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Impaired physical performance is common in older adults and has been identified as a major risk factor for falls. To date, there are no conclusive data on the impairment of balance parameters in older subjects with different levels of physical performance.The aim of this study was to investigate the relationship between different grades of physical performance, as assessed by the Short Physical Performance Battery (SPPB), and the multidimensional balance control parameters, as measured by means of a robotic system, in community-dwelling older adults.This study enrolled subjects aged ≥ 65 years. Balance parameters were assessed by the hunova robot in static and dynamic (unstable and perturbating) conditions, in both standing and seated positions and with the eyes open/closed.The study population consisted of 96 subjects (62 females, mean age 77.2 ± 6.5 years). According to their SPPB scores, subjects were separated into poor performers (SPPB 8, n = 29), intermediate performers (SPPB = 8-9, n = 29) and good performers (SPPB 9, n = 38). Poor performers displayed significantly worse balance control, showing impaired trunk control in most of the standing and sitting balance tests, especially in dynamic (both with unstable and perturbating platform/seat) conditions.For the first time, multidimensional balance parameters, as detected by the hunova robotic system, were significantly correlated with SPPB functional performances in community-dwelling older subjects. In addition, balance parameters in dynamic conditions proved to be more sensitive in detecting balance impairments than static tests.

Spinal Cord Injury (SCI) affects trunk control and determines altered or absent neuromuscular activity and sensory feedback below the lesioned spinal segment. The practice of sport or of any physical activity are key elements for improving the health and quality of life of people with SCI. Paralympic athletes overcome limits related to their injuries, achieving high neuromuscular control and coordination. Among the sports that have been adapted for people with disabilities, sit-skiing is a sport that requires good trunk control. However, there is a lack of instruments and protocols for its quantitative assessment. In this work we describe a robot-based protocol designed to assess trunk control and tested with two expert sit-skiers and eight unimpaired subjects. We used the robotic platform hunova® to evaluate both the active and the reactive component of trunk control through two different exercises. We investigated the strategy adopted by subjects to perform these exercises and the changes due to their repetition. All unimpaired subjects successfully completed the proposed protocol. The repetition of both exercises induced a learning process leading to differences in motor performance. Similar results could be observed also in the two athletes, whose performance was characterized by differences due to the severity of their lesion and their skiing skills.

BackgroundFalls in the elderly are a major public health concern because of their high incidence, the involvement of many risk factors, the considerable post-fall morbidity and mortality, and the health-related and social costs. Given that many falls are preventable, the early identification of older adults at risk of falling is crucial in order to develop tailored interventions to prevent such falls. To date, however, the fall-risk assessment tools currently used in the elderly have not shown sufficiently high predictive validity to distinguish between subjects at high and low fall risk. Consequently, predicting the risk of falling remains an unsolved issue in geriatric medicine. This one-year prospective study aims to develop and validate, by means of a cross-validation method, a multifactorial fall-risk model based on clinical and robotic parameters in older adults.MethodsCommunity-dwelling subjects aged ≥ 65 years were enrolled. At the baseline, all subjects were evaluated for history of falling and number of drugs taken daily, and their gait and balance were evaluated by means of the Timed "Up & Go" test (TUG), Gait Speed (GS), Short Physical Performance Battery (SPPB) and Performance-Oriented Mobility Assessment (POMA). They also underwent robotic assessment by means of the hunova robotic device to evaluate the various components of balance. All subjects were followed up for one-year and the number of falls was recorded. The models that best predicted falls-on the basis of: i) only clinical parameters; ii) only robotic parameters; iii) clinical plus robotic parameters-were identified by means of a cross-validation method.ResultsOf the 100 subjects initially enrolled, 96 (62 females, mean age 77.17±.49 years) completed the follow-up and were included. Within one year, 32 participants (33%) experienced at least one fall ("fallers"), while 64 (67%) did not ("non-fallers"). The best classifier model to emerge from cross-validated fall-risk estimation included eight clinical variables (age, sex, history of falling in the previous 12 months, TUG, Tinetti, SPPB, Low GS, number of drugs) and 20 robotic parameters, and displayed an area under the receiver operator characteristic (ROC) curve of 0.81 (95% CI: 0.72-0.90). Notably, the model that included only three of these clinical variables (age, history of falls and low GS) plus the robotic parameters showed similar accuracy (ROC AUC 0.80, 95% CI: 0.71-0.89). In comparison with the best classifier model that comprised only clinical parameters (ROC AUC: 0.67; 95% CI: 0.55-0.79), both models performed better in predicting fall risk, with an estimated Net Reclassification Improvement (NRI) of 0.30 and 0.31 (p = 0.02), respectively, and an estimated Integrated Discrimination Improvement (IDI) of 0.32 and 0.27 (pConclusionA multifactorial fall-risk assessment that includes clinical and hunova robotic variables significantly improves the accuracy of predicting the risk of falling in community-dwelling older people. Our data suggest that combining clinical and robotic assessments can more accurately identify older people at high risk of falls, thereby enabling personalized fall-prevention interventions to be undertaken.

Measuring human arm stiffness in robot interaction is a crucial topic in both neuroscience and the related learning process during skill acquisition and functional recovery in neurological subjects. However, it is a complex and time-consuming procedure often requiring a computational burden which prevents from an online estimation of the data. Most systems described in the previous literature uses robotic manipulandum to estimate limb stiffness by perturbing the arm across different directions over multiple trials and acquiring the corresponding restoring forces. The proposed method is still robust and accurate, although with rather strong limitations in terms of speed and acquisition bandwidth. For this reason, we designed a mechatronic device able to carry out endpoint stiffness estimation within in a single trial. The proposed system can be operated in a stand-alone configuration or can be plugged in a robotic manipulandum, allowing us to perform the measurement during a posture maintaining task in contact with the robotic counterpart. This paper describes the mechanism and the design, testing the device in different experimental contexts, using a customized test bench to characterize the potentials and the limits of the proposed architecture. Furthermore, we tested the system on human subjects to obtain a reliable bidimensional estimation of arm stiffness when it is plugged in a robotic device. Results are reported and discussed in detail highlighting the limitations and the advantages of using the proposed solution.

It is known that physical coupling between two subjects may be advantageous in joint tasks. However, little is known about how two people mutually exchange information to exploit the coupling. Therefore, we adopted a reversed, novel perspective to the standard one that focuses on the ability of physically coupled subjects to adapt to cooperative contexts that require negotiating a common plan: we investigated how training in pairs on a novel task affects the development of motor skills of each of the interacting partners. The task involved reaching movements in an unstable dynamic environment using a bilateral non-linear elastic tool that could be used bimanually or dyadically. The main result is that training with an expert leads to the greatest performance in the joint task. However, the performance in the individual test is strongly affected by the initial skill level of the partner. Moreover, practicing with a peer rather than an expert appears to be more advantageous for a naive; and motor skills can be transferred to a bimanual context, after training with an expert, only if the non-expert subject had prior experience of the dynamics of the novel task.

Introduction/Background Lower limb trauma can cause kinetic chains impairments that compromise quality of movement and postural stability A pilot study is now being conducted in INAIL Rehabilitation Center of Volterra using Hunova, a robotic system for lower limbs and core stability training and evaluation, to examine whether robot-assisted therapy is effective in motor control and gait performance recovery when compared to conventional rehabilitation programs. Material and method Hunova consists of two mobile platforms for exercising in both seated and upright mono and bipodalic conditions The device can operate in passive, active and assistive mode, detecting compensatory trunk movements with an inertial sensor and giving sensory feedback during exercise. The ongoing open randomized controlled trial foresees the enrolment of fifty-six patients with functional locomotor impairments following work-related injuries of the lower limbs Patients are randomly allocated to experimental or control group and receive a 3 weeks rehabilitation program and a pre- and post-treatment assessment including robotic, clinical and instrumental non-robotic evaluations. All participants undergo an individualized rehabilitation protocol, tailored to specific patient needs and injury characteristics; the experimental group perform instability and resistive training with Hunova; control subjects follow a training program using traditional non-robotic equipment Results Robotic therapy was well tolerated and easy to manage An interim analysis on 37 patients shows that both groups benefited the proposed training protocol and robotic therapy was not inferior to conventional rehabilitation; moreover, patients with distal lower extremity injury show a significantly greater improvement in statistic stability than patients with proximal lower extremity injury. Conclusion Hunova allows to measure significant parameters of static and dynamic stability and can centralize a complex progression of exercises to recover trunk control and reactive balance after traumatic injuries Final results of the study will contribute to explore the rule of robotic therapy in orthopedic conditions.

Background: Several neurodevelopmental disorders and brain injuries in children have been associated with proprioceptive dysfunction that will negatively affect their movement. Unfortunately, there is lack of reliable and objective clinical examination protocols and our current knowledge of how proprioception evolves in typically developing children is still sparse. Methods: Using a robotic exoskeleton, we investigated proprioceptive acuity of the wrist in a group of 49 typically developing healthy children (8–15 years), and a group of 40 young adults. Without vision participants performed an ipsilateral wrist joint position matching task that required them to reproduce (match) a previously experienced target position. All three joint degrees-of-freedom of the wrist/hand complex were assessed. Accuracy and precision were evaluated as a measure of proprioceptive acuity. The cross-sectional data indicating the time course of development of acuity were then fitted by four models in order to determine which function best describes developmental changes in proprioception across age. Results: First, the robot-aided assessment proved to be an easy to administer method for objectively measuring proprioceptive acuity in both children and adult populations. Second, proprioceptive acuity continued to develop throughout middle childhood and early adolescence, improving by more than 50% with respect to the youngest group. Adult levels of performance were reached approximately by the age of 12 years. An inverse-root function best described the development of proprioceptive acuity across the age groups. Third, wrist/forearm proprioception is anisotropic across the three DoFs with the Abduction/Adduction exhibiting a higher level of acuity than those of Flexion/extension and Pronation/Supination. This anisotropy did not change across development. Conclusions: Proprioceptive development for the wrist continues well into early adolescence. Our normative data obtained trough this novel robot-aided assessment method provide a basis against which proprioceptive function of pediatric population can be compared. This may aid the design of more effective sensorimotor intervention programs. Published version

This study examined the trainability of the proprioceptive sense and explored the relationship between proprioception and motor learning. With vision blocked, human learners had to perform goal-directed wrist movements relying solely on proprioceptive/haptic cues to reach several haptically specified targets. One group received additional somatosensory movement error feedback in form of vibro-tactile cues applied to the skin of the forearm. We used a haptic robotic device for the wrist and implemented a 3-day training regimen that required learners to make spatially precise goal-directed wrist reaching movements without vision. We assessed whether training improved the acuity of the wrist joint position sense. In addition, we checked if sensory learning generalized to the motor domain and improved spatial precision of wrist tracking movements that were not trained. The main findings of the study are: First, proprioceptive acuity of the wrist joint position sense improved after training for the group that received the combined proprioceptive/haptic and vibro-tactile feedback (VTF). Second, training had no impact on the spatial accuracy of the untrained tracking task. However, learners who had received VTF significantly reduced their reliance on haptic guidance feedback when performing the untrained motor task. That is, concurrent VTF was highly salient movement feedback and obviated the need for haptic feedback. Third, VTF can be also provided by the limb not involved in the task. Learners who received VTF to the contralateral limb equally benefitted. In conclusion, somatosensory training can significantly enhance proprioceptive acuity within days when learning is coupled with vibro-tactile sensory cues that provide feedback about movement errors. The observable sensory improvements in proprioception facilitates motor learning and such learning may generalize to the sensorimotor control of the untrained motor tasks. The implications of these findings for neurorehabilitation are discussed.

Neural processes of sensory-motor- and motor-sensory integration link perception and action, forming the basis for human interaction with the environment. Haptic perception, the ability to extract object features through action, is based on these processes. To study the development of motor-sensory integration, children judged the curvature of virtual objects after exploring them actively or while guided passively by a robot. Haptic acuity reached adult levels only at early adolescence. Unlike in adults, haptic precision in children was consistently lower during active exploration when compared to passive motion. Thus, the exploratory movements themselves constitute a form of noise for the developing haptic system that younger brains cannot compensate until mid-adolescence. Computationally, this is consistent with a noisy efference copy mechanism producing imprecise predicted sensory feedback, which compromises haptic precision in children, while the mature mechanism aids the adult brain to account for the effect of self-generated motion on perception.

Proprioceptive signals from peripheral mechanoreceptors form the basis for bodily perception and are known to be essential for motor control. However we still have an incomplete understanding of how proprioception differs between joints, whether it differs among the various degrees-of-freedom (DoFs) within a particular joint, and how such differences affect motor control and learning. We here introduce a robot-aided method to objectively measure proprioceptive function: specifically, we systematically mapped wrist proprioceptive acuity across the three DoFs of the wrist/hand complex with the aim to characterize the wrist position sense. Thirty healthy young adults performed an ipsilateral active joint position matching task with their dominant wrist using a haptic robotic exoskeleton. Our results indicate that the active wrist position sense acuity is anisotropic across the joint, with the abduction/adduction DoF having the highest acuity (the error of acuity for flexion/extension is 4.64 ± 0.24°; abduction/adduction: 3.68 ± 0.32°; supination/pronation: 5.15 ± 0.37°) and they also revealed that proprioceptive acuity decreases for smaller joint displacements. We believe this knowledge is imperative in a clinical scenario when assessing proprioceptive deficits and for understanding how such sensory deficits relate to observable motor impairments.

Neurological movement disorders such as stroke or sensory neuropathy are associated with somatosensory deficits. From a neurorehabilitation perspective, the assessment of proprioceptive function is important for planning and applying adequate rehabilitation treatments. Numerous behavioral and psychophysical methods are available to measure proprioceptive acuity. However, no universally accepted and adopted protocol exists. In recent years robotic devices have increasingly been used to investigate and assess proprioceptive function, but few studies have focused on the wrist joint. To fill this knowledge gap, this study aimed to systematically map the proprioceptive acuity of the wrist for its two joint degrees of freedom (DoF) - flexion/extension (FE) and abduction/adduction (AA). Twenty eight healthy young adults performed an ipsilateral, active joint position matching task using a robotic device. As a measure of proprioceptive acuity we determined the error between target position and the matched joint position. Results showed that: first, proprioceptive acuity varied between the two joint DoF with the matching error for AA being lower than the FE. Second, within each DoF, the motion direction did not affect the accuracy. Third, the radial component of the matching error showed DoF dependence: the FE movements tended to undershoot, while the AA movement overshot the target position. Results are indicative of a joint DoF dependent anisotropy of wrist proprioceptive acuity.

Upper limb robotic rehabilitation technology has recognized the importance of biofeedback signals for optimizing motor recovery. Impaired motor control is typically associated with abnormal muscle activation patterns and such patterns can be revealed by electromyography (EMG). However, before using user-generated EMG signals as biofeedback for controlling and optimizing force output of a robot, it is imperative that the healthy muscle innervation patterns are fully established to guide possible robot-aided rehabilitation protocols. Given the muscular redundancy found in many human limb systems, and given that force generation of human muscles is not linear, it becomes important to understand how synergistic control influences joint force and joint kinematics. It is the purpose of this study to map the electromyographic activation patterns of the major human muscles involved in controlling the hand/wrist system. By means of a robotic exoskeleton three Degrees of Freedom (DoF) were evaluated: wrist flexion-extension and adduction-abduction as well as forearm pronation-supination separately and for different ranges of the workspace. We recorded EMG activity of 7 arm muscles of 4 healthy subjects performing the task and we therefore defined the typical EMG activation patterns of such muscles during robotic training.

Several studies support the hypothesis that robot assisted therapy for adult subjects with motor impairments resulting from neurological damages can be beneficial in promoting the recovery process when conveyed in conjunction to conventional rehabilitation. Robotic therapy has been mainly applied to adult subjects and little is known about children or youth. This study presents the results of a robot-assisted rehabilitation training protocol applied to two young subjects suffering of hemiparesis. Robotic therapy was applied to the distal portion of the affected upper limb, through a fully backdrivable exoskeleton that allows full range of motion over the three degrees of freedom of the wrist. The training protocol consisted of ten therapy sessions and two days of robotic and clinical assessment pre and post training. With the main purpose of reducing the degree of motor impairment and promoting recovery, a control scheme was implemented which is characterized by an adaptive assistance delivered to the subjects as to help them completing the therapeutic task. The implementation of the new haptic controller is discussed in details and results are reported comparing the effect of robotic therapy for both dynamic and kinematic changes at the beginning and at end of the experiment. The results show that robot-assisted training successfully improved hand and wrist movement ability and promoted upper extremity functional recovery, thus highlighting the effectiveness of robotic therapy for both dynamic and kinematic motor performance.

Proprioception has a crucial role in promoting or hindering motor learning. In particular, an intact position sense strongly correlates with the chances of recovery after stroke. A great majority of neurological patients present both motor dysfunctions and impairments in kinesthesia, but traditional robot and virtual reality training techniques focus either in recovering motor functions or in assessing proprioceptive deficits. An open challenge is to implement effective and reliable tests and training protocols for proprioception that go beyond the mere position sense evaluation and exploit the intrinsic bidirectionality of the kinesthetic sense, which refers to both sense of position and sense of movement. Modulated haptic interaction has a leading role in promoting sensorimotor integration, and it is a natural way to enhance volitional effort. Therefore, we designed a preliminary clinical study to test a new proprioception-based motor training technique for augmenting kinesthetic awareness via haptic feedback. The feedback was provided by a robotic manipulandum and the test involved seven chronic hemiparetic subjects over 3 weeks. The protocol included evaluation sessions that consisted of a psychometric estimate of the subject’s kinesthetic sensation, and training sessions, in which the subject executed planar reaching movements in the absence of vision and under a minimally assistive haptic guidance made by sequences of graded force pulses. The bidirectional haptic interaction between the subject and the robot was optimally adapted to each participant in order to achieve a uniform task difficulty over the workspace. All the subjects consistently improved in the perceptual scores as a consequence of training. Moreover, they could minimize the level of haptic guidance in time. Results suggest that the proposed method is effective in enhancing kinesthetic acuity, but the level of impairment may affect the ability of subjects to retain their improvement in time. Published version

Is there any difference between matching the position of the hands by asking the subjects to move them to the same spatial location or to mirror-symmetric locations with respect to the body midline? If the motion of the hands were planned in the extrinsic space, the mirror-symmetric task would imply an additional challenge, because we would need to flip the coordinates of the target on the other side of the workspace. Conversely, if the planning were done in intrinsic coordinates, in order to move both hands to the same spot in the workspace, we should compute different joint angles for each arm. Even if both representations were available to the subjects, the two tasks might lead to different results, providing some cue on the organization of the "body schema". In order to answer such questions, the middle fingertip of the non-dominant hand of a population of healthy subjects was passively moved by a manipulandum to 20 different target locations. Subjects matched these positions with the middle fingertip of their dominant hand. For most subjects, the matching accuracy was higher in the extrinsic modality both in terms of systematic error and variability, even for the target locations in which the configuration of the arms was the same for both modalities. This suggests that the matching performance of the subjects could be determined not only by proprioceptive information but also by the cognitive representation of the task: expressing the goal as reaching for the physical location of the hand in space is apparently more effective than requiring to match the proprioceptive representation of joint angles.

SUMMARYAlthough proprioceptive impairment is likely to affect in a significant manner the capacity of stroke patients to recover functionality of upper limb, clinical assessment methods currently in use are rather crude, with a low level of reliability and a limited capacity to discriminate the relevant features of this severe deficit. In the present paper, we describe a new technique based on robot technology, with the goal of providing a reliable, accurate, and quantitative evaluation of kinesthetic acuity, which can be integrated in robot therapy. The proposed technique, based on a pulsed assistance paradigm, has been evaluated on a group of healthy subjects.

The term Robotic Rehabilitation defines a class of machines employed for different scenarios, ranging from therapeutic and assistive applications to robots devoted to neuroscience, behavioral research, and cognitive aspects. The first use of such technology dates back to early 1990s, with a relatively long history and it remains linked to the idea that robots, even with a certain degree of autonomy, must be directly controlled by humans while the interaction must be opportunely regulated in order to promote motor recovery or independent living. These devices are designed for individuals with neuromotor and cognitive disabilities to provide rehabilitative exercises or assistance for activity of daily living. They are also measurement systems i.e. they can incorporate sensors for monitoring kinematic and kinetic interaction with subjects such as movement, force or inertial sensors, or for detecting EMG signals to trigger the assistance or to provide – in more complex architectures – Functional Electric Stimulation (FES) to promote motor activity. In this chapter we will focus on therapeutic robots, which are usually employed to perform rehabilitation protocol, describing in details the most widely used control architectures, the implementation of rehabilitation exercises to restore specific motor functions and the measures of the corresponding performance.