Testing Dynamic Balance in People with Multiple Sclerosis: A Correlational Study between Standard Posturography and Robotic-Assistive Device.

BACKGROUND: Robotic devices are known to provide pivotal parameters to assess motor functions in Multiple Sclerosis (MS) as dynamic balance. However, there is still a lack of validation studies comparing innovative technologies with standard solutions. Thus, this study's aim was to compare the postural assessment of fifty people with MS (PwMS) during dynamic tasks performed with the gold standard EquiTest® and the robotic platform hunova®, using Center of Pressure (COP)-related parameters and global balance indexes. METHODS: Pearson's ρ correlations were run for each COP-related measure and the global balance index was computed from EquiTest® and hunova® in both open (EO) and closed-eyes (EC) conditions. RESULTS: Considering COP-related parameters, all correlations were significant in both EO (0.337 ≤ ρ ≤ 0.653) and EC (0.344 ≤ ρ ≤ 0.668). Furthermore, Pearson's analysis of global balance indexes revealed relatively strong for visual and vestibular, and strong for somatosensory system associations (ρ = 0.573; ρ = 0.494; ρ = 0.710, respectively). CONCLUSIONS: Findings confirm the use of hunova® as a valid device for dynamic balance assessment in MS, suggesting that such a robotic platform could allow for a more sensitive assessment of balance over time, and thus a better evaluation of the effectiveness of personalized treatment, thereby improving evidence-based clinical practice.

Evaluation of a novel technology-supported fall prevention intervention - study protocol of a multi-centre randomised controlled trial in older adults at increased risk of falls.

BACKGROUND: Increasing number of falls and fall-related injuries in an aging society give rise to the need for effective fall prevention and rehabilitation strategies. Besides traditional exercise approaches, new technologies show promising options for fall prevention in older adults. As a new technology-based approach, the hunova robot can support fall prevention in older adults. The objective of this study is to implement and evaluate a novel technology-supported fall prevention intervention using the hunova robot compared to an inactive control group. The presented protocol aims at introducing a two-armed, multi-centre (four sites) randomised controlled trial, evaluating the effects of this new approach on the number of falls and number of fallers as primary outcomes. METHODS: The full clinical trial incorporates community-dwelling older adults at risk of falls with a minimum age of 65 years. Including a one-year follow-up measurement, all participants are tested four times. The training programme for the intervention group comprises 24-32 weeks in which training sessions are scheduled mostly twice a week; the first 24 training sessions use the hunova robot, these are followed by a home-based programme of 24 training sessions. Fall-related risk factors as secondary endpoints are measured using the hunova robot. For this purpose, the hunova robot measures the participants' performance in several dimensions. The test outcomes are input for the calculation of an overall score which indicates the fall risk. The hunova-based measurements are accompanied by the timed-up-and-go test as a standard test within fall prevention studies. DISCUSSION: This study is expected to lead to new insights which may help establish a new approach to fall prevention training for older adults at risk of falls. First positive results on risk factors can be expected after the first 24 training sessions using the hunova robot. As primary outcomes, the number of falls and fallers within the study (including the one-year follow-up period) are the most relevant parameters that should be positively influenced by our new approach to fall prevention. After the study completion, approaches to examine the cost-effectiveness and develop an implementation plan are relevant aspects for further steps. TRIAL REGISTRATION: German Clinical Trial Register (DRKS), ID: DRKS00025897. Prospectively registered 16 August 2021, https://drks.de/search/de/trial/DRKS00025897 .

Robotic balance assessment in community-dwelling older people with different grades of impairment of physical performance.

BACKGROUND: 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. AIMS: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Robot-aided developmental assessment of wrist proprioception in children.

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.

Relationship between Timed Up and Go performance and quantitative biomechanical measures of balance.

Traumatic brain injury (TBI) impairs sensory-motor functions, with debilitating consequences on postural control and balance, which persist during the chronic stages of recovery. The Timed Up and Go (TUG) test is a reliable, safe, time-efficient, and one of the most widely used clinical measures to assess gait, balance, and fall risk in TBI patients and is extensively used in inpatient and outpatient settings. Although the TUG test has been used extensively due to its ease of performance and excellent reliability, limited research has been published that investigates the relationship between TUG performance and quantitative biomechanical measures of balance. The objective of this paper was to quantify the relationship between biomechanical variables of balance and the TUG scores in individuals with chronic TBI. Regression models were constructed using six biomechanical variables to predict TUG scores. The model that conservatively removed gait speed (i.e., TUG-1/GS) gave the best results, achieving a root-mean-square error of ∼±2 s and explaining over 69% of the variability.

Parkinson's disease accelerates age-related decline in haptic perception by altering somatosensory integration.

This study investigated how Parkinson's disease alters haptic perception and the underlying mechanisms of somatosensory and sensorimotor integration. Changes in haptic sensitivity and acuity (the abilities to detect and to discriminate between haptic stimuli) due to Parkinson's disease were systematically quantified and contrasted to the performance of healthy older and young adults. Using a robotic force environment, virtual contours of various curvatures were presented. Participants explored these contours with their hands and indicated verbally whether they could detect or discriminate between two contours. To understand what aspects of sensory or sensorimotor integration are altered by ageing and disease, we manipulated the sensorimotor aspect of the task: the robot either guided the hand along the contour or the participant actively moved the hand. Active exploration relies on multimodal sensory and sensorimotor integration, while passive guidance only requires sensory integration of proprioceptive and tactile information. The main findings of the study are as follows: first, a decline in haptic precision can already be observed in adults before the age of 70 years. Parkinson's disease may lead to an additional decrease in haptic sensitivity well beyond the levels typically seen in middle-aged and older adults. Second, the haptic deficit in Parkinson's disease is general in nature. It becomes manifest as a decrease in sensitivity and acuity (i.e. a smaller perceivable range and a diminished ability to discriminate between two perceivable haptic stimuli). Third, thresholds during both active and passive exploration are elevated, but not significantly different from each other. That is, active exploration did not enhance the haptic deficit when compared to passive hand motion. This implies that Parkinson's disease affects early stages of somatosensory integration that ultimately have an impact on processes of sensorimotor integration. Our results suggest that the known motor problems in Parkinson's disease that are generally characterized as a failure of sensorimotor integration may, in fact, have a sensory origin.

Standard versus innovative robotic balance assessment for people with multiple sclerosis: a correlational study.

INTRODUCTION: Balance disorders are common in people with Multiple Sclerosis (PwMS) and, together with other impairments and disabilities, often prevent PwMS from performing their daily living activities. Besides clinical scales and performance tests, robotic platforms can provide more sensitive, specific, and objective monitoring. Validated technologies have been adopted as gold standard, but innovative robotic solutions would represent an opportunity to detect balance impairment in PwMS. AIM: Study's aim was to compare postural assessment of 46 PwMS with a relapsing-remitting form during static tasks performed with the novel robotic platform hunova® and the gold standard EquiTest®, METHODS: Pearson's r was run on Center of Pressure (COP)-related parameters and global static balance measures computed from hunova® and EquiTest® in eyes-open (EO) and eyes-closed (EC) conditions. In addition, agreeableness level toward the use of both devices was tested through numeric rating scale. RESULTS: Considering COP-related parameters, correlations were significant for all measures (p < .001). Interestingly, in EO, a strong correlation was shown for sway area (r = .770), while Medio-Lateral (ML) and Anterior-Posterior (AP) oscillation range, path length, ML and AP speed, ML and AP root mean square distance had a relatively strong association (.454 ≤ r ≤ .576). In EC, except for ML oscillation range showing a relatively strong correlation (r = .532), other parameters were strongly associated (.603 ≤ r ≤ .782). Correlations between global balance indexes of hunova® and EquiTest® revealed a relatively strong association between the Somatosensory Score in EquiTest® and the Somatosensory Index in hunova® (r = - .488). While in EO Static Balance Index from hunova® was highly correlated with Equilibrium score of EquiTest® (r = .416), Static Balance Index had a relatively strong association with both the Equilibrium (r = .482) and Strategy Score (r = .583) of EquiTest® in EC. Results from agreeableness rating scale revealed that hunova® was highly appreciated compared to EquiTest® (p = .044). CONCLUSIONS: hunova® represents an innovative adjunct to standard robotic balance evaluation for PwMS. This confirms that combining traditional and robotic assessments can more accurately detect balance impairments in MS.

Two hands, one perception: how bimanual haptic information is combined by the brain.

Humans routinely use both of their hands to gather information about shape and texture of objects. Yet, the mechanisms of how the brain combines haptic information from the two hands to achieve a unified percept are unclear. This study systematically measured the haptic precision of humans exploring a virtual curved object contour with one or both hands to understand if the brain integrates haptic information from the two hemispheres. Bayesian perception theory predicts that redundant information from both hands should improve haptic estimates. Thus exploring an object with two hands should yield haptic precision that is superior to unimanual exploration. A bimanual robotic manipulandum passively moved the hands of 20 blindfolded, right-handed adult participants along virtual curved contours. Subjects indicated which contour was more "curved" (forced choice) between two stimuli of different curvature. Contours were explored uni- or bimanually at two orientations (toward or away from the body midline). Respective psychophysical discrimination thresholds were computed. First, subjects showed a tendency for one hand to be more sensitive than the other with most of the subjects exhibiting a left-hand bias. Second, bimanual thresholds were mostly within the range of the corresponding unimanual thresholds and were not predicted by a maximum-likelihood estimation (MLE) model. Third, bimanual curvature perception tended to be biased toward the motorically dominant hand, not toward the haptically more sensitive left hand. Two-handed exploration did not necessarily improve haptic sensitivity. We found no evidence that haptic information from both hands is integrated using a MLE mechanism. Rather, results are indicative of a process of "sensory selection", where information from the dominant right hand is used, although the left, nondominant hand may yield more precise haptic estimates.

Motor commands in children interfere with their haptic perception of objects.

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.

A Lifespan Approach to Balance in Static and Dynamic Conditions: The Effect of Age on Balance Abilities.

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.

Inter-limb interference during bimanual adaptation to dynamic environments.

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.

Predicted sensory feedback derived from motor commands does not improve haptic sensitivity.

Haptic perception is based on the integration of afferent proprioceptive and tactile signals. A further potential source of information during active touch is predicted sensory feedback (PSF) derived from a copy of efferent motor commands that give rise to the exploratory actions. There is substantial evidence that PSF is important for predicting the sensory consequences of action, but its role in perception is unknown. Theoretically, PSF leads to a higher redundancy of haptic information, which should improve sensitivity of the haptic sense. To investigate the effect of PSF on haptic precision, blindfolded subjects haptically explored the curved contour of a virtual object generated by a robotic manipulandum. They either actively moved their hand along the contour, or their hand was moved passively by the device along the same contour. In the active condition afferent sensory information and PSF were present, while in the passive condition subjects relied solely on afferent information. In each trial, two stimuli of different curvature were presented. Subjects needed to indicate which of the two was more "curved" (forced choice). For each condition, the detection and three discrimination thresholds were computed. The main finding is that absence of efference copy information did not systematically degrade haptic acuity. This indirectly implies that PSF does not aid or enhance haptic perception. We conclude that when maximum haptic sensitivity is required to explore novel objects, the perceptual system relies primarily on afferent tactile and proprioceptive information, and PSF has no added effect on the precision of the perceptual estimate.

Adaptive robot training for the treatment of incoordination in Multiple Sclerosis.

BACKGROUND: Cerebellar symptoms are extremely disabling and are common in Multiple Sclerosis (MS) subjects. In this feasibility study, we developed and tested a robot therapy protocol, aimed at the rehabilitation of incoordination in MS subjects. METHODS: Eight subjects with clinically defined MS performed planar reaching movements while grasping the handle of a robotic manipulandum, which generated forces that either reduced (error-reducing, ER) or enhanced (error-enhancing, EE) the curvature of their movements, assessed at the beginning of each session. The protocol was designed to adapt to the individual subjects' impairments, as well as to improvements between sessions (if any). Each subject went through a total of eight training sessions. To compare the effect of the two variants of the training protocol (ER and EE), we used a cross-over design consisting of two blocks of sessions (four ER and four EE; 2 sessions/week), separated by a 2-weeks rest period. The order of application of ER and EE exercises was randomized across subjects. The primary outcome measure was the modification of the Nine Hole Peg Test (NHPT) score. Other clinical scales and movement kinematics were taken as secondary outcomes. RESULTS: Most subjects revealed a preserved ability to adapt to the robot-generated forces. No significant differences were observed in EE and ER training. However over sessions, subjects exhibited an average 24% decrease in their NHPT score. The other clinical scales showed small improvements for at least some of the subjects. After training, movements became smoother, and their curvature decreased significantly over sessions. CONCLUSIONS: The results point to an improved coordination over sessions and suggest a potential benefit of a short-term, customized, and adaptive robot therapy for MS subjects.

Self-adaptive robot training of stroke survivors for continuous tracking movements.

BACKGROUND: Although robot therapy is progressively becoming an accepted method of treatment for stroke survivors, few studies have investigated how to adapt the robot/subject interaction forces in an automatic way. The paper is a feasibility study of a novel self-adaptive robot controller to be applied with continuous tracking movements. METHODS: The haptic robot Braccio di Ferro is used, in relation with a tracking task. The proposed control architecture is based on three main modules: 1) a force field generator that combines a non linear attractive field and a viscous field; 2) a performance evaluation module; 3) an adaptive controller. The first module operates in a continuous time fashion; the other two modules operate in an intermittent way and are triggered at the end of the current block of trials. The controller progressively decreases the gain of the force field, within a session, but operates in a non monotonic way between sessions: it remembers the minimum gain achieved in a session and propagates it to the next one, which starts with a block whose gain is greater than the previous one. The initial assistance gains are chosen according to a minimal assistance strategy. The scheme can also be applied with closed eyes in order to enhance the role of proprioception in learning and control. RESULTS: The preliminary results with a small group of patients (10 chronic hemiplegic subjects) show that the scheme is robust and promotes a statistically significant improvement in performance indicators as well as a recalibration of the visual and proprioceptive channels. The results confirm that the minimally assistive, self-adaptive strategy is well tolerated by severely impaired subjects and is beneficial also for less severe patients. CONCLUSIONS: The experiments provide detailed information about the stability and robustness of the adaptive controller of robot assistance that could be quite relevant for the design of future large scale controlled clinical trials. Moreover, the study suggests that including continuous movement in the repertoire of training is acceptable also by rather severely impaired subjects and confirms the stabilizing effect of alternating vision/no vision trials already found in previous studies.

Dynamic Stability and Trunk Control Improvements Following Robotic Balance and Core Stability Training in Chronic Stroke Survivors: A Pilot Study.

Stroke survivors show greater postural oscillations and altered muscular activation compared to healthy controls. This results in difficulties in walking and standing, and in an increased risk of falls. A proper control of the trunk is related to a stable walk and to a lower falling risk; to this extent, rehabilitative protocols are currently working on core stability. The main objective of this work was to evaluate the effectiveness of trunk and balance training performed with a new robotic device designed for evaluation and training of balance and core stability, in improving the recovery of chronic stroke patients compared with a traditional physical therapy program. Thirty chronic stroke patients, randomly divided in two groups, either underwent a traditional rehabilitative protocol, or a robot-based program. Each patient was assessed before and after the rehabilitation and at 3-months follow-up with clinical and robot-based evaluation exercises focused on static and dynamic balance and trunk control. Results from clinical scores showed an improvement in both groups in balance and trunk control. Robot-based indices analysis indicated that the experimental group showed greater improvements in proprioceptive control, reactive balance and postural control in unstable conditions, compared to the control group, showing an improved trunk control with reduced compensatory strategies at the end of the training. Moreover, the experimental group had an increased retention of the benefits obtained with training at 3 months follow up. These results support the idea that such robotic device is a promising tool for stroke rehabilitation.

Development and validation of a robotic multifactorial fall-risk predictive model: A one-year prospective study in community-dwelling older adults.

BACKGROUND: Falls 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. METHODS: Community-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. RESULTS: Of 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 (p<0.001), respectively. The best model that comprised only robotic parameters (the 20 parameters identified in the final model) achieved a better performance than the clinical parameters alone, but worse than the combination of both clinical and robotic variables (ROC AUC: 0.73, 95% CI 0.63-0.83). CONCLUSION: A 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.

Robot therapy of the upper limb in stroke patients: preliminary experiences for the principle-based use of this technology.

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.

Robot therapy for stroke survivors: proprioceptive training and regulation of assistance.

Robot therapy seems promising with stroke survivors, but it is unclear which exercises are most effective, and whether other pathologies may benefit from this technique. In general, exercises should exploit the adaptive nature of the nervous system, even in chronic patients. Ideally, exercise should involve multiple sensory modalities and, to promote active subject participation, the level of assistance should be kept to a minimum. Moreover, exercises should be tailored to the different degrees of impairment, and should adapt to changing performance. To this end, we designed three tasks: (i) a hitting task, aimed at improving the ability to perform extension movements; (ii) a tracking task, aimed at improving visuo-motor control; and (iii) a bimanual task, aimed at fostering inter-limb coordination. All exercises are conducted on a planar manipulandum with two degrees of freedom, and involve alternating blocks of exercises performed with and without vision. The degree of assistance is kept to a minimum, and adjusted to the changing subject's performance. All three exercises were tested on chronic stroke survivors with different levels of impairment. During the course of each exercise, movements became faster, smoother, more precise, and required decreasing levels of assistive force. These results point to the potential benefit of that assist-as-needed training with a proprioceptive component in a variety of clinical conditions.

Design and Development of a Novel Core, Balance and Lower Limb Rehabilitation Robot: hunova®.

This article describes the motivation behind and the technical aspects at the basis of the development of the innovative rehabilitation robot hunova®. The paper describes in detail the hardware and software design of the system and summarizes the clinical studies carried out to validate the technology.

Robot-based assessment of sitting and standing balance: preliminary results in Parkinson's disease.

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.