In this paper, a robot-assisted therapy system is presented, mainly focused on the improvement of fine movements of patients with motor deficits of upper limbs. This system combines the use of a haptic device with an augmented reality environment, where a kind of occupational therapy exercises are implemented. The main goal of the system is to provide an extra motivation to patients, who are stimulated visually and tactilely into a scene that mixes elements of real and virtual worlds. Additionally, using the norm of tracking error, it is possible to quantitatively measure the performance of the patient during a therapy session, likewise, it is possible to obtain information such as runtime and the followed path.

No abstract

Traditional upper limb rehabilitation exercises are primarily aimed at regaining the strength or range of motion of the patients' injured area. An alternative option that has been presented in the last years is the use of haptic interfaces, which have shown their potential as tools that support rehabilitation therapies. This article presents a haptic system of rehabilitation for fine upper limb movements, whose main characteristic is that users of the system can interact in a visual and tactile fashion with virtual objects mixed with real scenarios, thereby achieving an augmented reality environment. The system was tested in two stages, both with subjects who had a degree of disability in upper limbs. The data collected were followed trajectories, follow-up errors and the muscular activity obtained by means of electromyography; the collected information enabled the analysis, in a quantitative way, of the degree of progress of the patients. In addition, the assessments made by physiotherapists were considered, concluding that the proposed system can be used as a viable complementary tool for conventional rehabilitation therapies.

In general, indirect force control schemes (stiffness, impedance, etc.) assume that robot actuators can provide any torque value to achieve the goal of interaction control. This study attempts to regulate robot–environment interaction by generating bounded control signals and to avoid accurate knowledge of the parameters associated with gravitational effects and the stiffness of the environment. To achieve this aim, a generalized and saturating adaptive stiffness control scheme in task‐space is proposed. For the purpose of this work, the interaction or contact between the end‐effector of a robot manipulator and the environment is modeled as a vector of bounded spring‐like forces. The proposed control approach has a proportional‐derivative structure with static model‐based compensation of gravitational and interaction forces, which it achieves by including a regressor‐based adaptive term. As a theoretical basis to support the proposal, Lyapunov's stability analysis of the closed‐loop equilibrium vector is presented. Finally, the suitability of the proposed stiffness control scheme for interaction tasks is verified through simulations and experimental tests by using three‐degree‐of‐freedom robotic arms.

No abstract