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Prior studies have shown that the accuracy and efficiency of reaching can be improved using novel sensory interfaces to apply task-specific vibrotactile feedback (VTF) during movement. However, those studies have typically evaluated performance after less than 1 h of training using VTF. Here, we tested the effects of extended training using a specific form of vibrotactile cues-supplemental kinesthetic VTF-on the accuracy and temporal efficiency of goal-directed reaching. Healthy young adults performed planar reaching with VTF encoding of the moving hand's instantaneous position, applied to the non-moving arm. We compared target capture errors and movement times before, during, and after approximately 10 h (20 sessions) of training on the VTF-guided reaching task. Initial performance of VTF-guided reaching showed that people were able to use supplemental VTF to improve reaching accuracy. Performance improvements were retained from one training session to the next. After 20 sessions of training, the accuracy and temporal efficiency of VTF-guided reaching were equivalent to or better than reaches performed with only proprioception. However, hand paths during VTF-guided reaching exhibited a persistent strategy where movements were decomposed into discrete sub-movements along the cardinal axes of the VTF display. We also used a dual-task condition to assess the extent to which performance gains in VTF-guided reaching resist dual-task interference. Dual-tasking capability improved over the 20 sessions, such that the primary VTF-guided reaching and a secondary choice reaction time task were performed with increasing concurrency. Thus, VTF-guided reaching is a learnable skill in young adults, who can achieve levels of accuracy and temporal efficiency equaling or exceeding those observed during movements guided only by proprioception. Future studies are warranted to explore learnability in older adults and patients with proprioceptive deficits, who might benefit from using wearable sensory augmentation technologies to enhance control of arm movements., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

As the population worldwide ages, there is a growing need for assistive technology and effective human-machine interfaces to address the wider range of motor disabilities that older adults may experience. Motor disabilities can make it difficult for individuals to perform basic daily tasks, such as getting dressed, preparing meals, or using a computer. The goal of this study was to investigate the effect of two weeks of training with a myoelectric computer interface (MCI) on motor functions in younger and older adults. Twenty people were recruited in the study: thirteen younger (range: 22-35 years old) and seven older (range: 61-78 years old) adults. Participants completed six training sessions of about 2 hours each, during which the activity of right and left biceps and trapezius were mapped into a control signal for the cursor of a computer. Results highlighted significant improvements in cursor control, and therefore in muscle coordination, in both groups. All participants with training became faster and more accurate, although people in different age range learned with a different dynamic. Results of the questionnaire on system usability and quality highlighted a general consensus about easiness of use and intuitiveness. These findings suggest that the proposed MCI training can be a powerful tool in the framework of assistive technologies for both younger and older adults. Further research is needed to determine the optimal duration and intensity of MCI training for different age groups and to investigate long-term effects of training on physical and cognitive function.

Cervical spinal cord injury (cSCI) often results in bilateral impairment of the arms, leading to difficulties in performing daily activities. However, little is known about the neuromotor alterations that affect the ability of individuals with cSCI to perform coordinated movements with both arms. To address this issue, we developed and tested a functional assessment that integrates clinical, kinematic, and muscle activity measures, including the evaluation of bilateral arm movements. Twelve subjects with a C5-C7 spinal lesion and six unimpaired subjects underwent an evaluation that included three tests: the Manual Muscle Test, Range Of Motion test and Arm stabilisation test, a subsection of the "Van Lieshout arm/hand function test". During the latter, we recorded kinematic and muscle activity data from the upper-body during the execution of a set of movements that required participants to stabilize both arms against gravity at different configurations. Analytical methods, including muscle synergies, spinal maps, and Principal Component Analysis, were used to analyse the data. Clinical tests detected limitations in shoulder abduction-flexion of cSCI participants and alterations in elbows-wrists motor function. The instrumented assessment provided insight into how these limitations impacted the ability of cSCI participants to perform bilateral movements. They exhibited severe difficulty in performing movements involving over-the-shoulder motion and shoulder internal rotation due to altered patterns of activity of the scapular stabilizer muscles, latissimus dorsi, pectoralis, and triceps. Our findings shed light on the bilateral neuromotor changes that occur post-cSCI addressing not only motor deficits, but also the underlying abnormal, weak, or silent muscle activations.

Multiple sclerosis (MS) is an autoimmune and neurodegenerative disease resulting in motor impairments associated with muscle weakness and lack of movement coordination. The goal of this work was to quantify upper limb motor deficits in asymptomatic MS subjects with a robot-based assessment including performance and muscle synergies analysis. A total of 7 subjects (MS: 3 M-4 F; 42 ± 10 years) with clinically definite MS according to McDonald criteria, but with no clinical disability, and 7 age- and sex-matched subjects without a history of neurological disorders participated in the study. All subjects controlled a cursor on the computer screen by moving their hand or applying forces in 8 coplanar directions at their self-selected speed. They grasped the handle of a robotic planar manipulandum that generated four different environments: null, assistive or resistive forces, and rigid constraint. Simultaneously, the activity of 15 upper body muscles was recorded. Asymptomatic MS subjects generated less smooth and less accurate cursor trajectories than control subjects in controlling a force profile, while the end-point error was significantly different also in the other environments. The EMG analysis revealed different muscle activation patterns in MS subjects when exerting isometric forces or when moving in presence of external forces generated by a robot. While the two populations had the same number and similar structure of muscle synergies, they had different activation profiles. These results suggested that a task requiring to control forces against a rigid environment allows better than movement tasks to detect early sensory-motor signs related to the onset of symptoms of multiple sclerosis and to differentiate between stages of the disease., Competing Interests: MCo was employed by confinis ag. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Pierella, Pellegrino, Muller, Inglese, Solaro, Coscia and Casadio.)

The use of augmented reality (AR) and virtual reality (VR) for life support training is increasing. These technologies provide an immersive experience that supports learning in a safe and controlled environment. This review focuses on the use of AR and VR for emergency care training for health care providers, medical students, and nonprofessionals. In particular, we analyzed (1) serious games, nonimmersive games, both single-player and multiplayer; (2) VR tools ranging from semi-immersive to immersive virtual and mixed reality; and (3) AR applications. All the toolkits have been investigated in terms of application goals (training, assessment, or both), simulated procedures, and skills. The main goal of this work is to summarize and organize the findings of studies coming from multiple research areas in order to make them accessible to all the professionals involved in medical simulation. The analysis of the state-of-the-art technologies reveals that tools and studies related to the multiplayer experience, haptic feedback, and evaluation of user's manual skills in the foregoing health care-related environments are still limited and require further investigation. Also, there is an additional need to conduct studies aimed at assessing whether AR/VR-based systems are superior or, at the minimum, comparable to traditional training methods., (©Serena Ricci, Andrea Calandrino, Giacomo Borgonovo, Marco Chirico, Maura Casadio. Originally published in JMIR Serious Games (https://games.jmir.org), 23.03.2022.)

Postural control is a complex sensorimotor skill that is fundamental to our daily life. The abilities to maintain and recover balance degrade with age. However, the time decay of balance performance with age is not well understood. In this study, we aim at quantifying the age-dependent changes in standing balance under static and dynamic conditions. We tested 272 healthy subjects with ages ranging from 20 to 90. Subjects maintained the upright posture while standing on the robotic platform hunova®. In the evaluation of static balance, subjects stood on the fixed platform both with eyes open (EO) and eyes closed (EC). In the dynamic condition, subjects stood with eyes open on the moving foot platform that provided three different perturbations: (i) an inclination proportional to the center of pressure displacements, (ii) a pre-defined predictable motion, and (iii) an unpredictable and unexpected tilt. During all these tests, hunova® measured the inclination of the platform and the displacement of the center of pressure, while the trunk movements were recorded with an accelerometer placed on the sternum. To quantify balance performance, we computed spatio-temporal parameters typically used in clinical environments from the acceleration measures: mean velocity, variability of trunk motion, and trunk sway area. All subjects successfully completed all the proposed exercises. Their motor performance in the dynamic balance tasks quadratically changed with age. Also, we found that the reliance on visual feedback is not age-dependent in static conditions. All subjects well-tolerated the proposed protocol independently of their age without experiencing fatigue as we chose the timing of the evaluations based on clinical needs and routines. Thus, this study is a starting point for the definition of robot-based assessment protocols aiming at detecting the onset of age-related standing balance deficits and allowing the planning of tailored rehabilitation protocols to prevent falls in older adults., Competing Interests: ADL and VS works for Movendo Technology srl, work for Movendo Technology that commercializes the hunova robotic device used in this study. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Marchesi, De Luca, Squeri, De Michieli, Vallone, Pilotto, Leo, Casadio and Canessa.)

Effective control of trunk muscles is fundamental to perform most daily activities. Stroke affects this ability also when sitting, and the Modified Functional Reach Test is a simple clinical method to evaluate sitting balance. We characterize the upper body kinematics and muscular activity during this test. Fifteen chronic stroke survivors performed twice, in separate sessions, three repetitions of the test in forward and lateral directions with their ipsilesional arm. We focused our analysis on muscles of the trunk and of the contralesional, not moving, arm. The bilateral activations of latissimi dorsi, trapezii transversalis and oblique externus abdominis were left/right asymmetric, for both test directions, except for the obliquus externus abdominis in the frontal reaching. Stroke survivors had difficulty deactivating the contralesional muscles at the end of each trial, especially the trapezii trasversalis in the lateral direction. The contralesional, non-moving arm had muscular activations modulated according to the movement phases of the moving arm. Repeating the task led to better performance in terms of reaching distance, supported by an increased activation of the trunk muscles. The reaching distance correlated negatively with the time-up-and-go test score.

Motor memories undergo a period of consolidation before they become resistant to the practice of another task. Although movement variability is important in motor memory consolidation, its role is not fully understood in redundant tasks where variability can exist along two orthogonal subspaces (the 'task space' and the 'null space') that have different effects on task performance. Here, we used haptic perturbations to augment variability in these different spaces and examined their effect on motor memory consolidation. Participants learned a shuffleboard task, where they held a bimanual manipulandum and made a discrete throwing motion to slide a virtual puck towards a target. The task was redundant because the distance travelled by the puck was determined by the sum of the left and right hand speeds at release. After participants practiced the task, we used haptic perturbations to introduce motor variability in the task space or null space and examined consolidation of the original task on the next day. We found that regardless of the amplitude, augmenting variability in the task space resulted in significantly better consolidation relative to augmenting variability in the null space, but was not different from a control group that practiced with no variability. This benefit of increasing task space variability relative to increasing null space variability was likely due to the fact that it did not disrupt the pre-existing coordination strategy. These results suggest that the effects of variability on motor memory consolidation depend on the interplay between the induced variability and the pre-existing coordination strategy., (Copyright © 2021 IBRO. Published by Elsevier Ltd. All rights reserved.)

The first minute of life, the Golden Minute, has been defined as a critical window in which fundamental physiological processes occur for establishing spontaneous ventilation in a newborn. Resuscitation is more likely to succeed if it is performed properly and at the right time. In this scenario, simulation is an appropriate tool for training and evaluating the abilities of all staff working in the delivery room, as well as students. As simulations require a high degree of immersivity in order to be effective, the use of technologies like Virtual (VR) and mixed reality (MR) have garnered more interest in training. Currently, some VR and MR applications have been developed for adult life support training, but neonatal tools are still missing. To overcome this limitation, we present RiNeo MR, a prototype of a MR simulator for neonatal resuscitation training. The simulator consists of (i) a sensorized physical model of the newborn that allows monitoring chest compressions; (ii) a VR head mounted display that allows visualizing a virtual 3D model of the manikin and scenarios of the delivery and operating rooms. This enables students, and healthcare providers to be immersed in realistic hospital settings while performing life support procedures on the newborn manikin. Clinical Relevance-The newborn life support training (NLS) in facilities reduces term intrapartum-related deaths by 30%.

In human-machine interfaces, decoder calibration is critical to enable an effective and seamless interaction with the machine. However, recalibration is often necessary as the decoder off-line predictive power does not generally imply ease-of-use, due to closed loop dynamics and user adaptation that cannot be accounted for during the calibration procedure. Here, we propose an adaptive interface that makes use of a non-linear autoencoder trained iteratively to perform online manifold identification and tracking, with the dual goal of reducing the need for interface recalibration and enhancing human-machine joint performance. Importantly, the proposed approach avoids interrupting the operation of the device and it neither relies on information about the state of the task, nor on the existence of a stable neural or movement manifold, allowing it to be applied in the earliest stages of interface operation, when the formation of new neural strategies is still on-going. In order to more directly test the performance of our algorithm, we defined the autoencoder latent space as the control space of a body-machine interface. After an initial offline parameter tuning, we evaluated the performance of the adaptive interface versus that of a static decoder in approximating the evolving low-dimensional manifold of users simultaneously learning to perform reaching movements within the latent space. Results show that the adaptive approach increased the representational efficiency of the interface decoder. Concurrently, it significantly improved users' task-related performance, indicating that the development of a more accurate internal model is encouraged by the online co-adaptation process., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Position sense refers to an aspect of proprioception crucial for motor control and learning. The onset of neurological diseases can damage such sensory afference, with consequent motor disorders dramatically reducing the associated recovery process. In regular clinical practice, assessment of proprioceptive deficits is run by means of clinical scales which do not provide quantitative measurements. However, existing robotic solutions usually do not involve multi-joint movements but are mostly applied to a single proximal or distal joint. The present work provides a testing paradigm for assessing proprioception during coordinated multi-joint distal movements and in presence of kinaesthetic perturbations: we evaluated healthy subjects' ability to match proprioceptive targets along two of the three wrist's degrees of freedom, flexion/extension and abduction/adduction. By introducing rotations along the pronation/supination axis not involved in the matching task, we tested two experimental conditions, which differed in terms of the temporal imposition of the external perturbation: in the first one, the disturbance was provided after the presentation of the proprioceptive target, while in the second one, the rotation of the pronation/ supination axis was imposed during the proprioceptive target presentation. We investigated if (i) the amplitude of the perturbation along the pronation/supination would lead to proprioceptive miscalibration; (ii) the encoding of proprioceptive target, would be influenced by the presentation sequence between the target itself and the rotational disturbance. Eighteen participants were tested by means of a haptic neuroergonomic wrist device: our findings provided evidence that the order of disturbance presentation does not alter proprioceptive acuity. Yet, a further effect has been noticed: proprioception is highly anisotropic and dependent on perturbation amplitude. Unexpectedly, the configuration of the forearm highly influences sensory feedbacks, and significantly alters subjects' performance in matching the proprioceptive targets, defining portions of the wrist workspace where kinaesthetic and proprioceptive acuity are more sensitive. This finding may suggest solutions and applications in multiple fields: from general haptics where, knowing how wrist configuration influences proprioception, might suggest new neuroergonomic solutions in device design, to clinical evaluation after neurological damage, where accurately assessing proprioceptive deficits can dramatically complement regular therapy for a better prediction of the recovery path., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 D'Antonio, Galofaro, Zenzeri, Patané, Konczak, Casadio and Masia.)

The COVID-19 pandemic has highlighted the need for advancing the development and implementation of novel means for home-based telerehabilitation in order to enable remote assessment and training for individuals with disabling conditions in need of therapy. While somatosensory input is essential for motor function, to date, most telerehabilitation therapies and technologies focus on assessing and training motor impairments, while the somatosensorial aspect is largely neglected. The integration of tactile devices into home-based rehabilitation practice has the potential to enhance the recovery of sensorimotor impairments and to promote functional gains through practice in an enriched environment with augmented tactile feedback and haptic interactions. In the current review, we outline the clinical approaches for stimulating somatosensation in home-based telerehabilitation and review the existing technologies for conveying mechanical tactile feedback (i.e., vibration, stretch, pressure, and mid-air stimulations). We focus on tactile feedback technologies that can be integrated into home-based practice due to their relatively low cost, compact size, and lightweight. The advantages and opportunities, as well as the long-term challenges and gaps with regards to implementing these technologies into home-based telerehabilitation, are discussed., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Handelzalts, Ballardini, Avraham, Pagano, Casadio and Nisky.)

Objective: Body-Machine Interfaces (BoMIs) establish a way to operate a variety of devices, allowing their users to extend the limits of their motor abilities by exploiting the redundancy of muscles and motions that remain available after spinal cord injury or stroke. Here, we considered the integration of two types of signals, motion signals derived from inertial measurement units (IMUs) and muscle activities recorded with electromyography (EMG), both contributing to the operation of the BoMI., Approach: A direct combination of IMU and EMG signals might result in inefficient control due to the differences in their nature. Accordingly, we used a nonlinear-regression-based approach to predict IMU from EMG signals, after which the predicted and actual IMU signals were combined into a hybrid control signal. The goal of this approach was to provide users with the possibility to switch seamlessly between movement and EMG control, using the BoMI as a tool for promoting the engagement of selected muscles. We tested the interface in three control modalities, EMG-only, IMU-only and hybrid, in a cohort of 15 unimpaired participants. Participants practiced reaching movements by guiding a computer cursor over a set of targets., Main Results: We found that the proposed hybrid control led to comparable performance to IMU-based control and significantly outperformed the EMG-only control. Results also indicated that hybrid cursor control was predominantly influenced by EMG signals., Significance: We concluded that combining EMG with IMU signals could be an efficient way to target muscle activations while overcoming the limitations of an EMG-only control.

The purpose of this study was to find a parsimonious representation of hand kinematics data that could facilitate prosthetic hand control. Principal Component Analysis (PCA) and a non-linear Autoencoder Network (nAEN) were compared in their effectiveness at capturing the essential characteristics of a wide spectrum of hand gestures and actions. Performance of the two methods was compared on (a) the ability to accurately reconstruct hand kinematic data from a latent manifold of reduced dimension, (b) variance distribution across latent dimensions, and (c) the separability of hand movements in compressed and reconstructed representations derived using a linear classifier. The nAEN exhibited higher performance than PCA in its ability to more accurately reconstruct hand kinematic data from a latent manifold of reduced dimension. Whereas, for two dimensions in the latent manifold, PCA was able to account for 78% of input data variance, nAEN accounted for 94%. In addition, the nAEN latent manifold was spanned by coordinates with more uniform share of signal variance compared to PCA. Lastly, the nAEN was able to produce a manifold of more separable movements than PCA, as different tasks, when reconstructed, were more distinguishable by a linear classifier, SoftMax regression. It is concluded that non-linear dimensionality reduction may offer a more effective platform than linear methods to control prosthetic hands., (Copyright © 2020 Portnova-Fahreeva, Rizzoglio, Nisky, Casadio, Mussa-Ivaldi and Rombokas.)

Background/Objective . Position sense, defined as the ability to identify joint and limb position in space, is crucial for balance and gait but has received limited attention in patients with multiple sclerosis (MS). We investigated lower limb position sense deficits, their neural correlates, and their effects on standing balance in patients with early MS. Methods . A total of 24 patients with early relapsing-remitting MS and 24 healthy controls performed ipsilateral and contralateral matching tasks with the right foot during functional magnetic resonance imaging. Corpus callosum (CC) integrity was estimated with diffusion tensor imaging. Patients also underwent an assessment of balance during quiet standing. We investigated differences between the 2 groups and the relations among proprioceptive errors, balance performance, and functional/structural correlates. Results . During the contralateral matching task, patients demonstrated a higher matching error than controls, which correlated with the microstructural damage of the CC and with balance ability. In contrast, during the ipsilateral task, the 2 groups showed a similar matching performance, but patients displayed a functional reorganization involving the parietal areas. Neural activity in the frontoparietal regions correlated with the performance during both proprioceptive matching tasks and quiet standing. Conclusion. Patients with early MS had subtle, clinically undetectable, position sense deficits at the lower limbs that, nevertheless, affected standing balance. Functional changes allowed correct proprioception processing during the ipsilateral matching task but not during the more demanding bilateral task, possibly because of damage to the CC. These findings provide new insights into the mechanisms underlying disability in MS and could influence the design of neurorehabilitation protocols.

Maintaining balance standing upright is an active process that complements the stabilizing properties of muscle stiffness with feedback control driven by independent sensory channels: proprioceptive, visual, and vestibular. Considering that the contribution of these channels is additive, we investigated to what extent providing an additional channel, based on vibrotactile stimulation, may improve balance control. This study focused only on healthy young participants for evaluating the effects of different encoding methods and the importance of the informational content. We built a device that provides a vibrotactile feedback using two vibration motors placed on the anterior and posterior part of the body, at the L5 level. The vibration was synchronized with an accelerometric measurement encoding a combination of the position and acceleration of the body center of mass in the anterior-posterior direction. The goal was to investigate the efficacy of the information encoded by this feedback in modifying postural patterns, comparing, in particular, two different encoding methods: vibration always on and vibration with a dead zone , i.e., silent in a region around the natural stance posture. We also studied if after the exposure, the participants modified their normal oscillation patterns, i.e., if there were after effects. Finally, we investigated if these effects depended on the informational content of the feedback, introducing trials with vibration unrelated to the actual postural oscillations ( sham feedback). Twenty-four participants were asked to stand still with their eyes closed, alternating trials with and without vibrotactile feedback: nine were tested with vibration always on and sham feedback, fifteen with dead zone feedback. The results show that synchronized vibrotactile feedback reduces significantly the sway amplitude while increasing the frequency in anterior-posterior and medial-lateral directions. The two encoding methods had no different effects of reducing the amount of postural sway during exposure to vibration, however only the dead-zone feedback led to short-term after effects. The presence of sham vibration, instead, increased the sway amplitude, highlighting the importance of the encoded information., (Copyright © 2020 Ballardini, Florio, Canessa, Carlini, Morasso and Casadio.)

Are the muscle synergies extracted from multiple electromyographic signals an expression of neural information processing, or rather a by-product of mechanical and task constraints? To address this question, we asked 41 right-handed adults to perform a variety of motor tasks with their left and right arms. The analysis of the muscle activities resulted in the identification of synergies whose activation was different for the two sides. In particular, tasks involving the control of isometric forces resulted in larger differences. As the two arms essentially have identical biomechanical structure, we concluded that the differences observed in the activation of the respective synergies must be attributed to neural control.

A medical student learning to perform a laparoscopic procedure or a recently paralyzed user of a powered wheelchair must learn to operate machinery via interfaces that translate their actions into commands for an external device. Since the user's actions are selected from a number of alternatives that would result in the same effect in the control space of the external device, learning to use such interfaces involves dealing with redundancy. Subjects need to learn an externally chosen many-to-one map that transforms their actions into device commands. Mathematically, we describe this type of learning as a deterministic dynamical process, whose state is the evolving forward and inverse internal models of the interface. The forward model predicts the outcomes of actions, while the inverse model generates actions designed to attain desired outcomes. Both the mathematical analysis of the proposed model of learning dynamics and the learning performance observed in a group of subjects demonstrate a first-order exponential convergence of the learning process toward a particular state that depends only on the initial state of the inverse and forward models and on the sequence of targets supplied to the users. Noise is not only present but necessary for the convergence of learning through the minimization of the difference between actual and predicted outcomes., Competing Interests: The authors have declared that no competing interests exist.

Vibrotactile interfaces are an inexpensive and non-invasive way to provide performance feedback to body-machine interface users. Interfaces for the upper extremity have utilized a multi-channel approach using an array of vibration motors placed on the upper extremity. However, for successful perception of multi-channel vibrotactile feedback on the arm, we need to account for vibration propagation across the skin. If two stimuli are delivered within a small distance, mechanical propagation of vibration can lead to inaccurate perception of the distinct vibrotactile stimuli. This study sought to characterize vibration propagation across the hairy skin of the forearm. We characterized vibration propagation by measuring accelerations at various distances from a source vibration of variable intensities (100-240 Hz). Our results showed that acceleration from the source vibration was present at a distance of 4 cm at intensities >150 Hz. At distances greater than 8 cm from the source, accelerations were reduced to values substantially below vibrotactile discrimination thresholds for all vibration intensities. We conclude that in future applications of vibrotactile interfaces, stimulation sites should be separated by a distance of at least 8 cm to avoid potential interference in vibration perception caused by propagating vibrations., Competing Interests: Conflicts of Interest: The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Body-machine interfaces (BMIs) provide a non-invasive way to control devices. Vibrotactile stimulation has been used by BMIs to provide performance feedback to the user, thereby reducing visual demands. To advance the goal of developing a compact, multivariate vibrotactile display for BMIs, we performed two psychophysical experiments to determine the acuity of vibrotactile perception across the arm. The first experiment assessed vibration intensity discrimination of sequentially presented stimuli within four dermatomes of the arm (C5, C7, C8, and T1) and on the ulnar head. The second experiment compared vibration intensity discrimination when pairs of vibrotactile stimuli were presented simultaneously vs. sequentially within and across dermatomes. The first experiment found a small but statistically significant difference between dermatomes C7 and T1, but discrimination thresholds at the other three locations did not differ. Thus, while all tested dermatomes of the arm and hand could serve as viable sites of vibrotactile stimulation for a practical BMI, ideal implementations should account for small differences in perceptual acuity across dermatomes. The second experiment found that sequential delivery of vibrotactile stimuli resulted in better intensity discrimination than simultaneous delivery, independent of whether the pairs were located within the same dermatome or across dermatomes. Taken together, our results suggest that the arm may be a viable site to transfer multivariate information via vibrotactile feedback for body-machine interfaces. However, user training may be needed to overcome the perceptual disadvantage of simultaneous vs. sequentially presented stimuli.

During spontaneous and operative deliveries it is important to correctly estimate the position and orientation of the fetus in the birth canal. In fact, incorrect evaluations can lead to errors in ventouse extraction, forceps application, and increased use of cesarean section. In this scenario, simulation is an appropriate tool for training and evaluating the abilities of gynecologists and midwives, because it allows student to practice both common situations and unlikely or risky events.Here we present eBSim, a prototype of a low-cost birth simulator that allows for precise identification of the fetal position, orientation, and station. The simulator consists on a sensorized physical model of the fetus and the pelvis, a corresponding virtual model, and an application, which allows students, instructors, and doctors to use the simulator for training and assessment of gynecological skills.

Simulation is a powerful learning tool, as it allows gaining direct experience in a controlled and repeatable way. However, the simulation is effective when it is able to reproduce the real conditions and when the user feels him/herself immersed and present in the situation. With the aim of improving these critical points, we propose an immersive virtual reality system for first-aid handling. Specifically, we increase the visual realism of medical mannequins and the contextualization, and we add the touch feedback by mapping the real mannequin into its virtual representation. Moreover, the interaction is performed by using a virtual representation of the users own hands by allowing a more realistic execution of tasks. The results show a good accuracy in the mapping between the real and the virtual mannequin, and a high degree of presence for both the control group and the medical one. These results and the low values of simulator sickness reported during the experiment are a good starting point for the use of the proposed mixed reality system in simulation scenarios.

Assessing proprioception is important for understanding and treating sensorimotor impairments. Many daily tasks require bimanual manipulation of objects, but state of the art methods for the assessment of proprioception are far away from bimanual activities, and instead evaluate sensorimotor integrity in oversimplified and often unimanual goal-directed tasks. Here, we developed a new device and method to assess proprioception and force production by simulating a realistic bimanual behavior. Twelve healthy participants held a physically coupled object - a sensorized box - and matched target orientations about the three principal axes without and with added weights. Our preliminary findings indicate that bimanual proprioception during orientation matching depends on the axis of rotation. For example, in rotations about the lateral axis of the body, underestimation and overestimation of the target angle depends on its orientation in a body-centered reference frame: participants tended to underestimate targets that required rotation far away from the body and overestimated angles that required rotation towards the body. We also found that for the same rotation axis, the larger were the rotations, the higher was the force applied. Moreover, we also found that fatigue causes undershoot in orientation matching. In the future, this tool could be adopted for assessment and treatment of sensorimotor deficits in bimanual functional tasks.

Postural responses to unstable conditions or perturbations are important predictors of the risk of falling and can reveal balance deficits in people with neurological disorders, such as Parkinson's Disease (PD). However, there is a lack of evidences related to devices and protocols providing a comprehensive and quantitative evaluation of postural responses in different stability conditions. We tested ten people with PD and ten controls on a robotic platform capable to provide different mechanical interactions and to measure the center of pressure displacement, while trunk acceleration was recorded with a sensor placed on the sternum. We evaluated performance while maintaining upright posture in unperturbed, perturbed, and unstable conditions. The latter was tested while standing and sitting. We measured whether the proposed exercises and metrics could highlight differences in postural control. Participants with PD had worse performance metrics when standing under unperturbed or unstable conditions, and when sitting on the unstable platform. PD subjects in response to a forward perturbation showed bigger trunk oscillations coupled with a sharper increase of the CoP backward displacement. These responses could be due to higher stiffness of lower limb which leads to postural instability. The exercises and the proposed metrics highlighted differences in postural control, hence they can be used in clinical environment for the assessment and progression of postural impairments.

Proprioceptive deficits are frequent and disabling symptoms of neurological diseases such as Multiple Sclerosis (MS). These deficits are poorly understood partly because of the limited sensitivity and reproducibility of clinical measures. However, their assessment is crucial in planning and evaluating rehabilitative treatments. Therefore, we designed a device and a protocol for assessing proprioceptive deficits by evaluating the position and force control performance. We focused on bimanual tasks, as most daily life activities require the combined use of both hands while MS induces coordination problems and often affects the two arms differently. Specifically, without being able to see their arms, subjects had (1) to reach with their hands a target positions holding objects of equal or different weights; (2) to exert equal isometric forces with the two hands in upward direction against rigid constraints at the same or different heights. For a first proof of concept of the feasibility we enrolled seven MS subjects with different levels of upper limb impairment and seven sex and age matched controls. We found that the ability to exert symmetric forces with both arms was significantly altered in all MS subjects, while position control decreased only for higher level of impairment. These preliminary findings suggest that in people with MS the ability to exert bilaterally required levels of force might be affected earlier compared to the ability to control hand position.

Myoelectric Computer Interfaces (MCIs) are a viable option to promote the recovery of movements following spinal cord injury (SCI), stroke, or other neurological disorders that impair motor functions. We developed and tested a MCI interface with the goal of reducing abnormal muscular activations due to compensatory strategies or undesired co-contraction after SCI. The interface mapped surface electromyographic signals (sEMG) into the movement of a cursor on a computer monitor. First, we aimed to reduce the co-activation of muscles pairs: the activation of two muscles controlled orthogonal directions of the cursor movements. Furthermore, to decrease the undesired concurrent activation of a third muscle, we modulated the visual feedback related to the position of the cursor on the screen based on the activation of this muscle. We tested the interface with six unimpaired and two SCI participants. Participants were able to decrease the activity of the targeted muscle when it was associated with the visual feedback of the cursor, but, interestingly, after training, its activity increased again. As for the SCI participants, one successfully decreased the co-activation of arm muscles, while the other successfully improved the selective activation of leg muscles. This is a first proof of concept that people with SCI can acquire, through the proposed MCI, a greater awareness of their muscular activity, reducing abnormal muscle simultaneous activations.

Vibrotactile feedback (VTF) has been proposed as a non-invasive way to augment impaired or lost kinesthetic feedback in certain patient populations, thereby enhancing the real-time control of purposeful limb movements and quality of life. We used a dual tasking scenario to investigate the effects of cognitive load and short-term VTF training on VTF-guided reaching. Participants grasped the handle of a planar manipulandum with one hand and received VTF of its motion via a vibrotactile display attached to the non-moving arm. We asked participants to simultaneously perform VTF-guided reaching and a choice reaction time task both before and after training with VTF-guided reaching. Participants readily used VTF to guide goal-directed hand movements in the absence of visual feedback in the dual-task setting, even prior to training. This capability came at the cost of increased movement completion time. Short-term training on VTF-guided reaching induced significant improvements in target capture errors. Pre- and post-training comparisons of dual-task performance found training-related improvements in VTF-guided reach accuracy were resistant to dual-task interference. We found no training-related improvements in movement completion time or button press performance. These results indicate that VTF can be used to complete goal-directed reaches in a dual task situation, and that a single short bout of training sufficed for participants to begin the transition between the cognitive and associative phases of learning for the integration of VTF into the planning and ongoing control of reaching movements.

Many neurological diseases impair the motor and somatosensory systems. While several different technologies are used in clinical practice to assess and improve motor functions, somatosensation is evaluated subjectively with qualitative clinical scales. Treatment of somatosensory deficits has received limited attention. To bridge the gap between the assessment and training of motor vs. somatosensory abilities, we designed, developed, and tested a novel, low-cost, two-component (bimanual) mechatronic system targeting tactile somatosensation: the Tactile-STAR -a tactile stimulator and recorder. The stimulator is an actuated pantograph structure driven by two servomotors, with an end-effector covered by a rubber material that can apply two different types of skin stimulation: brush and stretch. The stimulator has a modular design, and can be used to test the tactile perception in different parts of the body such as the hand, arm, leg, big toe, etc. The recorder is a passive pantograph that can measure hand motion using two potentiometers. The recorder can serve multiple purposes: participants can move its handle to match the direction and amplitude of the tactile stimulator, or they can use it as a master manipulator to control the tactile stimulator as a slave. Our ultimate goal is to assess and affect tactile acuity and somatosensory deficits. To demonstrate the feasibility of our novel system, we tested the Tactile-STAR with 16 healthy individuals and with three stroke survivors using the skin-brush stimulation. We verified that the system enables the mapping of tactile perception on the hand in both populations. We also tested the extent to which 30 min of training in healthy individuals led to an improvement of tactile perception. The results provide a first demonstration of the ability of this new system to characterize tactile perception in healthy individuals, as well as a quantification of the magnitude and pattern of tactile impairment in a small cohort of stroke survivors. The finding that short-term training with Tactile-STAR can improve the acuity of tactile perception in healthy individuals suggests that Tactile-STAR may have utility as a therapeutic intervention for somatosensory deficits.

Multiple sclerosis is a chronic, autoimmune and neurodegenerative disease affecting multiple functional systems and resulting in motor impairments associated with muscle weakness and lack of movement coordination. We quantified upper limb motor deficits with a robot-based assessment including behavioral and muscle synergy analysis in 11 multiple sclerosis subjects with mild to moderate upper limb impairment (9 female; 50 ± 10 years) compared to 11 age- and gender- matched controls (9 female; 50 ± 9 years). All subjects performed planar reaching tasks by moving their upper limb or applying force while grasping the handle of a robotic manipulandum that generated four different environments: free space, assistive or resistive forces, and rigid constraint. We recorded the activity of 15 upper body muscles. Multiple sclerosis subjects generated irregular trajectories. While activities in isolated arm muscles appeared generally normal, shoulder muscle coordination with arm motions was impaired and there was a marked co-activation of the biceps and triceps in extension movements. Systematic differences in timing and organization of muscle synergies have also been observed. This study supports the definition of new biomarkers and rehabilitative treatments for improving upper limb motor coordination in multiple sclerosis.

Robot-assisted rehabilitation of stroke survivors mainly focuses on the impaired side of the body while the role of the unimpaired side in the recovery after stroke is still controversial. The goal of this study is to investigate the influence on sitting balance and paretic arm functions of a training protocol based on movements of the unimpaired arm. Sixteen chronic stroke survivors underwent nineteen training sessions, in which they performed active movements with the unimpaired arm supported by a passive exoskeleton. Performance of the trunk and upper limbs was evaluated before treatment, after treatment and at six months follow up with clinical scales and an instrumented evaluation. A reaching test executed with the exoskeleton was used to assess changes in performance of both arms. The treatment based on the unimpaired arm's movements executed with a correct body posture led to benefits in control of the trunk and of both the trained and the untrained arm. The amount of impaired arm improvement in the Fugl-Meyer score was comparable to the outcome of robotic treatments focused directly on this arm. Our results highlight the importance of taking into account all body schema in the rehabilitation robotic program, instead of focusing only on the impaired side of the body.

People with Spinal Cord Injury do not only lack the ability to control their muscles, but also miss the sensory information from below the level of their lesion. Therefore, it may become difficult for them to perceive the state of the body during walking, which is however often used to control wearable exoskeletons. In the present study the possibilities of providing vibrotactile feedback about the Center of Mass (CoM) during walking were investigated. The results showed that healthy subjects could successfully interpret the provided vibrotactile cues and change their walking pattern accordingly. Vibrotactile stimulation was either provided in a concurrent (over the complete CoM movement) or terminal (only when the desired CoM displacement was reached) way. The latter led to a better accuracy and can be easily implemented in a wearable exoskeleton where a certain amount of CoM displacement is needed to initiate stepping.

Despite progress in using computational approaches to inform medicine and neuroscience in the last 30 years, there have been few attempts to model the mechanisms underlying sensorimotor rehabilitation. We argue that a fundamental understanding of neurologic recovery, and as a result accurate predictions at the individual level, will be facilitated by developing computational models of the salient neural processes, including plasticity and learning systems of the brain, and integrating them into a context specific to rehabilitation. Here, we therefore discuss Computational Neurorehabilitation, a newly emerging field aimed at modeling plasticity and motor learning to understand and improve movement recovery of individuals with neurologic impairment. We first explain how the emergence of robotics and wearable sensors for rehabilitation is providing data that make development and testing of such models increasingly feasible. We then review key aspects of plasticity and motor learning that such models will incorporate. We proceed by discussing how computational neurorehabilitation models relate to the current benchmark in rehabilitation modeling - regression-based, prognostic modeling. We then critically discuss the first computational neurorehabilitation models, which have primarily focused on modeling rehabilitation of the upper extremity after stroke, and show how even simple models have produced novel ideas for future investigation. Finally, we conclude with key directions for future research, anticipating that soon we will see the emergence of mechanistic models of motor recovery that are informed by clinical imaging results and driven by the actual movement content of rehabilitation therapy as well as wearable sensor-based records of daily activity.

The stabilization of the human standing posture was originally attributed to the stiffness of the ankle muscles but direct measurements of the ankle stiffness ruled out this hypothesis, leaving open the possibility for a feedback stabilization strategy driven by proprioceptive signals. This solution, however, could be implemented with two different kinds of control mechanisms, namely continuous or intermittent feedback. The debate is now settled and the latter solution seems to be the most plausible one. Moreover, stabilization of unstable dynamics is not limited to bipedal standing. Indeed many manipulation tasks can be described in the same framework and thus a very general protocol for addressing this kind of problems is the use of haptic virtual reality where instability is generated by some kind of divergent or saddle-like force field. Several studies demonstrated that human subjects can choose to adopt a stiffness or feedback strategy as a combination of biomechanical and task constraints and can learn to switch from one strategy to the other if it is feasible or to use one or the other is infeasible. Understanding such mechanisms is relevant, for example, for the design of novel ergonomic man-machine interfaces in difficult, unstable tasks., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

The purpose of this study is to identify white matter microstructure changes following bilateral upper extremity motor skill training to increase our understanding of learning-induced structural plasticity and enhance clinical strategies in physical rehabilitation. Eleven healthy subjects performed two visuo-spatial motor training tasks over 9 sessions (2-3 sessions per week). Subjects controlled a cursor with bilateral simultaneous movements of the shoulders and upper arms using a body machine interface. Before the start and within 2days of the completion of training, whole brain diffusion tensor MR imaging data were acquired. Motor training increased fractional anisotropy (FA) values in the posterior and anterior limbs of the internal capsule, the corona radiata, and the body of the corpus callosum by 4.19% on average indicating white matter microstructure changes induced by activity-dependent modulation of axon number, axon diameter, or myelin thickness. These changes may underlie the functional reorganization associated with motor skill learning., (Copyright © 2013 Elsevier Inc. All rights reserved.)

An intact position sense is considered important for neuromotor recovery, but the available methods and protocols for its assessment are still limited. In the clinical practice it is generally tested trough a bimanual position matching test, that consists of replicating with one arm the angular positions of the other arm in space (intrinsic coordinates matching). However, the same test could be carried out by matching the hand location in space (extrinsic coordinates matching). Is there any difference between the procedures that may be relevant to the evaluation of position sense deficits? In this study we compared the performance of eight right handed subjects and two stroke survivors with left hemiparesis performing the test in the two conditions. A robotic manipulandum passively moved the left arm of the participants in twenty-four positions in the workspace. Subjects had to match the left arm position with their right arm either in intrinsic or extrinsic coordinates. The results show that all the subjects (impaired and controls) performed better when using the extrinsic paradigm.

High-level spinal cord injury (SCI) survivors face every day two related problems: recovering motor skills and regaining functional independence. Body machine interfaces (BoMIs) empower people with sever motor disabilities with the ability to control an external device, but they also offer the opportunity to focus concurrently on achieving rehabilitative goals. In this study we developed a portable, and low-cost BoMI that addresses both problems. The BoMI remaps the user's residual upper body mobility to the two coordinates of a cursor on a computer monitor. By controlling the cursor, the user can perform functional tasks, such as entering text and playing games. This framework also allows the mapping between the body and the cursor space to be modified, gradually challenging the user to exercise more impaired movements. With this approach, we were able to change the behavior of our SCI subject, who initially used almost exclusively his less impaired degrees of freedom - on the left side - for controlling the BoMI. At the end of the few practice sessions he had restored symmetry between left and right side of the body, with an increase of mobility and strength of all the degrees of freedom involved in the control of the interface. This is the first proof of concept that our BoMI can be used to control assistive devices and reach specific rehabilitative goals simultaneously.

Motor skill learning has different components. When we acquire a new motor skill we have both to learn a reliable action-value map to select a highly rewarded action (task model) and to develop an internal representation of the novel dynamics of the task environment, in order to execute properly the action previously selected (internal model). Here we focus on a 'pure' motor skill learning task, in which adaptation to a novel dynamical environment is negligible and the problem is reduced to the acquisition of an action-value map, only based on knowledge of results. Subjects performed point-to-point movement, in which start and target positions were fixed and visible, but the score provided at the end of the movement depended on the distance of the trajectory from a hidden viapoint. Subjects did not have clues on the correct movement other than the score value. The task is highly redundant, as infinite trajectories are compatible with the maximum score. Our aim was to capture the strategies subjects use in the exploration of the task space and in the exploitation of the task redundancy during learning. The main findings were that (i) subjects did not converge to a unique solution; rather, their final trajectories are determined by subject-specific history of exploration. (ii) with learning, subjects reduced the trajectory's overall variability, but the point of minimum variability gradually shifted toward the portion of the trajectory closer to the hidden via-point.

Can haptic interaction improve the tracking performance in a fetch & pursue task, similar to clay pigeon shooting? In order to answer this question, we challenged the tracking movements of the subjects by a saddle-like moving force field, with the unstable manifold aligned along the moving target and the stable manifold orthogonal to it. The experimental results show a positive effect, suggesting that the internal model acquired by the subjects for compensating the target-linked haptic disturbance can improve the prediction capability of the subjects based on pure visuo-motor feedback.

In this paper we discuss two possible strategies of movement control that can be used by stroke survivors during rehabilitation robotics training. To perform a reaching task in a minimally assistive force field, subjects either can move following the trajectory provided by the assistive force or they can use an internal representation of a minimum jerk trajectory from their starting position to the target. We used the stiffness and damping values directly estimated from the experimental data to simulate the trajectories that result by taking into account both hypotheses. The comparison of the simulated results with the data collected on four hemiparetic subjects supports the hypothesis that the central nervous system (CNS) is still able to correctly plan the movement, although a normal execution is impaired.

Stroke survivors strongly rely on visual feedback to control their movements, since segmental reflexes are characterized by an inherent hyper-excitability. To test the effect of visual feedback on the modulation of arm stability we estimated the stiffness of the paretic arm in nine stroke survivors during robot mediated therapy, where subjects trained with and without vision. While several studies found a negligible effect in unimpaired individuals, our results highlighted a marked reduction of stroke survivors' arm stiffness in absence of visual feedback.

Studies of adaptation to patterns of deterministic forces have revealed the ability of the motor control system to form and use predictive representations of the environment. These studies have also pointed out that adaptation to novel dynamics is aimed at preserving the trajectories of a controlled endpoint, either the hand of a subject or a transported object. We review some of these experiments and present more recent studies aimed at understanding how the motor system forms representations of the physical space in which actions take place. An extensive line of investigations in visual information processing has dealt with the issue of how the Euclidean properties of space are recovered from visual signals that do not appear to possess these properties. The same question is addressed here in the context of motor behavior and motor learning by observing how people remap hand gestures and body motions that control the state of an external device. We present some theoretical considerations and experimental evidence about the ability of the nervous system to create novel patterns of coordination that are consistent with the representation of extrapersonal space. We also discuss the perspective of endowing human-machine interfaces with learning algorithms that, combined with human learning, may facilitate the control of powered wheelchairs and other assistive devices., (Copyright © 2011 Elsevier B.V. All rights reserved.)

Survivors of spinal cord injury need to reorganize their residual body movements for interacting with assistive devices and performing activities that used to be easy and natural. To investigate movement reorganization, we asked subjects with high-level spinal cord injury (SCI) and unimpaired subjects to control a cursor on a screen by performing upper-body motions. While this task would be normally accomplished by operating a computer mouse, here shoulder motions were mapped into the cursor position. Both the control and the SCI subjects were rapidly able to reorganize their movements and to successfully control the cursor. The majority of the subjects in both groups were successful in reducing the movements that were not effective at producing cursor motions. This is inconsistent with the hypothesis that the control system is merely concerned with the accurate acquisition of the targets and is unconcerned with motions that are not relevant to this goal. In contrast, our findings suggest that subjects can learn to reorganize coordination so as to increase the correspondence between the subspace of their upper-body motions with the plane in which the controlled cursor moves. This is effectively equivalent to constructing an inverse internal model of the map from body motions to cursor motions, established by the experiment. These results are relevant to the development of interfaces for assistive devices that optimize the use of residual voluntary control and enhance the learning process in disabled users, searching for an easily learnable map between their body motor space and control space of the device.

Skillful manipulation of objects often requires the spatio-temporal coordination of both hands and, at the same time, the compensation of environmental forces. In bimanual coordination, movements of the two hands may be coupled because each hand needs to compensate the forces generated by the other hand or by an object operated by both hands (dynamic coupling), or because the two hands share the same workspace (spatial coupling). We examined how spatial coupling influences bimanual coordination, by looking at the adaptation of velocity-dependent force fields during a task in which the two hands simultaneously perform center-out reaching movements with the same initial position and the same targets, equally spaced on a circle. Subjects were randomly allocated to two groups, which differed in terms of the force fields they were exposed to: in one group (CW-CW), force fields had equal clockwise orientations in both hands; in the other group (CCW-CW), they had opposite orientations. In both groups, in randomly selected trials (catch trials) of the adaptation phase, the force fields were unexpectedly removed. Adaptation was quantified in terms of the changes of directional error for both hand trajectories. Bimanual coordination was quantified in terms of inter-limb longitudinal and sideways displacements, in force field and in catch trials. Experimental results indicate that both arms could simultaneously adapt to the two force fields. However, in the CCW-CW group, adaptation was incomplete for the movements from the central position to the more distant targets with respect to the body. In addition, in this group the left hand systematically leads in the movements toward targets on the left of the starting position, whereas the right hand leads in the movements to targets on the right. We show that these effects are due to a gradual sideways shift of the hands, so that during movements the left hand tends to consistently remain at the left of the right hand. These findings can be interpreted in terms of a neural mechanism of bimanual coordination/interaction, triggered by the force field adaptation process but largely independent from it, which opposes movements that may lead to the crossing of the hands. In conclusion, our results reveal a concurrent interplay of two task-dependent modules of motor-cognitive processing: an adaptive control module and a 'protective' module that opposes potentially 'dangerous' (or cognitively costly) bimanual interactions.

The present study proposes a computational model for the formation of whole body reaching synergy, i.e., coordinated movements of lower and upper limbs, characterized by a focal component (the hand must reach a target) and a postural component (the center of mass must remain inside the support base). The model is based on an extension of the equilibrium point hypothesis that has been called Passive Motion Paradigm (PMP), modified in order to achieve terminal attractor features and allow the integration of multiple constraints. The model is a network with terminal attractor dynamics. By simulating it in various conditions it was possible to show that it exhibits many of the spatio-temporal features found in experimental data. In particular, the motion of the center of mass appears to be synchronized with the motion of the hand and with proportional amplitude. Moreover, the joint rotation patterns can be accounted for by a single functional degree of freedom, as shown by principal component analysis. It is also suggested that recent findings in motor imagery support the idea that the PMP network may represent the motor cognitive part of synergy formation, uncontaminated by the effect of execution.

Objective: To carry out a preliminary feasibility study of a new concept of robot therapy for severely impaired patients after stroke., Design: A haptic manipulandum connected to a bar that can rotate freely while providing a measure of the rotation angle. The controller combines a bilateral reaching task with the task of balancing the action of the 2 arms. Reinforcement is given to the subject in 2 forms: audio-visual and haptic by means of adaptable force fields., Patients: Four highly paretic patients with chronic stroke (Fugl-Meyer score less than 15)., Methods: The training cycle consisted of 5 sessions over a period of 2 weeks. Each session (45 min) was divided in blocks of 10 pairs of forward/backward movements. Performance was determined by evaluating the number of successful movements per session, the session-by-session decrease in the assistive field, the mean reaching time, and the mean stopping field., Results: All subjects could understand the task, appreciated it and improved their performance during training. The reaching movements became smoother and quicker; balance errors and the magnitude of the resisting field were consistently reduced., Conclusion: Bilateral robot therapy is a promising technique, provided that it self-adapts to the patient's performance. Formal clinical trials should address this point.

Robotic systems for neuromotor rehabilitation have been a part of clinical practice for more than a decade but the efficacy of this new technology is still debated. One reason for this, in our opinion, is that there is still no consensus on the most important features of these systems, or on the underlying theoretical basis, essential for the rational design of treatment protocols. The aim of this paper, born of our long experience in the study of the neural control of movement and the use of robots for characterizing motor control mechanisms, is to make a small contribution to clarifying this issue. What is needed in the future is a "research pipeline" encompassing experimentally validated models of neural control of movement, models of motor learning, models of functional recovery, and finally principle-based robot therapy control strategies. We believe this is a necessary prerequisite for carrying out well formulated comparisons of different control strategies as well as mixed strategies of robot/human treatment, in the framework of randomised, controlled clinical trials.

In stroke survivors, motor impairment is frequently associated with degraded proprioceptive and/or somatosensory functions. Here we address the question of how to use robots to improve proprioception in these patients. We used an 'assist-as-needed' protocol, in which robot assistance was kept to a minimum and was continuously adjusted during exercise. To specifically train proprioceptive functions, we alternated blocks of trials with and without vision. A total of nine chronic stroke survivors participated in the study, which consisted of a total of ten 1-h exercise sessions. We used a linear mixed-effects statistical model to account for the effects of exercise, vision and the degree of assistance on the overall performance, and to capture both the systematic effects and the individual variations. Although there was not always a complete recovery of autonomous movements, all subjects exhibited an increased amount of voluntary control. Moreover, training with closed eyes appeared to be beneficial for patients with abnormal proprioception. Our results indicate that training by alternating vision and no-vision blocks may improve the ability to use proprioception as well as the ability to integrate it with vision. We suggest that the approach may be useful in the more general case of motor skill acquisition, in which enhancing proprioception may improve the ability to physically interact with the external world.

Objective: To carry out a proof of concept study for integrating robot therapy with physiotherapy in the treatment of stroke patients., Design: A simple and 'gentle' paradigm of robot-patient interaction was designed in order to foster the re-emergence of smooth, active control patterns in coordinated shoulder/elbow reaching movements. A haptic robot was programmed according to a strategy of minimal, progressively reduced assistance, with a double representation of targets: (i) visual (circles on a screen) and (ii) haptic (robot-generated force fields). The protocol included trials with and without vision, in order to emphasize the role of proprioceptive feedback. The training paradigm included 10 sessions and more than 5000 movements., Subjects: Ten chronic, hemiparetic subjects; four controls provided reference values for the performance measurements., Outcome Measures: Four performance indicators (derived from the analysis of the reaching trajectories); clinical/functional measures (Fugl-Meyer and Ashworth scales)., Results: After robot therapy reaching movements became faster and smoother. The performance in the no-vision trials was at least as good as in the vision trials. The Fugl-Meyer arm scores also increased significantly and remained approximately constant at follow-up; the Ashworth scores did not change., Conclusion: In spite of its simplicity, a limited number of ;gentle' robot therapy sessions appear to be beneficial, even for severely impaired patients, although no firm conclusion can be drawn at this point. However, the study provides support material for the careful design of controlled clinical trials and for a better integration with physiotherapy.

In general, survivors of neuromotor disorders and injuries need to reorganize their body movements in order to achieve goals that used to be easy and natural. Often, disabled people are offered the option to control assistive devices that will facilitate the recovery of independence and capability in their daily lives. The knowledge acquired during the last few years in the motor control field can be used to study and enhance this learning process. Furthermore, this knowledge may aid in finding methods for optimizing the use of residual voluntary muscular control in disabled users and searching for an easily learnable map between body motor space and devices control space. To investigate movement reorganization we asked healthy subjects to control a cursor performing a reaching task using shoulders and upper arm movements. These movements were mapped to a lower dimensional space by principal components analysis and were used to control the cursor. We found that all subjects were able to learn to control the cursor with ease and precision while reducing the proportion of ineffective body movement components in favor of the components that mapped directly into the control space. Moreover, with practice the movements of the controlled device - the cursor - became faster, smother, more precise and with a nearly symmetric speed profile.