that the majority of neurons whose movement is not purely random migrate in association with glial cells. We conclude that glial cells, by guiding neurons during migration, play an important role in the cell organization in vitro.