Robotics

A hand‑exoskeleton and virtual‑reality system that fuses IMU and sEMG biosignals with AI‑based assessment to provide closed‑loop, assistance‑as‑needed rehabilitation for post‑stroke hand motor recovery. The study shows significant gains in FMA‑UE and high patient compliance.

After a neurological adverse event, restoring trunk functionality is essential for regaining balance, proprioception, and strength, all of which are critical for performing activities of daily living and enabling rehabilitation for impaired upper and lower limbs. Traditional therapy focuses on enhancing core strength, stability, and proprioceptive capabilities. Recent advancements in the field propose robotic solutions that utilize platforms to induce specific movements, stimulating muscular activation and prompting patients to respond to guided motions. These solutions often employ robotic seats that mimic traditional clinical tools, such as cushions or physiotherapy balls, to assist in mobilizing patients. In this work, we introduce a novel approach to trunk rehabilitation through a robotic system: a Series Elastic Actuator (SEA)-based trunk robotic mobilizer. This device is paired with a suite of control strategies designed to address various neurological conditions, including spinal cord injury, post-stroke impairments, and pusher syndrome.

Article explores the rise of humanoid robots, AI-driven training via simulations, and their potential roles in industry and defense. It discusses advances in autonomous learning, charging challenges, and the shift toward speech-based robot instruction.

Millions of individuals surviving a stroke have lifelong gait impairments that reduce their personal independence and quality of life. Reduced walking speed is one of the major problems limiting community mobility and reintegration. Previous studies have shown positive effect of robot-assisted gait training utilizing hip exoskeletons for individuals with gait impairments due to a stroke, leading to increased walking speed in post‑treatment compared to pre‑treatment assessments. However, no evidence emerged of a significant increasing in walking speed attributable to device usage compared to walking without the device. In this pilot investigation, we observed that hip flexion/extension assistance delivered by a portable bilateral powered hip exoskeleton increased overground self‑selected walking speed by 20.2 ± 5.0% on average among six chronic post‑stroke survivors. When comparing walking with and without the hip exoskeleton within the same experimental session, the observed speed increment resulted in statistically and clinically meaningful improvement (0.14 ± 0.03 m/s > minimal clinically important difference, p = 0.015). The increased walking speed was the result of a higher self‑selected cadence and longer step length both on the paretic and nonparetic limbs. By facilitating gait, a bilateral hip exoskeleton could be a viable technology for extending locomotor mobility and facilitating gait training of individuals affected by post‑stroke hemiparesis.

The aim of this study was to evaluate the feasibility of using a biofeedback-enhanced robotics-assisted tilt table (RATT) to investigate time- and intensity-dependent changes in heart rate variability (HRV) at rest and during heart rate-controlled exercise in patients recovering from a stroke. Twelve patients (age 55.3 years ± 15.6 years, 7 women) completed two separate measurement sessions. The first involved familiarization and system identification to determine parameters of a feedback system for automatic control of heart rate (HR). The second comprised 14 min of rest and 21 min of active exercise during which HR was held constant using feedback control to eliminate cardiovascular drift. HR data were collected using a chest-belt HR sensor, and raw RR intervals were employed for HRV analysis during periods of rest (0–7 min and 7–14 min) and exercise (5–13 min and 13–21 min). A biofeedback-enhanced, robotics-assisted tilt table can be successfully employed to perform heart rate-controlled exercises in patients after a stroke. All HRV metrics were substantially lower during exercise compared to rest. In the rest period, HRV values during 0–7 min were lower than during 7–14 min, in line with a slight HR decrease over the entire rest period. During exercise, HRV values during 5–13 min were higher than during 13–21 min, suggesting a time-dependent HRV decrease. All HRV metrics exhibited intensity- and time-dependent changes: higher HRV at rest and decreasing HRV over time. Understanding these HRV characteristics will support the development of heart rate-controlled exercise regimens and protocols for examining HRV changes during exercise in patients.

The article explores the promise and current limitations of humanoid robots, focusing on trust, AI-driven teleoperation, ethical concerns, and remote labor implications.

Introduction The use of visual and proprioceptive feedback is a key property of motor rehabilitation techniques. This feedback can be used alone, for example, for vision in mirror or video therapy, for proprioception in focal tendon vibration therapy, or in combination, for example, in robot-assisted training. This Electroencephalographic (EEG) study in healthy subjects explored the distinct neurophysiological impact of adding visual (video therapy), proprioceptive (focal tendinous vibration), or combined feedback (video therapy and focal tendinous vibration) to a motor imagery task. Methods Sixteen healthy volunteers performed 20 mental imagery (MI) tasks involving right wrist extension and flexion under four conditions: MI alone (IA), MI + video feedback observation (IO), MI + vibratory feedback (IV), and MI + observation + vibratory feedback (IOV). Brain activity was monitored with EEG, and time-frequency neurophysiological markers of movement were computed. The emotions of the patients were also measured during the task. Results In the alpha band, we observed bilateral ERD in the visual feedback conditions (IO, IOV). In the beta band, the ERD was bilateral in the IA, IV and IOV but more lateralized in the IV and IOV. After movement, we observed strong ERS in the IO and IOV but not in the IA or IV. Embodiment was stronger in conditions with vibratory feedback (IOV > IV > IA and IO). Conclusion Conditions with visual feedback (IO, IOV) recruit the mirror neurons system (alpha ERD) and provide more accurate feedback of the task than IA and IV, which triggers motor validation pathways (beta rebound analysis). Vibratory feedback enhances the recruitment of the left sensorimotor areas, with a synergistic effect in the IOV (beta ERD analysis), thus maximizing embodiment. Visual and vibratory feedback recruits the sensorimotor cortex during motor imagery in different ways and can be combined to maximize the benefits of both techniques

An opinion piece exploring how AI technologies—chatbots, generative art tools, autonomous vehicles, synthetic limbs, and assistive robotics—can improve accessibility and autonomy for people with disabilities.

Background Patients with neurological disorders including stroke use rehabilitation to improve cognitive abilities, to regain motor function and to reduce the risk of further complications. Robotics-assisted tilt table technology has been developed to provide early mobilisation and to automate therapy involving the lower limbs. The aim of this study was to evaluate the feasibility of employing a feedback control system for heart rate (HR) during robotics-assisted tilt table exercise in patients after a stroke. Methods This feasibility study was designed as a case series with 12 patients (n = 12) with no restriction on the time post-stroke or on the degree of post-stroke impairment severity. A robotics-assisted tilt table was augmented with force sensors, a work rate estimation algorithm, and a biofeedback screen that facilitated volitional control of a target work rate. Dynamic models of HR response to changes in target work rate were estimated in system identification tests; nominal models were used to calculate the parameters of feedback controllers designed to give a specified closed-loop bandwidth; and the accuracy of HR control was assessed quantitatively in feedback control tests. Results Feedback control tests were successfully conducted in all 12 patients. Dynamic models of heart rate response to imposed work rate were estimated with a mean root-mean-square (RMS) model error of 2.16 beats per minute (bpm), while highly accurate feedback control of heart rate was achieved with a mean RMS tracking error (RMSE) of 2.00 bpm. Control accuracy, i.e. RMSE, was found to be strongly correlated with the magnitude of heart rate variability (HRV): patients with a low magnitude of HRV had low RMSE, i.e. more accurate HR control performance, and vice versa. Conclusions Feedback control of heart rate during robotics-assisted tilt table exercise was found to be feasible. Future work should investigate robustness aspects of the feedback control system. Modifications to the exercise modality, or alternative modalities, should be explored that allow higher levels of work rate and heart rate intensity to be achieved.

For centuries scientists and technologists have sought artificial leg replacements that fully capture the versatility of their intact biological counterparts. However, biological gait requires coordinated volitional and reflexive motor control by complex afferent and efferent neural interplay, making its neuroprosthetic emulation challenging after limb amputation. Here we hypothesize that continuous neural control of a bionic limb can restore biomimetic gait after below‑knee amputation when residual muscle afferents are augmented. To test this hypothesis, we present a neuroprosthetic interface consisting of surgically connected, agonist–antagonist muscles including muscle‑sensing electrodes. In a cohort of seven leg amputees, the interface is shown to augment residual muscle afferents by 18% of biologically intact values. Compared with a matched amputee cohort without the afferent augmentation, the maximum neuroprosthetic walking speed is increased by 41%, enabling equivalent peak speeds to persons without leg amputation. Further, this level of afferent augmentation enables biomimetic adaptation to various walking speeds and real‑world environments, including slopes, stairs and obstructed pathways. Our results suggest that even a small augmentation of residual muscle afferents restores biomimetic gait under continuous neuromodulation in individuals with leg amputation.

Despite theoretical benefits of collaborative robots, disappointing outcomes are well documented by clinical studies, spanning rehabilitation, prostheses, and surgery. Cognitive load theory provides a possible explanation for why humans in the real world are not realizing the benefits of collaborative robots: high cognitive loads may be impeding human performance. Measuring cognitive availability using an electrocardiogram, we ask 25 participants to complete a virtual-reality task alongside an invisible agent that determines optimal performance by iteratively updating the Bellman equation. Three robots assist by providing environmental information relevant to task performance. By enabling the robots to act more autonomously—managing more of their own behavior with fewer instructions from the human—here we show that robots can augment participants’ cognitive availability and decision-making. The way in which robots describe and achieve their objective can improve the human’s cognitive ability to reason about the task and contribute to human–robot collaboration outcomes. Augmenting human cognition provides a path to improve the efficacy of collaborative robots. By demonstrating how robots can improve human cognition, this work paves the way for improving the cognitive capabilities of first responders, manufacturing workers, surgeons, and other future users of collaborative autonomy systems.

BACKGROUND: Upper limb (UL) motor impairment following stroke is a leading cause of functional limitations in activities of daily living. Robot-assisted therapy supports rehabilitation, but how its efficacy and the underlying neural mechanisms depend on the time after stroke is yet to be assessed. AIM: We investigated the response to an intensive protocol of robot-assisted rehabilitation in sub‑acute and chronic stroke patients, by analyzing the underlying changes in clinical scores, electroencephalography (EEG) and end‑effector kinematics. We aimed at identifying neural correlates of the participants’ upper limb motor function recovery, following an intensive 2‑week rehabilitation protocol. DESIGN: Prospective cohort study. SETTING: Inpatients and outpatients from the Neurorehabilitation Unit of Pisa University Hospital, Italy. POPULATION: Sub‑acute and chronic stroke survivors. METHODS: Thirty‑one stroke survivors (14 sub‑acute, 17 chronic) with mild‑to‑moderate UL paresis were enrolled. All participants underwent ten rehabilitative sessions of task‑oriented exercises with a planar end‑effector robotic device. All patients were evaluated with the Fugl‑Marie Assessment Scale and the Wolf Motor Function Test, at recruitment (T0), end‑of‑treatment (T1), and one‑month follow‑up (T2). Along with clinical scales, kinematic parameters and quantitative EEG were collected for each patient. Kinematics metrics were related to velocity, acceleration and smoothness of the movement. Relative power in four frequency bands was extracted from the EEG signals. The evolution over time of kinematic and EEG features was analyzed, in correlation with motor recovery. RESULTS: Both groups displayed significant gains in motility after treatment. Sub‑acute patients displayed more pronounced clinical improvements, significant changes in kinematic parameters, and a larger increase in Beta‑band in the motor area of the affected hemisphere. In both groups these improvements were associated to a decrease in the Delta‑band of both hemispheres. Improvements were retained at T2. CONCLUSIONS: The intensive two‑week rehabilitation protocol was effective in both chronic and sub‑acute patients, and improvements in the two groups shared similar dynamics. However, stronger cortical and behavioral changes were observed in sub‑acute patients suggesting different reorganizational patterns. CLINICAL REHABILITATION IMPACT: This study paves the way to personalized approaches to UL motor rehabilitation after stroke, as highlighted by different neurophysiological modifications following recovery in subacute and chronic stroke patients.

Stroke is a common worldwide health problem and a crucial contributor to gained disability. The abilities of people, who are subjected to stroke, to live independently are significantly affected since affected upper limbs’ functions are essential for our daily life. This review article focuses on emerging trends in BCI-controlled rehabilitation techniques based on EMG, EEG, or EGM + EEG signals in the last few years. Working on developing rehabilitation robotics, is considered a wealthy scientific area for researchers in the last period. There is a significant advantage that the human acquires from the interaction between the machine and his body, rehabilitation for a patient’s limb is very important to get the body limb recovery, and this is what is provided mostly by applying robotic devices.

Rehabilitation training for patients with motor disabilities usually requires specialized devices in rehabilitation centers. Home-based multi-purpose training would significantly increase treatment accessibility and reduce medical costs. While it is unlikely to equip a set of rehabilitation robots at home, we investigate the feasibility to use the general-purpose collaborative robot for rehabilitation therapies. In this work, we developed a new system for multi-purpose upper-limb rehabilitation training using a generic robot arm with human motor feedback and preference. We integrated surface electromyography, force/torque sensors, RGB-D cameras, and robot controllers with the Robot Operating System to enable sensing, communication, and control of the system. Imitation learning methods were adopted to imitate expert-provided training trajectories which could adapt to subject capabilities to facilitate in-home training. Our rehabilitation system is able to perform gross motor function and fine motor skill training with a gripper-based end-effector. We simulated system control in Gazebo and training effects (muscle activation level) in OpenSim and evaluated its real performance with human subjects. For all the subjects enrolled, our system achieved better training outcomes compared to specialist-assisted rehabilitation under the same conditions. Our work demonstrates the potential of utilizing collaborative robots for in-home motor rehabilitation training. Clinical relevance—The collaborative robot system is capable of providing safe and effective training comparable to specialized rehabilitation robots, enabling possibilities of convenient rehabilitation training at home.

This study was designed to investigate the feasibility and the potential effects on walking performance of a short gait training with a novel impairment-specific hip assistance (iHA) through a bilateral active pelvis orthosis (APO) in patients with acquired brain injury (ABI). Fourteen subjects capable of independent gait and exhibiting mild-to-moderate gait deficits

This paper investigates the EEG spectral feature modulations associated with fatigue induced by robot-mediated upper limb gross motor and fine motor interactions. Twenty healthy participants were randomly assigned to either perform a gross motor interaction with HapticMASTER or a fine motor interaction with SCRIPT passive orthosis for 20 minutes or until volitional fatigue. EEG relative and ratio band power measures were estimated from the data recorded before and after the interactions. Paired-samples t-tests found a significant increase in relative alpha band power on FC3, C3, P3 electrodes, and (θ + α)/β and α/β on C3 electrode following the gross motor interaction. Conversely, relative delta band power on C3 significantly decreased. A significant increase in relative alpha band power on FP1, C3 electrodes and relative theta band power on C4 electrode were found following the fine motor interaction whereas relative delta band power on FP1 electrode significantly decreased. Most participants reported an increase in their physical fatigue level following the gross movements and an increase in their mental fatigue level following the fine movements. Findings affirm that changes to localised brain activity patterns are an indication of fatigue developed from the robot-mediated interactions. It can be concluded that regional differences in the prominent EEG spectral features are most likely due to the differences in the nature of the task (fine/gross motor and distal/proximal upper limb) that may have differently altered an individual’s physical and mental fatigue level. The findings could potentially be utilised to monitor and moderate fatigue during robot-mediated post‑stroke therapies.

The recovery of symmetric and efficient walking is one of the key goals of a rehabilitation program in patients with stroke. The use of overground exoskeletons alongside conventional gait training might help foster rhythmic muscle activation in the gait cycle toward a more efficient gait. About twenty-nine patients with subacute stroke have been recruited and underwent either conventional gait training or experimental training, including overground gait training using a wearable powered exoskeleton alongside conventional therapy. Before and after the rehabilitation treatment, we assessed: (i) gait functionality by means of clinical scales combined to obtain a Capacity Score, and (ii) gait neuromuscular lower limbs pattern using superficial EMG signals. Both groups improved their ability to walk in terms of functional gait, as detected by the Capacity Score. However, only the group treated with the robotic exoskeleton regained a controlled rhythmic neuromuscular pattern in the proximal lower limb muscles, as observed by the muscular activation analysis. Coherence analysis suggested that the control group (CG) improvement was mediated mainly by spinal cord control, while experimental group improvements were mediated by cortical-driven control. In subacute stroke patients, we hypothesize that exoskeleton multijoint powered fine control overground gait training, alongside conventional care, may lead to a more fine-tuned and efficient gait pattern.

For decades, powered exoskeletons have been considered for possible employment in rehabilitation and personal use. Yet, these devices are still far from addressing the needs of users. Here, we introduce TWIN, a novel modular lower limb exoskeleton for personal use of spinal-cord injury (SCI) subjects. This system was designed according to a set of user requirements (lightweight and autonomous portability, quick and autonomous donning and setup, stability when standing/walking, cost effectiveness, long battery life, comfort, safety) which emerged during participatory investigations that organically involved patients, engineers, designers, physiatrists, and physical therapists from two major rehabilitation centers in Italy. As a result of this user-centered process, TWIN’s design is based on a variety of small mechatronic modules which are meant to be easily assembled and donned on or off by the user in full autonomy. This paper presents the development of TWIN, an exoskeleton for personal use of SCI users, and the application of user-centered design methods that are typically adopted in medical device industry, for its development. We can state that this approach revealed to be extremely effective and insightful to direct and continuously adapt design goals and activities toward the addressment of user needs, which led to the development of an exoskeleton with modular mechatronics and novel lateral quick release systems. Additionally, this work includes the preliminary assessment of this exoskeleton, which involved healthy volunteers and a complete SCI patient. Tests validated the mechatronics of TWIN and emphasized its high potential in terms of system usability for its intended use. These tests followed procedures defined in existing standards in usability engineering and were part of the formative evaluation of TWIN as a premise to the summative evaluation of its usability as medical device.

Voluntary control of sensorimotor rhythms (SMR, 8-12 Hz) can be used for brain-computer interface (BCI)-based operation of an assistive hand exoskeletons to restore lost hand function, e.g., in finger paralysis after stroke. To gain SMR control, stroke survivors are usually instructed to engage in motor imagery (MI) or to attempt moving the paralyzed fingers resulting in task- or event-related desynchronization (ERD) of SMR (SMR-ERD). However, as these tasks are cognitively demanding, and thus be important to identify biomarkers that predict decline in BCI control performance in order to optimize the man-machine interaction scheme. Here we determine the link between time over time and heart rate variability (HRV). Specifically, we investigated whether HRV can be used to predict decline during voluntary control of SMR-ERD across 17 healthy participants using SMR-ERD was visually displayed on a screen. Participants were instructed to engage in MI-based control over two consecutive runs of 8.5 minutes each. During the second run, task difficulty was gradually increased, while control performance (p = .18) and HRV (p = .16) remained unchanged across participants during the first run, during the second run, both measures declined over time at high correlation (performance: -0.61%/10s, p < .001). We found that HRV Granger-caused BCI control performance (p < .001) exhibited predictive characteristics of HRV on an individual participant level. These results suggest that HRV can predict decline in BCI performance paving the way for adaptive BCI control paradigms, e.g., to individualize and optimize assistive BCI systems in stroke.

Background: Overground Robot-Assisted Gait Training (o-RAGT) provides intensive gait rehabilitation. This study investigated the efficacy of o-RAGT in subacute stroke subjects, compared to conventional gait training. Methods: A multicenter randomized controlled trial was conducted on 75 subacute stroke subjects (38 in the Experimental Group (EG) and 37 in the Control Group (CG)). Both groups received 15 sessions of gait training (5 sessions/week for 60 min) and daily conventional rehabilitation. The subjects were assessed at the beginning (T1) and end (T2) of the training period with the primary outcome of a 6 Minutes Walking Test (6MWT), the Modified Ashworth Scale of the Affected lower Limb (MAS-AL), the Motricity Index of the Affected lower Limb (MI-AL), the Trunk Control Test (TCT), Functional Ambulation Classification (FAC), a 10 Meters Walking Test (10MWT), the modified Barthel Index (mBI), and the Walking Handicap Scale (WHS). Results: The 6MWT increased in both groups, which was confirmed by both frequentist and Bayesian analyses. Similar outcomes were registered in the MI-AL, 10MWT, mBI, and MAS-AL. The FAC and WHS showed a significant number of subjects improving in functional and community ambulation in both groups at T2. Conclusions: The clinical effects of o-RAGT were similar to conventional gait training in subacute stroke subjects. The results obtained in this study are encouraging and suggest future clinical trials on the topic.

Background: Stroke is a disease with a high associated disability burden. Robotic-assisted gait training offers an opportunity for the practice intensity levels associated with good functional walking outcomes in this population. Neural interfacing technology, electroencephalography (EEG), or electromyography (EMG) can offer new strategies for robotic gait re-education after a stroke by promoting more active engagement in movement intent and/or neurophysiological feedback. Objectives: This study identifies the current state-of-the-art and the limitations in direct neural interfacing with robotic gait devices in stroke rehabilitation. Methods: A pre-registered systematic review was conducted using standardized search operators that included the presence of stroke and robotic gait training and neural biosignals (EMG and/or EEG) and was not limited by study type. Results: From a total of 8,899 papers identified, 13 articles were considered for the final selection. Only five of the 13 studies received a strong or moderate quality rating as a clinical study. Three studies recorded EEG activity during robotic gait, two of which used EEG for BCI purposes. While demonstrating utility for decoding kinematic and EMG-related gait data, no EEG study has been identified to close the loop between robot and human. Twelve of the studies recorded EMG activity during or after robotic walking, primarily as an outcome measure. One study used multisource information fusion from EMG, joint angle, and force to modify robotic commands in real time, with higher error rates observed during active movement. A novel study identified used EMG data during robotic gait to derive the optimal, individualized robot-driven step trajectory. Conclusions: Wide heterogeneity in the reporting and the purpose of neurobiosignal use during robotic gait training after a stroke exists. Neural interfacing with robotic gait after a stroke demonstrates promise as a future field of study. However, as a nascent area, direct neural interfacing with robotic gait after a stroke would benefit from a more standardized protocol for biosignal collection and processing and for robotic deployment. Appropriate reporting for clinical studies of this nature is also required with respect to the study type and the participants’ characteristics.

. Collaborative robots and humans can cooperate in different industrial processes by combining their peculiar skills: the accuracy and repeatability of the manipulators can be exploited in synergy with human intelligence and flexibility. Since the cobots are safe and reliable, they can be adopted in the health sector, in particular in rehabilitation: the cobots allow the three-dimensional manipulation of the limbs and can be easily adapted to different anthropometric parameters. The kinematic models of the human-robot system presented in this paper can be exploited to develop motion planning algorithms for rehabilitation exercises. Furthermore, the estimation of the interaction forces in the human-robot interface can be obtained by multibody dynamic simulations. The proposed methodology is a starting point for the study of the integration of cobots into current rehabilitation practices, evaluating the feasibility and providing useful ideas in order to plan different man-robot working modalities.

To obtain synchronized gait assistance, this paper presents a new delayless adaptive dual-oscillator (ADO) scheme to address the inherent delay issue. In the ADO structure, a new oscillator is coupled with the primitive one but the phase is adaptively feed-forward compensated. It’s remarkable that the compensated phase is determined by the proposed extended phase lag observer, in which both the phase lag and phase leading can be properly estimated and eliminated in the steady and non‑steady gait. Moreover, a unified exoskeleton control scheme based on ADO is further proposed to improve the gait segmentation, velocity/acceleration estimation, intention estimation, and assistance generation performances, which further enhances the assistance synergy and reduces the safety risks. Experimental results demonstrate better alignment assistance and consequently reduced muscle efforts with ADO‑based assistance control.

Ageing population is now a global challenge, where physical deterioration is the common feature in elderly people. In addition, the diseases, such as spinal cord injury, stroke, and injury, could cause a partial or total loss of the ability of human locomotion. Thus, assistance is necessary for them to perform safe activities of daily living. Robotic hip exoskeletons are able to support ambulatory functions in elderly people and provide rehabilitation for the patients with gait impairments. They can also augment human performance during normal walking, loaded walking, and manual handling of heavy‐duty tasks by providing assistive force/torque. In this article, a systematic review of robotic hip exoskeletons is presented, where biomechanics of the human hip joint, pathological gait pattern, and common approaches to the design of robotic hip exoskeletons are described. Finally, limitations of the available robotic hip exoskeletons and their possible future directions are discussed, which could serve a useful reference for the engineers and researchers to develop robotic hip exoskeletons with practical and plausible applications in geriatric orthopaedics. *The translational potential of this article:* The past decade has witnessed a remarkable progress in research and development of robotic hip exoskeletons. Our aim is to summarize recent developments of robotic hip exoskeletons for the engineers, clinician scientists and rehabilitation personnel to develop efficient robotic hip exoskeletons for practical and plausible applications.

Lower limb exoskeletons require the correct support magnitude and timing to achieve user assistance. This study evaluated whether the sign of the angular velocity of lower limb segments can be used to determine the timing of the stance and the swing phase during walking. We assumed that stance phase is characterized by a positive, swing phase by a negative angular velocity. Thus, the transitions can be used to also identify heel-strike and toe-off. Thirteen subjects without gait impairments walked on a treadmill at speeds between 0.5 and 2.1 m/s on level ground and inclinations between -10 and +10°. Kinematic and kinetic data was measured simultaneously from an optical motion capture system, force plates, and five inertial measurement units (IMUs). These recordings were used to compute the angular velocities of four lower limb segments: two biological (thigh, shank) and two virtual that were geometrical projections of the biological segments (virtual leg, virtual extended leg). We analyzed the reliability (two sign changes of the angular velocity per stride) and the accuracy (offset in timing between sign change and ground reaction force based timing) of the virtual and biological segments for detecting the gait phases stance and swing. The motion capture data revealed that virtual limb segments seem superior to the biological limb segments in the reliability of stance and swing detection. However, increased signal noise when using the IMUs required additional rule sets for reliable stance and swing detection. With IMUs, the biological shank segment had the least variability in accuracy. The IMU-based heel-strike events of the shank and both virtual segment were slightly early (3.3-4.8% of the gait cycle) compared to the ground reaction force-based timing. Toe-off event timing showed more variability (9.0% too early to 7.3% too late) between the segments and changed with walking speed. The results show that the detection of the heel-strike, and thus stance phase, based on IMU angular velocity is possible for different segments when additional rule sets are included. Further work is required to improve the timing accuracy for the toe-off detection (swing).

Background: Wearable powered exoskeletons provide intensive overground gait training with patient’s active participation: these features promote a successful active motor relearning of ambulation in stroke survivors. Aim: The aim of this study was to investigate the feasibility and the clinical effects of an overground exoskeleton-assisted gait training (OEAGT) in subacute stroke patients. Design: Prospective, pilot pre-post, open label, non-randomized experimental study. Setting: Four Italian neurological rehabilitation centers. Population: Forty-eight subacute stroke patients were enrolled. Two patients dropped out because of medical problems. Data analysis was conducted on 46 subjects (56.84±14.29 years; 27 male; 29 ischemic; 24 left hemiparesis). Methods: Patients underwent 15±2 sessions (60 min/session, 3-5 times/week) of OEAGT. Clinical and gait assessments were performed at the beginning (T1) and at the end (T2) of the training period: modified Barthel Index (BI), modified Ashworth Scale at Hip (MAS-H), Knee (MAS-K), and Ankle (MAS-A) level, Motricity Index (MI), Trunk Control Test (TCT), Functional Ambulation Classification (FAC), Walking Handicap Scale (WHS), 10-Meter Walking Test (10MWT), 6-Minute Walking Test (6mWT), Timed Up-and-Go test (TUG). The Technology Acceptance Model (TAM) questionnaire evaluated the acceptance of OEAGT by patients. Data stratification was performed using the time post the acute event and the onset of rehabilitation treatment, and the MI at T1. Wilcoxon’s test (P&lt;0.05) was used. Results: All clinical scales significantly improved at T2; no statistically significant changes were reported for MAS-H, MAS-K, MAS-A. The 69.57% patients were able to walk at T1; 17.39% were not able to walk at T1 but regained ambulation at T2; and 13.04% were not able to walk at either T1 or T2. The ambulant patients showed a statistical improvement in speed measured during the 10MWT and in the distance covered over a time of 6 minutes (6mWT). The results from the TAM questionnaire showed that all subjects perceived the OEAGT positively. The data stratification analysis suggests that the OEAGT does not have any restriction of use. Conclusions: The OEAGT improved the clinical and gait outcomes in subacute patients. Randomized studies on larger samples are needed to confirm these data and to assess the efficacy of OEAGT. Clinical rehabilitation impact: Introduce innovative rehabilitation strategies based on customized OEAGT.

Recovery of upper and lower limbs function is essential to reach independence in daily activities in patients with upper motor neuron syndrome (UMNS). Rehabilitation can provide a guide for motor recovery influencing the neurobiology of neuronal plasticity providing controlled, repetitive, and variable patterns. Increasing therapy dosage, intensity, number of repetition, execution of task-oriented exercises, and combining top-down and bottom-up approaches can promote plasticity and functional recovery. Robotic exoskeletons for upper and lower limbs, based on the principle of motor learning, have been introduced in neurorehabilitation. In this narrative review, we provide an overview of literature published on exoskeleton devices for upper and lower limb rehabilitation in patients with UMNS; we summarized the available current research evidence and outlined the new challenges that neurorehabilitation and bioengineering will have to face in the upcoming years. Robotic treatment should be considered a rehabilitation tool useful to generate a more complex, controlled multisensory stimulation of the patient and useful to modify the plasticity of neural connections through the experience of movement. Efficacy and efficiency of robotic treatment should be defined starting from intensity, complexity, and specificity of the robotic exercise, that are related to human-robot interaction in terms of motion, emotion, motivation, meaning of the task, feedback from the exoskeleton, and fine motion assistance. Duration of a single session, global period of the treatment, and the timing for beginning of robotic treatment are still open questions. There is the need to evaluate and individualize the treatment according to patient’s characteristics. Robotic devices for upper and lower limbs open a window to define therapeutic modalities as possible beneficial drug, able to boost biological, neurobiological, and epigenetic changes in central nervous system. We need to implement large and innovative research programs to answer these issues in the near future.

Background: Wearable powered robotic exoskeletons allow patients with complete spinal cord injury (SCI) to practice over‑ground real‑world gait scenarios. The global functional interaction subject‑exoskeleton is a key factor to produce interlimb coordinated movements. Efficacy and efficiency of over‑ground walking abilities using powered exoskeletons are related not only to the symbiotic sensory‑motor interaction subject‑exoskeleton but also to exoskeleton control. Aim: Assess if walking ability of motor complete SCI patients at thoracic or lower level, using a wearable powered exoskeleton (ReWalk), can be influenced by different exoskeleton software control. Design: Observational study; an open, non‑comparative, non‑randomized study. Setting: A single neurological rehabilitation center for inpatients and outpatients. Population: Fifteen SCI chronic patients (4 females and 11 males) were recruited and divided in two groups: group 1, trained with the first software generation of ReWalk, and group 2, trained with the second software generation, a software upgrade of the previous version. Methods: Subjects were trained during three 60‑minute sessions a week, during at least eight weeks using ReWalk, a wearable lower limb powered exoskeleton that allows thoracic or lower level motor‑complete individuals with SCI to walk, stand, sit and climb/descend stairs. Outcome measures, collected at the end of the training period wearing the exoskeleton, were: 6‑min Walking Test, 10‑m Walking Test, and the time necessary to pass from sitting to standing and start to walk (STS‑time). For each group Pearson Coefficient was calculated to explore correlations between the subjects’ characteristics and gait performance reached at the end of the training period. Results: Group 1 showed correlation between performances and weight, height, neurological lesion level, while group 2 showed no correlation between performances weight and height, but correlation only with neurological lesion level. Group 2 covered more distance in 6 min (+124.52%) and required less time (-70.34%) to perform 10 mtWT and to STS‑time (-38.25%) if compared to group 1. Conclusions: ReWalk allows chronic complete spinal cord injury patients to perform over‑ground walking. Different exoskeleton software control of the smoothness of the gait pattern improves functional outcome, eliminating the relationship between anthropometric factors and gait performances. The smoothness of the kinematic control of the lower limbs of the exoskeleton is a key factor to facilitate human‑robot interaction and to increase walking abilities of the subject. Clinical rehabilitation impact: To underline how the kinematic control of the exoskeleton influences the walking abilities of the complex system subject‑exoskeleton.

Prolong walking is a notable risk factor for work-related lower-limb disorders (WRLLD) in industries such as agriculture, construction, service profession, healthcare and retail works. It is one of the common causes of lower limb fatigue or muscular exhaustion leading to poor balance and fall. Exoskeleton technology is seen as a modern strategy to assist worker’s in these professions to minimize or eliminate the risk of WRLLDs. Exoskeleton has potentials to benefit workers in prolong walking (amongst others) by augmenting their strength, increasing their endurance, and minimizing high muscular activation, resulting in overall work efficiency and productivity. Controlling exoskeleton to achieve this purpose for able-bodied personnel without impeding their natural movement is, however, challenging. In this study, we propose a control strategy that integrates a Dual Unscented Kalman Filter (DUKF) for trajectory generation/prediction of the spatio-temporal features of human walking (i.e. joint position, and velocity, and acceleration) and an impedance cum supervisory controller to enable the exoskeleton to follow this trajectory to synchronize with the human walking.

The intrinsic soft appealing ca healthcare the tec ties e nature of compliant supernumerary limbs and exosuits makes them candidates for assisting human movements, with potential applications in e, human augmentation and logistics. In the following chapter, we describe chnology used in exosuits and supernumerary limbs for assistance of activi-s of daily living, with emphasis on aiding grasping and flexion/extension of the h elbow joint. We discuss the mechanical design principles of such devices, detail the control paradigms that can be used for intention detection and present the design and evaluation of cutaneous interfaces used for force feedback rendering. Tests on healthy and impaired subjects highlight that exosuits and supernumerary limbs are potential cost-effective and intrinsically safe solutions for increasing the capabilities of healthy subjects and improving the quality of life of subjects suffering from motor disorders.

Stroke‑related locomotor impairments are often associated with abnormal timing and intensity of recruitment of the affected and non‑affected lower limb muscles. Restoring the proper lower limbs muscles activation is a key factor to facilitate recovery of gait capacity and performance, and to reduce maladaptive plasticity. Ekso is a wearable powered exoskeleton robot able to support over‑ground gait training. The user controls the exoskeleton by triggering each single step during the gait cycle. The fine‑tuning of the exoskeleton control system is crucial‑it is set according to the residual functional abilities of the patient, and it needs to ensure lower limbs powered gait to be the most physiological as possible. This work focuses on the definition of an automatic calibration procedure able to detect the best Ekso setting for each patient. EMG activity has been recorded from Tibialis Anterior, Soleus, Rectus Femoris, and Semitendinosus muscles in a group of 7 healthy controls and 13 neurological patients. EMG signals have been processed so to obtain muscles activation patterns. The mean muscular activation pattern derived from the controls cohort has been set as reference. The developed automatic calibration procedure requires the patient to perform overground walking trials supported by the exoskeleton while changing parameters setting. The Gait Metric index is calculated for each trial, where the closer the performance is to the normative muscular activation pattern, in terms of both relative amplitude and timing, the higher the Gait Metric index is. The trial with the best Gait Metric index corresponds to the best parameters set. It has to be noted that the automatic computational calibration procedure is based on the same number of overground walking trials, and the same experimental set‑up as in the current manual calibration procedure. The proposed approach allows supporting the rehabilitation team in the setting procedure. It has been demonstrated to be robust, and to be in agreement with the current gold standard (i.e. manual calibration performed by an expert engineer). The use of a graphical user interface is a promising tool for the effective use of an automatic procedure in a clinical context.

A better understanding of the neural substrates that underlie motor recovery after stroke has led to the development of innovative rehabilitation strategies and tools that incorporate key elements of motor skill relearning, that is, intensive motor training involving goal-oriented repeated movements. Robotic devices for the upper limb are increasingly used in rehabilitation. Studies have demonstrated the effectiveness of these devices in reducing motor impairments, but less so for the improvement of upper limb function. Other studies have begun to investigate the benefits of combined approaches that target muscle function (functional electrical stimulation and botulinum toxin injections), modulate neural activity (noninvasive brain stimulation), and enhance motivation (virtual reality) in an attempt to potentialize the benefits of robot-mediated training. The aim of this paper is to overview the current status of such combined treatments and to analyze the rationale behind them.

With the increase in the elderly, stroke has become a common disease, often leading to motor dysfunction and even permanent disability. Lower-limb rehabilitation robots can help patients to carry out reasonable and effective training to improve the motor function of paralyzed extremity. In this paper, the developments of lower-limb rehabilitation robots in the past decades are reviewed. Specifically, we provide a classification, a comparison, and a design overview of the driving modes, training paradigm, and control strategy of the lower-limb rehabilitation robots in the reviewed literature. A brief review on the gait detection technology of lower-limb rehabilitation robots is also presented. Finally, we discuss the future directions of the lower-limb rehabilitation robots.

This chapter presents a lower limb exoskeleton mechatronic design. The design aims to be used as a walking support device focused on patients who suffer of partial lower body paralysis due to spine injuries or caused by a stroke. First, the mechanical design is presented and the results are validated through dynamical simulations performed in Autodesk Inventor and MATLAB. Second, a communication network design is proposed in order to establish a secure and fast data link between sensors, actuators, and microprocessors. Finally, patient‑exoskeleton system interaction is presented and detailed. Movement generation is performed by means of digital signal processing techniques applied to electromyography (EMG) and electrocardiography (EEG) signals. Such interaction system design is tested and evaluated in MATLAB whose results are presented and explained. A proposal of real‑time supervisory control is also presented as a part of the integration of every component of the exoskeleton.

Background: Recovery of therapeutic or functional ambulatory capacity in post-stroke patients is a primary goal of rehabilitation. Wearable powered exoskeletons allow patients with gait dysfunctions to perform over-ground gait training, even immediately after the acute event. Aim: To investigate the feasibility and the clinical effects of an over-ground walking training with a wearable powered exoskeleton in sub-acute and chronic stroke patients. Design: Prospective, pilot pre-post, open label, non-randomized experimental study. Setting: A single neurological rehabilitation center for inpatients and outpatients. Population: Twenty-three post-stroke patients were enrolled: 12 sub-acute (mean age: 43.8±13.3 years, 5 male and 7 female, 7 right hemiparesis and 5 left hemiparesis) and 11 chronic (mean age: 55.5±15.9 years, 7 male and 4 female, 4 right hemiparesis and 7 left hemiparesis) patients. Methods: Patients underwent 12 sessions (60 min/session, 3 times/week) of walking rehabilitation training using Ekso™, a wearable bionic suit that enables individuals with lower extremity disabilities and minimal forearm strength to stand up, sit down and walk over a flat hard surface with a full weight-bearing reciprocal gait. Clinical evaluations were performed at the beginning of the training period (t0), after 6 sessions (t1) and after 12 sessions (t2) and were based on the Ashworth scale, Motricity Index, Trunk Control Test, Functional Ambulation Scale, 10-Meter Walking Test, 6-Minute Walking Test, and Walking Handicap Scale. Wilcoxon’s test (P<0.05) was used to detect significant changes. Results: Statistically significant improvements were observed at the three assessment periods for both groups in Motricity Index, Functional Ambulation Scale, 10-meter walking test, and 6-minute walking test. Sub-acute patients achieved statistically significant improvement in Trunk Control Test and Walking Handicap Scale at t0-t2. Sub-acute and chronic patient did not achieve significant improvement in Ashworth scale at t0-t2. Conclusions: Twelve sessions of over-ground gait training using a powered wearable robotic exoskeleton improved ambulatory functions in sub-acute and chronic post-stroke patients. Large, randomized multicenter studies are needed to confirm these preliminary data. Clinical rehabilitation impact: To plan a completely new individual tailored robotic rehabilitation strategy after stroke, including task-oriented over-ground gait training.

A prototype for a walking assistance apparatus for the elderly or rehabilitants of motor palsy patients was developed as a next-generation vehicle or movable neuro-rehabilitation training appliance, using a novel spatial parallel link mechanism and a bearing lift. The flat steps of the apparatus move in parallel with the ground; the apparatus can support entire leg alignment (including soles) and assist; walking behavior at ankle, knee and hip joints simultaneously. To respond to the variation of equipped person’s walking velocity, the length of stride and walking cycle while walking with wearing the apparatus were compensated by using walking ratio. Therefore the apparatus can be controlled in response to equipped person’s will. Next, we developed a control method of the apparatus by using impedance control, taking into account the dynamics of the apparatus and the legs of an equipped person, and assist ratio for the equipped person. By adjusting the value of natural angular frequency of the desired dynamic equation for the equipped person, this apparatus can assist walking according to the equipped person’s desired response of the apparatus. Furthermore, motor palsy and muscle weakness patients can walk by themselves by using the apparatus; patients who have ambulation difficulty can use the apparatus with weight bearing lift that we developed. Using the apparatus with the weight bearing lift prevents stumbling and enables input of walking movement to the brain motor area.

In recent years, gait robots have become increasingly common for gait rehabilitation in non-ambulatory stroke patients. Cardiovascular treadmill training, which has been shown to provide great benefit to stroke survivors, cannot be performed with non-ambulatory patients. We therefore integrated cardiovascular training in robot-assisted gait therapy to combine the benefits of both training modi. We developed a model of human heart rate as a function of exercise parameters during robot-assisted gait training and applied it for automatic control purposes. This structural model of the physiological processes describes the change in heart rate caused by treadmill speed and the power exchanged between robot and subject. We performed physiological parameter estimation for each tested individual and designed a model-based feedback controller to guide heart rate to a desired time profile. Five healthy subjects and eight stroke patients were recorded for model parameter identification, which was successfully used for heart rate control of three healthy subjects. We showed that a model-based control approach can take into account patient-specific limitations of treadmill speed as well as individual power expenditure.

Body weight supported treadmill training (BWSTT) assisted with a robotic-driven gait orthosis is utilized in rehabilitation of individuals with lost motor skills. A typical rehabilitation session included: sitting, standing, suspension, robotic-assisted walking at 1.5 and 2.5km/h, respectively with 50% body weight support and recovery. While the effects of robotic-assisted BWSTT on motor performances were deeply studied, the influences on the cardiovascular control are still unknown. The aim of the study was to evaluate in stroke (ST) and cervical spondylotic myelopathy (CSM) patients: (1) the autonomic response during a traditional robotic-assisted BWSTT session of motor rehabilitation; (2) the effects of 30 daily sessions of BWSTT on cardiovascular regulation. The autonomic response was assessed through symbolic analysis of short-term heart rate variability in 11 pathologic subjects (5 ST and 6 CSM patients) whose motor skills were improved as a result of the rehabilitation therapy. Results showed variable individual responses to the rehabilitation session in ST patients at the beginning of the therapy. At the end of the rehabilitation process, the responses of ST patients were less variable and more similar to those previously observed in healthy subjects. CSM patients exhibited an exaggerated vagal response to the fastest walking phase during the first rehabilitative session. This abnormal response was limited after the last rehabilitative session. We conclude that robotic-assisted BWSTT is helpful in restoring cardiovascular control in rehabilitation-responsive ST patients and limiting vagal responses in rehabilitation-responsive CSM patients.

During the last decade we assisted to relevant progress in rehabilitation studies and in technological development. From the combination of these issues rises the tele-rehabilitation – a subfield of telemedicine consisting of a system to control rehabilitation “at distance” – as an actual possibility of application and a promising development in the future. The rehabilitation studies demonstrate that in order to increase the efficacy, the rehabilitation program should: start as soon as possible; be intensive as much as possible; be prolonged during the recovery phase at home. On the other hand the technological field offers now robotic or automatated machines, electronically controlled, that are suitable to be used locally to increase the intensity of rehabilitation and to introduce new exercise paradigms. These systems might be used also at distance and controlled via telecommunication systems. Many initiatives have been taken to develop telemedicine applications in rehabilitation. Published studies and current experiences show that tele-rehabilitation mainly addresses: – patient’s functional assessment; – patient’s clinical management at distance; – management of rehabilitation programs by remote; – selection of the needs of the patient or the caregiver; – tele-consulting; – education of professionals and care