Marco Guidali

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.

ARMin III --arm therapy exoskeleton with an ergonomic shoulder actuation

Rehabilitation robots have become important tools in stroke rehabilitation. Compared to manual arm training, robot-supported training can be more intensive, of longer duration and more repetitive. Therefore, robots 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 towards exoskeleton robots is taking place because they offer a better guidance of the human arm, especially for movements with a large range of motion. However, the implementation of an exoskeleton device introduces the challenge of reproducing the motion of the human shoulder, which is one of the most complex joints of the body. Thus, this paper starts with describing a simplified model of the human shoulder. On the basis of that model, a new ergonomic shoulder actuation principle that provides motion of the humerus head is proposed, and its implementation in the ARMin III arm therapy robot is described. The focus lies on the mechanics and actuation principle. The ARMin III robot provides three actuated degrees of freedom for the shoulder and one for the elbow joint. An additional module provides actuated lower arm pro/supination and wrist flexion/extension. Five ARMin III devices have been manufactured and they are currently undergoing clinical evaluation in hospitals in Switzerland and in the United States.

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.

Online learning and adaptation of patient support during ADL training

Neurological patients with impaired upper limbs often receive arm therapy to restore or relearn lost motor functions. During the last years robotic devices were developed to assist the patient during the training. In daily life the diversity of movements is large because the human arm has many degrees of freedom and is used as a manipulandum to interact with the environment. To support a patient during the training the amount of support should be adapted in an assist-as-needed manner. We propose a method to learn the arm support needed during the training of activities of daily living (ADL) with an arm rehabilitation robot. The model learns the performance of the patient and creates an impairment space with a radial basis function network that can be used to assist the patient together with a patient-cooperative control strategy. Together with the arm robot ARMin the learning algorithm was evaluated. The results showed that the proposed model is able to learn the required arm support for different movements during ADL training.

Assessment and training of synergies with an arm rehabilitation robot

Patients with moderate to severe hemiparesis following stroke often show abnormal muscle coactivation and a loss of interjoint coordination in the hemiparetic limb. These abnormal stereotypic movement patterns are known in clinical rehabilitation as abnormal secondary torques or synergies. In the beginning of a rehabilitation process the patients often train inside those synergistic patterns, what helps to restore some functionality, but makes it more difficult to break out of them later. Preliminary tests in our lab showed, that there is no precise test to characterize short term alteration in abnormal coupling between different joints. Therefore, a new assessment tool has been developed and implemented on the arm rehabilitation robot ARMin. A special synergy training program has been assembled and evaluated with one patient. The new assessment method showed to be appropriate for a qualitative measurement of abnormal couplings. After training, the patients dominant synergy pattern were reduced.

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.

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.

Patient-Cooperative Control: Providing Safe Support without Restricting Movement

Patient-cooperative behavior of a rehabilitation robot can be seen as a tight interplay of three control components: The first and most important is the intervention paradigm, which can for example be assistance, resistance, or error augmentation. The second and third are more related to the underlying properties of the robot: On the one hand the robot should be transparent in “free” movements, and on the other hand it should provide a safe training frame with appropriate virtual constraints for the movement. In this paper, control strategies to enhance transparency and to constrain movement with virtual tunnels are presented using the examples of the ARMin and the Lokomat, which are rehabilitation robots for upper and lower extremities, respectively. Differences and similarities in control of these robots are outlined in terms of the control strategies for transparency enhancement and movement constraints. The control concepts Generalized Elasticities and Path Control are described, which improve transparency in free movements inside an allowed spatial region, and which impose movement constraints to confine the user to this allowed region. Generalized Elastic Path Control unifies both control approaches within a single potential field, and preliminary results of this controller on the Lokomat are shown.

Using a Robotic Gait Orthosis as Haptic Display - A Perception-Based Optimization Approach

The actuated gait orthosis Lokomat has been developed at University Hospital Balgrist for patients with impairments due to neurological or orthopedic lesions. To enhance rehabilitation with the Lokomat, patient-cooperative techniques have been developed. Patient-cooperative means that the technical system considers the patient intention and efforts rather than imposing any predefined movement or inflexible strategy. It is hypothesized that patient-cooperative techniques have the potential to improve the therapeutic outcome compared to classical rehabilitation strategies. One example for patient-cooperative techniques are immersive, multi-modal scenarios. They can provide task-specific feedback and are expected to increase patients motivation to contribute. One interaction possibility is haptic feedback which can be provided by the gait orthosis to simulate interaction with solid objects. The work described here investigated the potential of the Lokomat to provide haptic feedback. Frequency response measurements under closed-loop conditions were conducted to determine the force and position bandwidths. The final goal was to develop an approach for haptic rendering and optimize its parameters with experiments. Optimization criteria were object hardness and stability during object contact. Results of the bandwidth measurements show that the angle bandwidth is 3 Hz (excitation angle amplitude: 3deg) and the force bandwidth 8 Hz (excitation force amplitude: 10 N). The implemented haptic approach combines an impulsive force component, a penalty force component, and a component for lateral friction force. Best results were achieved for a combination of sine shape impulse, spring constant K with 2000 N/m, and modified damping coefficient B with 300 Ns/m2.

A system for sensory motor rehabilitation of the upper limb with virtual reality, exoskeleton robot, and real objects

Technology assisted therapy has the potential to transform rehabilitation options available, and to dramatically increase the reach of todays healthcare system. Yet challenges persist in rendering translational application designs that optimize the full potential of technology and create value for the patient and the therapist. In a step towards optimizing value of technologies for practical applications to support very weak patients who might otherwise be unable to participate in traditional therapies, an integrated sensory motor training station was designed and developed. Inspired by recent neuroscientific research findings the goal of the design was to provide concurrent first person perspective immersive action observation of both virtual and real elements for motor and sensory experience; the system incorporates a virtual limb proxy that can be personalized and actuated by the robot and that is accompanied by exercise practice in peripersonal space for a plasticity promoting experience for the hand and arm. The station uses virtual reality and real objects for visual sensory experience, real objects also provide tactile sensory experience, and an exoskeleton upper limb robot provides assistance to patients. For many patients, successful movement and movement intensity required in rehabilitation is not achievable without the robot assistance. The multi-sensory features of the system promote a top-down strategy for training the upper limb (hand and arm) complementing the robot training; the system is ideally targeted for weak patients and those with tactile or proprioception sensory loss and those who are known to benefit from multi-sensory experiences.