Elena Vergaro

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

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

Bilateral robot therapy based on haptics and reinforcement learning: Feasibility study of a new concept for treatment of patients after stroke.

OBJECTIVE To carry out a preliminary feasibility study of a new concept of robot therapy for severely impaired patients after stroke. DESIGN A haptic manipulandum connected to a bar that can rotate freely while providing a measure of the rotation angle. The controller combines a bilateral reaching task with the task of balancing the action of the 2 arms. Reinforcement is given to the subject in 2 forms: audio-visual and haptic by means of adaptable force fields. PATIENTS Four highly paretic patients with chronic stroke (Fugl-Meyer score less than 15). METHODS The training cycle consisted of 5 sessions over a period of 2 weeks. Each session (45 min) was divided in blocks of 10 pairs of forward/backward movements. Performance was determined by evaluating the number of successful movements per session, the session-by-session decrease in the assistive field, the mean reaching time, and the mean stopping field. RESULTS All subjects could understand the task, appreciated it and improved their performance during training. The reaching movements became smoother and quicker; balance errors and the magnitude of the resisting field were consistently reduced. CONCLUSION Bilateral robot therapy is a promising technique, provided that it self-adapts to the patients performance. Formal clinical trials should address this point.

Force-Field Compensation in a Manual Tracking Task

This study addresses force/movement control in a dynamic “hybrid” task: the master sub-task is continuous manual tracking of a target moving along an eight-shaped Lissajous figure, with the tracking error as the primary performance index; the slave sub-task is compensation of a disturbing curl viscous field, compatibly with the primary performance index. The two sub-tasks are correlated because the lateral force the subject must exert on the eight-shape must be proportional to the longitudinal movement speed in order to perform a good tracking. The results confirm that visuo-manual tracking is characterized by an intermittent control mechanism, in agreement with previous work; the novel finding is that the overall control patterns are not altered by the presence of a large deviating force field, if compared with the undisturbed condition. It is also found that the control of interaction-forces is achieved by a combination of arm stiffness properties and direct force control, as suggested by the systematic lateral deviation of the trajectories from the nominal path and the comparison between perturbed trials and catch trials. The coordination of the two sub-tasks is quickly learnt after the activation of the deviating force field and is achieved by a combination of force and the stiffness components (about 80% vs. 20%), which is a function of the implicit accuracy of the tracking task.

Desirable features of a “humanoid” robot-therapist

In relation with a recent Cochrane review, the paper discusses desirable features of a “humanoid” robot-therapist: 1) high mechanical compliance, 2) large range of force, 3) minimum assistance level, 4) soft haptic interaction for proprioceptive awareness, 5) adaptative assistance properties. It also proposes a framework for addressing optimal assistance and learning paradigms in view of a consensus in the community of rehabilitation engineers about shared principles and common standards.

Robot therapy: the importance of haptic interaction

This paper proposes some general principles for designing robot therapy protocols that best fit the need of integrating robot therapy with physical therapy, in order to assure patients with the best chance of a carryover from performance improvements, evaluated in the framework of rehabilitation exercises, to improvements in daily life activities. In particular, we emphasize the importance of using really haptic robots that can emulate the soft interaction between patient and human therapist, thus providing a haptic virtual environment. From this we derive the concept of minimally assistive strategy for hemiparetic patients and we show its application in some experimental protocols. On the same line of reasoning we propose an adaptive training strategy for ataxic patients that again requires the soft interaction of haptic robots.

Training stroke patients with continuous tracking movements: Evaluating the improvement of voluntary control

We report on a pilot study of robot therapy with stroke patients. Patients were requested to track a continuously moving target according to a figure-of-eight. Assistance was provided by an attractive force field, whose magnitude was regulated according to a principle of minimal assistance and a principle of consolidation of the learned memory trace. From the analysis of the assistive forces, we show that subjects improve their degree of voluntary control.

Visuo-manual tracking in a robot-generated dynamic environment

This study investigates a dual task: 1) visuo-manual tracking of a target moving on an eight-shaped trajectory and 2) compensation of a robot-generated, motion-dependent force field. The target speed is dependent on the tracking error, in such a way that the task difficulty increases as tracking performance improves. The results show that although non trivial this dual-task protocol can be learned in a coordinated way, preserving features of intermittent control, also present when the dynamic component of the protocol is absent. The potential usefulness of this dual task in the rehabilitation of neurological patients is also discussed.