Verena Klamroth-Marganska

Three-dimensional, task-specific robot therapy of the arm after stroke: a multicentre, parallel-group randomised trial

BACKGROUND Arm hemiparesis secondary to stroke is common and disabling. We aimed to assess whether robotic training of an affected arm with ARMin--an exoskeleton robot that allows task-specific training in three dimensions-reduces motor impairment more effectively than does conventional therapy. METHODS In a prospective, multicentre, parallel-group randomised trial, we enrolled patients who had had motor impairment for more than 6 months and moderate-to-severe arm paresis after a cerebrovascular accident who met our eligibility criteria from four centres in Switzerland. Eligible patients were randomly assigned (1:1) to receive robotic or conventional therapy using a centre-stratified randomisation procedure. For both groups, therapy was given for at least 45 min three times a week for 8 weeks (total 24 sessions). The primary outcome was change in score on the arm (upper extremity) section of the Fugl-Meyer assessment (FMA-UE). Assessors tested patients immediately before therapy, after 4 weeks of therapy, at the end of therapy, and 16 weeks and 34 weeks after start of therapy. Assessors were masked to treatment allocation, but patients, therapists, and data analysts were unmasked. Analyses were by modified intention to treat. This study is registered with ClinicalTrials.gov, number NCT00719433. FINDINGS Between May 4, 2009, and Sept 3, 2012, 143 individuals were tested for eligibility, of whom 77 were eligible and agreed to participate. 38 patients assigned to robotic therapy and 35 assigned to conventional therapy were included in analyses. Patients assigned to robotic therapy had significantly greater improvements in motor function in the affected arm over the course of the study as measured by FMA-UE than did those assigned to conventional therapy (F=4.1, p=0.041; mean difference in score 0.78 points, 95% CI 0.03-1.53). No serious adverse events related to the study occurred. INTERPRETATION Neurorehabilitation therapy including task-oriented training with an exoskeleton robot can enhance improvement of motor function in a chronically impaired paretic arm after stroke more effectively than conventional therapy. However, the absolute difference between effects of robotic and conventional therapy in our study was small and of weak significance, which leaves the clinical relevance in question. FUNDING Swiss National Science Foundation and Bangerter-Rhyner Stiftung.

Effects of intensive arm training with the rehabilitation robot ARMin II in chronic stroke patients: four single-cases

BackgroundRobot-assisted therapy offers a promising approach to neurorehabilitation, particularly for severely to moderately impaired stroke patients. The objective of this study was to investigate the effects of intensive arm training on motor performance in four chronic stroke patients using the robot ARMin II.MethodsARMin II is an exoskeleton robot with six degrees of freedom (DOF) moving shoulder, elbow and wrist joints. Four volunteers with chronic (≥ 12 months post-stroke) left side hemi-paresis and different levels of motor severity were enrolled in the study. They received robot-assisted therapy over a period of eight weeks, three to four therapy sessions per week, each session of one hour.Patients 1 and 4 had four one-hour training sessions per week and patients 2 and 3 had three one-hour training sessions per week. Primary outcome variable was the Fugl-Meyer Score of the upper extremity Assessment (FMA), secondary outcomes were the Wolf Motor Function Test (WMFT), the Catherine Bergego Scale (CBS), the Maximal Voluntary Torques (MVTs) and a questionnaire about ADL-tasks, progress, changes, motivation etc.ResultsThree out of four patients showed significant improvements (p < 0.05) in the main outcome. The improvements in the FMA scores were aligned with the objective results of MVTs. Most improvements were maintained or even increased from discharge to the six-month follow-up.ConclusionData clearly indicate that intensive arm therapy with the robot ARMin II can significantly improve motor function of the paretic arm in some stroke patients, even those in a chronic state. The findings of the study provide a basis for a subsequent controlled randomized clinical trial.

Towards more effective robotic gait training for stroke rehabilitation: a review

BackgroundStroke is the most common cause of disability in the developed world and can severely degrade walking function. Robot-driven gait therapy can provide assistance to patients during training and offers a number of advantages over other forms of therapy. These potential benefits do not, however, seem to have been fully realised as of yet in clinical practice.ObjectivesThis review determines ways in which robot-driven gait technology could be improved in order to achieve better outcomes in gait rehabilitation.MethodsThe literature on gait impairments caused by stroke is reviewed, followed by research detailing the different pathways to recovery. The outcomes of clinical trials investigating robot-driven gait therapy are then examined. Finally, an analysis of the literature focused on the technical features of the robot-based devices is presented. This review thus combines both clinical and technical aspects in order to determine the routes by which robot-driven gait therapy could be further developed.ConclusionsActive subject participation in robot-driven gait therapy is vital to many of the potential recovery pathways and is therefore an important feature of gait training. Higher levels of subject participation and challenge could be promoted through designs with a high emphasis on robotic transparency and sufficient degrees of freedom to allow other aspects of gait such as balance to be incorporated.

A robotic system to train activities of daily living in a virtual environment

In the past decade, several arm rehabilitation robots have been developed to assist neurological patients during therapy. Early devices were limited in their number of degrees of freedom and range of motion, whereas newer robots such as the ARMin robot can support the entire arm. Often, these devices are combined with virtual environments to integrate motivating game-like scenarios. Several studies have shown a positive effect of game-playing on therapy outcome by increasing motivation. In addition, we assume that practicing highly functional movements can further enhance therapy outcome by facilitating the transfer of motor abilities acquired in therapy to daily life. Therefore, we present a rehabilitation system that enables the training of activities of daily living (ADL) with the support of an assistive robot. Important ADL tasks have been identified and implemented in a virtual environment. A patient-cooperative control strategy with adaptable freedom in timing and space was developed to assist the patient during the task. The technical feasibility and usability of the system was evaluated with seven healthy subjects and three chronic stroke patients.

ARMin - Exoskeleton Robot for Stroke Rehabilitation

Rehabilitation robots are becoming an important tool in rehabilitation of stroke, SCI and other neurological pathologies. Compared to manual arm training, robot-supported training can be more intensive, of longer duration, repetitive and task-oriented. Therefore, such devices have the potential to improve the rehabilitation process in stroke patients. Whereas a majority of previous work in upper limb rehabilitation robotics has focused on end-effector based robots, a shift toward exoskeleton robots is taking place because they offer a better guidance of the human arm, especially for movements with large range of motions. One of the first actuated exoskeleton robot that is ready for deployment in clinics is the ARMin III robot. This paper gives a short overview of the ongoing clinical application and evaluation process of the ARMin III robot.

Robot-Assisted Arm Assessments in Spinal Cord Injured Patients: A Consideration of Concept Study

Robotic assistance is increasingly used in neurological rehabilitation for enhanced training. Furthermore, therapy robots have the potential for accurate assessment of motor function in order to diagnose the patient status, to measure therapy progress or to feedback the movement performance to the patient and therapist in real time. We investigated whether a set of robot-based assessments that encompasses kinematic, kinetic and timing metrics is applicable, safe, reliable and comparable to clinical metrics for measurement of arm motor function. Twenty-four healthy subjects and five patients after spinal cord injury underwent robot-based assessments using the exoskeleton robot ARMin. Five different tasks were performed with aid of a visual display. Ten kinematic, kinetic and timing assessment parameters were extracted on joint- and end-effector level (active and passive range of motion, cubic reaching volume, movement time, distance-path ratio, precision, smoothness, reaction time, joint torques and joint stiffness). For cubic volume, joint torques and the range of motion for most joints, good inter- and intra-rater reliability were found whereas precision, movement time, distance-path ratio and smoothness showed weak to moderate reliability. A comparison with clinical scores revealed good correlations between robot-based joint torques and the Manual Muscle Test. Reaction time and distance-path ratio showed good correlation with the “Graded and Redefined Assessment of Strength, Sensibility and Prehension” (GRASSP) and the Van Lieshout Test (VLT) for movements towards a predefined position in the center of the frontal plane. In conclusion, the therapy robot ARMin provides a comprehensive set of assessments that are applicable and safe. The first results with spinal cord injured patients and healthy subjects suggest that the measurements are widely reliable and comparable to clinical scales for arm motor function. The methods applied and results can serve as a basis for the future development of end-effector and exoskeleton-based robotic assessments.

Robot-aided assessment of lower extremity functions: a review

The assessment of sensorimotor functions is extremely important to understand the health status of a patient and its change over time. Assessments are necessary to plan and adjust the therapy in order to maximize the chances of individual recovery. Nowadays, however, assessments are seldom used in clinical practice due to administrative constraints or to inadequate validity, reliability and responsiveness. In clinical trials, more sensitive and reliable measurement scales could unmask changes in physiological variables that would not be visible with existing clinical scores.In the last decades robotic devices have become available for neurorehabilitation training in clinical centers. Besides training, robotic devices can overcome some of the limitations in traditional clinical assessments by providing more objective, sensitive, reliable and time-efficient measurements. However, it is necessary to understand the clinical needs to be able to develop novel robot-aided assessment methods that can be integrated in clinical practice.This paper aims at providing researchers and developers in the field of robotic neurorehabilitation with a comprehensive review of assessment methods for the lower extremities. Among the ICF domains, we included those related to lower extremities sensorimotor functions and walking; for each chapter we present and discuss existing assessments used in routine clinical practice and contrast those to state-of-the-art instrumented and robot-aided technologies. Based on the shortcomings of current assessments, on the identified clinical needs and on the opportunities offered by robotic devices, we propose future directions for research in rehabilitation robotics. The review and recommendations provided in this paper aim to guide the design of the next generation of robot-aided functional assessments, their validation and their translation to clinical practice.

Estimating the patient's contribution during robot-assisted therapy

Robot-assisted therapy has become increasingly common in neurorehabilitation. Sophisticated controllers have been developed for robots to assist and cooperate with the patient. It is difficult for the patient to judge to what extent the robot contributes to the execution of a movement. Therefore, methods to comprehensively quantify the patients contribution and provide feedback are of key importance. We developed a method comprehensively to estimate the patients contribution by combining kinematic measures and the motor assistance applied. Inverse dynamic models of the robot and the passive human arm calculate the required torques to move the robot and the arm and build, together with the recorded motor torque, a metric (in percentage) that represents the patients contribution to the movement. To evaluate the developed metric, 12 nondisabled subjects and 7 patients with neurological problems simulated instructed movement contributions. The results are compared with a common performance metric. The estimation shows very satisfying results for both groups, even though the arm model used was strongly simplified. Displaying this metric to patients during therapy can potentially motivate them to actively participate in the training.

ChARMin: The First Actuated Exoskeleton Robot for Pediatric Arm Rehabilitation

ChARMin is the first actuated exoskeleton robot for pediatric arm rehabilitation. The device was specifically designed to provide intensive rehabilitative training for children with affected arm motor function, e.g., due to cerebral palsy; therewith complementing conventional therapies. This paper gives a comprehensive overview of the ChARMin robot, which provides six actuated degrees of freedom, and is designed to cover the complete target group of children and adolescents aged 5-18 years. Moreover, the new audiovisual game-like interface is presented, which motivates active participation of the child. To support the childs arm movements with the exoskeleton, a patient-cooperative control strategy was implemented. The controller enables free arm movements, assistance-as-needed, and complete guidance of the arm. Five children aged 5-17 years with impaired arm motor function due to cerebral palsy, stroke, and traumatic brain injury tested the various training scenarios with different amounts of support, and robot settings depending on the therapeutic goals and the childrens movement capabilities and preferences. These preliminary tests suggest that the ChARMin setup can be used as an advanced exercise tool for arm neurorehabilitation that optimally challenges children and adolescents with severely to moderately affected arm motor functions.

Online adaptive compensation of the ARMin Rehabilitation Robot

Robot-assisted arm therapy is increasingly applied in neurorehabilitation. The reason for this development over the last decades was that robots relieve the therapist from hard physical work while the training intensity can be increased. Importantly, an increase in training intensity is closely linked to functional improvements of the patient. However, usability of the robot for therapists was hardly considered an important factor in rehabilitation robot development so far. We believe that usability of the robot is a key factor for acceptance of the device by therapists. In this paper, an online adaptive compensation for the ARMin rehabilitation robot is presented, which aims at improving usability of the robot. Therefore, we expect ARMin therapy to become even more effective than conventional therapy at a level that is also relevant for the patient. Additionally, improved usability relieves the therapist from unnecessary/time-consuming tasks linked to robot handling. For the ARMin, the new online adaptive compensation takes over automatic updates of changed upper and lower arm lengths as well as adaptation of shoulder angle settings to fit the patients anthropometry. Simultaneously, the model-based compensation in ARMin is directly updated to account for hardware changes. Importantly, the online adaptive compensation provides improved performance of ARMin even at the borders of the workspace. In experiments, we could show that the adaptive online compensation relieves the force and position controller from additional burdens and increases the robot performance drastically especially at the workspace border.