Robot-based Rehabilitation Research Articles

The role of virtual reality in improving motor performance as revealed by EEG: a randomized clinical trial

BackgroundMany studies have demonstrated the usefulness of repetitive task practice by using robotic-assisted gait training (RAGT) devices, including Lokomat, for the treatment of lower limb paresis. Virtual reality (VR) has proved to be a valuable tool to improve neurorehabilitation training. The aim of our pilot randomized clinical trial was to understand the neurophysiological basis of motor function recovery induced by the association between RAGT (by using Lokomat device) and VR (an animated avatar in a 2D VR) by studying electroencephalographic (EEG) oscillations.MethodsTwenty-four patients suffering from a first unilateral ischemic stroke in the chronic phase were randomized into two groups. One group performed 40 sessions of Lokomat with VR (RAGT + VR), whereas the other group underwent Lokomat without VR (RAGT-VR). The outcomes (clinical, kinematic, and EEG) were measured before and after the robotic intervention.ResultsAs compared to the RAGT-VR group, all the patients of the RAGT + VR group improved in the Rivermead Mobility Index and Tinetti Performance Oriented Mobility Assessment. Moreover, they showed stronger event-related spectral perturbations in the high-γ and β bands and larger fronto-central cortical activations in the affected hemisphere.ConclusionsThe robotic-based rehabilitation combined with VR in patients with chronic hemiparesis induced an improvement in gait and balance. EEG data suggest that the use of VR may entrain several brain areas (probably encompassing the mirror neuron system) involved in motor planning and learning, thus leading to an enhanced motor performance.Trial registrationRetrospectively registered in Clinical Trials on 21-11-2016, n.NCT02971371.

Upper Limb Rehabilitation in People With Multiple Sclerosis

Background. There has been an increasing research interest in upper limb rehabilitation in multiple sclerosis (MS). The current changes in the research field inquire a new literature review. Objective. This systematic review aimed to provide an overview of the upper limb rehabilitation strategies in people with MS (PwMS). Methods. Articles published in PubMed and Web of Knowledge were selected when written in English, published in the past 25 years, peer reviewed, that included at least 5 PwMS, and described the effects of an intervention study including rehabilitation strategies targeting the upper limbs. Included articles were screened based on title/abstract and full text by 2 independent reviewers. Results. Thirty articles met the criteria and were included for data extraction. Only half of the included studies investigated the effects of a training program specially targeted toward the upper limbs, while in the other studies, a general whole body therapy was used. The therapy content and dosage varied greatly between the different included studies. Multidisciplinary and robot-based rehabilitation were the most investigated rehabilitation strategies and showed to improve upper limb capacity. Strength and endurance training improved the upper limb body functions and structures but did not influence the upper limb capacity and performance. Conclusions. The results of this systematic review indicated that different types of upper limb rehabilitation strategies can improve upper limb function in PwMS. Further research is necessary to compare directly the effects of different rehabilitation strategies and to investigate the optimal therapy dosage according to the upper limb disability level.

Robot-assisted humanized passive rehabilitation training based on online assessment and regulation.

Robot-assisted rehabilitation has been developed and proved effective for motion function recovery. Humanization is one of the crucial issues in the designing of robot-based rehabilitation system. However, most of the previous investigations focus on the simplex position control when comes to the control system design of robot-assisted passive training, and pay little attention to the dynamic adjustment according to the patient's performances. This paper presents a novel method to design the passive training system using a developed assessing-and-regulating section to online assess the subject's performances. The motion regulating mechanism is designed to dynamically adjust the training range and motion speed according to the actual performances, which is helpful to improve the humanization of the rehabilitation training. Moreover, position-based impedance control is adopted to achieve compliant trajectory tracking movement. Experimental results demonstrate that the proposed method presents good performances not only in motion control but also in humanization.

Monitoring Neuro-Motor Recovery From Stroke With High-Resolution EEG, Robotics and Virtual Reality: A Proof of Concept.

A novel system for the neuro-motor rehabilitation of upper limbs was validated in three sub-acute post-stroke patients. The system permits synchronized cortical and kinematic measures by integrating high-resolution EEG, passive robotic device and Virtual Reality. The brain functional re-organization was monitored in association with motor patterns replicating activities of daily living (ADL). Patients underwent 13 rehabilitation sessions. At sessions 1, 7 and 13, clinical tests were administered to assess the level of motor impairment, and EEG was recorded during rehabilitation task execution. For each session and rehabilitation task, four kinematic indices of motor performance were calculated and compared with the outcome of clinical tests. Functional source maps were obtained from EEG data and projected on the real patients' anatomy (MRI data). Laterality indices were calculated for hemispheric dominance assessment. All patients showed increased participation in the rehabilitation process. Cortical activation changes during recovery were detected in relation to different motor patterns, hence verifying the system's suitability to add quantitative measures of motor performance and neural recovery to classical tests. We conclude that this system seems a promising tool for novel robot-based rehabilitation paradigms tailored to individual needs and neuro-motor responses of the patients.

Upper Extremity Proprioception in Healthy Aging and Stroke Populations, and the Effects of Therapist- and Robot-Based Rehabilitation Therapies on Proprioceptive Function

The world’s population is aging, with the number of people ages 65 or older expected to surpass 1.5 billion people, or 16% of the global total. As people age, there are notable declines in proprioception due to changes in the central and peripheral nervous systems. Moreover, the risk of stroke increases with age, with approximately two-thirds of stroke-related hospitalizations occurring in people over the age of 65. In this literature review, we first summarize behavioral studies investigating proprioceptive deficits in normally aging older adults and stroke patients, and discuss the differences in proprioceptive function between these populations. We then provide a state of the art review the literature regarding therapist- and robot-based rehabilitation of the upper extremity proprioceptive dysfunction in stroke populations and discuss avenues of future research.

Hybrid-Mode Impedance Control for Position/Force Tracking in Motor-System Rehabilitation

This paper proposes a new robot controller for motor-system rehabilitation. The proposed controller simultaneously realizes rehabilitation motion tracking and force generation, as predefined through a musculoskeletal model-based optimization process. We introduce control parameters of weighted control action priorities for the motion-tracking and force-generation tasks, based on the position-tracking error. With the weighted control action priorities, the robot accords higher priority to motion tracking at the robot end point when the position-tracking error is larger than a threshold value, and to force generation when the position-tracking error is smaller than a threshold value. Smooth motion trajectory has to be designed and applied in robot-based rehabilitation. Through simulations and experimental results, we show the usefulness of the proposed control method.

The FES-assisted control for a lower limb rehabilitation robot: simulation and experiment

Abstract To design a control strategy for iLeg, an exoskeleton robot developed for lower limb rehabilitation aiming at investigating the feasibility of integrating functional electrical stimulation (FES) with robot-based rehabilitation training, an FES-assisted training strategy combined with impedance control, has been proposed in this paper. Through impedance control, an active compliance of the robot is established, and the patient’s voluntary effort to accomplish the training task is inspired. During the training process, the patient’s related muscles are applied with FES which provides an extra assistance to the patient. The intensity of the FES is properly chosen in order to induce a desired active torque which is proportional to the voluntary effort extracted from the electromyography signals of the related muscles using back propagation neural networks. This kind of enhancement serves as a positive feedback which reminds the patient of the correct attempt to fulfill the desired motion. FES control is conducted by a combination of neural network-based feedforward controller and a PD feedback controller. Simulation conducted using Matlab and the experiment with a spinal cord injury subject and a healthy subject have shown satisfactory results which verify the feasibility of this control strategy.

Toward minimum effort reaching trajectories formation in robot-based rehabilitation after stroke: an innovative guidance scheme proposition.

In therapy after stroke, intensive and repetitive training is crucial for relearning of motor abilities and functionalities. Besides conventional therapy, rehabilitation robotic systems are used in the treatment, where a minimum jerk model is used widely in the formation of the point-to-point movement trajectory, which is not necessarily the appropriate choice for hemiparetic upper extremity training. This paper examines and analyzes the influence of a selected form of a flexor muscle tightness on trajectory formation and proposes a guidance scheme that yields minimum effort in robot-assisted arm reaching movement. A dynamic upper extremity model with the three clinically most relevant muscles that develop tightness because of spasticity after stroke was used in the optimization study that examined key features of trajectory formation. The results showed that the trajectories and their velocity profiles become significantly different in the presence of muscle tightness. On the basis of dynamic optimization results, we experimentally examined selected trajectories in a selected individual with chronic hemiparesis. The experimental results confirmed the importance of appropriate selection of reaching trajectories' velocity profiles. The results of optimization and experimentation showed the importance of the velocity profile of the robot-based guidance scheme, which has an influence on the necessary invested 'effort' between starting/ending points to overcome muscle tightness. This study showed that muscle tightness exerts a significant influence on trajectory formation as well as on its velocity profile. The proposed innovative guidance scheme might be useful for practical arm reaching robot-supported movement training in the clinical environment. We suggested that for each hemiparetic patient, the initial identification session before training should experimentally determine the 'optimal' parameters for the rehabilitation guidance scheme that would optimally match the particular muscle tightness constraints.

Restoring Sensory Feedback Enables Real-Time Control of Prosthetic Hand [From the Field

The experimentation also highlighted the importance of reactivating tactile feedback to enable the patient to use the robotic prosthesis with dexterity. On 5 February 2013, the results of the second major experimental step of the LifeHand project were unveiled in conjunction with the publication of a related research article in the international journal Science Translational Medicine [1]. The work is coauthored by a group of Italian and other European research centers: 1) Scuola Superiore Sant'Anna, 2) Catholic University of Rome, 3) Campus Bio-Medico University of Rome, 4) IRCSS San Raffaele La Pisana, 5) EPFL-Switzerland, 6) University of Freiburg-Germany, and 7) Aalborg University-Denmark. LifeHand2 is the natural evolution of the research that led to the 2008 success of LifeHand1. The patient was an Italian-Brazilian national, Pierpaolo Petruzziello, who had undergone the exact same amputation (left arm immediately below the elbow) as Dennis Aabo Sorensen, the subject of this second experimentation. Starting from the demonstration of the possibility of restoring fine motor control capabilities in amputees by exploiting learning processes based on sensory feedback, it is expected that LifeHand2 can trigger many new research developments in the field of robotic prostheses and robot-based rehabilitation and assistive solutions.

Robot Training of Upper Limb in Multiple Sclerosis: Comparing Protocols With or WithoutManipulative Task Components

In this pilot study, we compared two protocols for robot-based rehabilitation of upper limb in multiple sclerosis (MS): a protocol involving reaching tasks (RT) requiring arm transport only and a protocol requiring both objects' reaching and manipulation (RMT). Twenty-two MS subjects were assigned to RT or RMT group. Both protocols consisted of eight sessions. During RT training, subjects moved the handle of a planar robotic manipulandum toward circular targets displayed on a screen. RMT protocol required patients to reach and manipulate real objects, by moving the robotic arm equipped with a handle which left the hand free for distal tasks. In both trainings, the robot generated resistive and perturbing forces. Subjects were evaluated with clinical and instrumental tests. The results confirmed that MS patients maintained the ability to adapt to the robot-generated forces and that the rate of motor learning increased across sessions. Robot-therapy significantly reduced arm tremor and improved arm kinematics and functional ability. Compared to RT, RMT protocol induced a significantly larger improvement in movements involving grasp (improvement in Grasp ARAT sub-score: RMT 77.4%, RT 29.5%, p=0.035) but not precision grip. Future studies are needed to evaluate if longer trainings and the use of robotic handles would significantly improve also fine manipulation.

Inter-hemispheric coupling changes associate with motor improvements after robotic stroke rehabilitation

In the chronic phase of stroke brain plasticity plays a crucial role for further motor control improvements. This study aims to assess the brain plastic reorganizations and their association with clinical progresses induced by a robot-aided rehabilitation program in chronic stroke patients. 7 stroke patients with an upper limb motor impairment in chronic phase underwent a multi-modal evaluation before starting and at the end of a 12-week upper-limb neurorehabilitation program. Fugl-Meyer Assessment (FMA) Scale scores and performance indices of hand movement performance (isometric pinch monitored through a visual feedback) were collected. Cerebral reorganizations were characterized by 32-channel electroencephalography (EEG) focusing on ipsilesional and contralesional resting state properties investigating both bipolar derivations overlying the middle cerebral artery territory and the primary somatosensory sources (S1) obtained through the Functional Source Separation (FSS) method. Power Spectral Density (PSD) and interhemispheric coherence (IHCoh) at rest were measured and correlated with clinical and hand control robot-induced improvements. After the robotic rehabilitation we found an improvement of FMAS scores and hand motor control performance and changes of brain connectivity in high frequency rhythms (24-90 Hz). In particular, the improvement of motor performance correlated with the modulation of the interhemispheric S1 coherence in the high beta band (24-33 Hz). Recently it has been shown that an upper limb robot-based rehabilitation improves motor performance in stroke patients. We confirm this potential and demonstrate that a robot-aided rehabilitation program induces brain reorganizations. Specifically, interhemispheric connectivity between primary somatosensory areas got closer to a 'physiological level' in parallel with the acquisition of more accurate hand control.

Robot-based rehabilitation of the upper limb in stroke patients: A longitudinal observational study

Robot-based rehabilitation of the upper limb in stroke patients: A longitudinal observational study

Robot-based rehabilitation of the upper limbs in multiple sclerosis: Feasibility and preliminary results

To make a preliminary evaluation of the feasibility of a robot-based rehabilitation protocol for the improvement of upper limb motor co-ordination in a group of patients with multiple sclerosis. Seven patients with multiple sclerosis underwent a training protocol of 8 sessions. During each session patients performed reaching movements toward virtual targets presented on a screen, by moving the handle of a robot, which generated resistive and disturbing forces. Each subject was evaluated before and after the treatment by means of clinical and instrumental tests. After the 8-session treatment, all patients significantly improved the velocity, linearity and smoothness of their reaching movements. Moreover, this amelioration was also present in other kinds of movement, not executed during the sessions. Results on the Nine-Hole Peg Test showed a clinically relevant improvement in the treated arm of 4 out of 7 patients, suggesting also a transfer of the therapy effect to tasks more related to activities of daily living. The preliminary results of this pilot study suggest that robot therapy can be applied to patients with multiple sclerosis in a clinical setting and may be beneficial for reduction of the upper limb motor co-ordination deficit.

Towards a Smooth Human–Robot Interaction for Rehabilitation Robotic Systems

The goal of this work is to develop a control framework to provide assistance to the subjects in such a manner that the interaction between the subjects and a robot-assisted rehabilitation system is smooth during the rehabilitation therapy. In order to achieve smoothness of interaction, a control framework is designed in such a way that it can automatically adjust the control gains of the robot-assisted rehabilitation system to modify the interaction dynamics between the system and the subject. An artificial neural network (ANN)-based proportional–integral (PI) gain scheduling controller is proposed to automatically determine the appropriate control gains for each individual subject. The human arm model is integrated with the ANN-based PI gain scheduling controller where the ANN uses estimated human arm parameters to select the appropriate PI gains for each subject such that the resultant interaction dynamics between the subject and the robot-assisted rehabilitation system could result in smooth interaction. Experimental results involving unimpaired subjects on a PUMA robot-based rehabilitation system are presented to demonstrate the efficacy of the proposed ANN-based PI gain scheduling controller on unimpaired subjects.