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Upper limb dysfunctions (ULD) are common following a stroke. Annually, more than 15 million people suffer a stroke worldwide. We have developed a 7 degrees of freedom (DoF) exoskeleton robot named the smart robotic exoskeleton (SREx) to provide upper limb rehabilitation therapy. The robot is designed for adults and has an extended range of motion compared to our previously designed ETS-MARSE robot. While providing rehabilitation therapy, the exoskeleton robot is always subject to random disturbance. Moreover, these types of robots manage various patients and different degrees of impairment, which are quite impossible to model and incorporate into the robot dynamics. We hypothesize that a model-independent controller, such as a PID controller, is most suitable for maneuvering a therapeutic exoskeleton robot to provide rehabilitation therapy. This research implemented a model-free proportional–integral–derivative (PID) controller to maneuver a complex 7 DoF anthropomorphic exoskeleton robot (i.e., SREx) to provide a wide variety of upper limb exercises to the different subjects. The robustness and trajectory tracking performance of the PID controller was evaluated with experiments. The results show that a PID controller can effectively control a highly nonlinear and complex exoskeleton-type robot. [ABSTRACT FROM AUTHOR]

SUMMARY: The robotic intervention has great potential in the rehabilitation of post-stroke patients to regain their lost mobility. In this paper, firstly, we present a design of a novel, 7 degree-of-freedom (DOF) upper limb robotic exoskeleton (u-Rob) that features shoulder scapulohumeral rhythm with a wide range of motions (ROM) compared to other existing exoskeletons. An ergonomic shoulder mechanism with two passive DOF was included in the proposed exoskeleton to provide scapulohumeral motion with corresponding full ROM. Also, the joints of u-Rob have more range of motions compared to its existing counterparts. Secondly, we propose a fractional sliding mode control (FSMC) to control u-Rob. Applying the Lyapunov theory to the proposed control algorithm, we showed the stability of it. To control u-Rob, FSMC has shown effectiveness to handle unmodeled dynamics (e.g. friction, disturbance, etc.) in terms of better tracking and chatter compared to traditional SMC. [ABSTRACT FROM AUTHOR]

This paper considers a new fuzzy sliding mode control (NFSMC) of a 7 Degree of Freedoms (7-DoF) upper-limb exoskeleton robot. The proposed exoskeleton robot has a complex structure, an appropriate control method should be chosen for this robotics system. Therefore, a new sliding mode controller (NSMC) is applied for controlling of this robot conveniently. For this task, a novel sliding surface is selected, which is robust against external disturbances and unknown dynamics such as friction forces, different upper-limb's mass, backlash, and input saturation. In order to improve the control method, fuzzy control is applied. Simulation results clearly validates that the proposed control method has some advantages such as high trajectory tracking, robustness, and zero tracking error. [ABSTRACT FROM AUTHOR]

This paper proposes a novel robust control method for the control of a 7-DOF exoskeleton robot. The external disturbances and unknown dynamics in the form of friction forces, different upper-limb’s mass, backlash, and input saturation make robot unstable, which prevents the robot from correctly following the defined path. A new fractional sliding mode controller (NFSMC) is designed, which is robust against unknown dynamic and external disturbances. Fractional PID controller (FPID) has high trajectory tracking, but it is not robust against external disturbances. Therefore, by combining NFSMC and FPID controllers, a new compound fractional PID sliding mode controller (NCFPIDSMC) is proposed, which benefits high trajectory tracking of FPID and robustness of NFSMC. The stability of the proposed control method is verified by Lyapunov theory. A random noise is applied in order to confirm the robustness of the proposed control method. [ABSTRACT FROM AUTHOR]

Exoskeleton robots, which can be worn on human limbs to improve or to rehabilitate their function, are currently of great importance. When these robots are used in rehabilitation, one aspect that must be fulfilled is their capacity to adapt to different patients without significantly varying their performance. This paper describes the application of a relatively new control technique called virtual decomposition control (VDC) to a seven degrees-of-freedom (DOF) exoskeleton robot arm, named ETS-MARSE. The VDC approach mainly involves decomposing complex systems into subsystems, and using the resulting simpler dynamics to conduct control computation, while strictly ensuring global stability and having the subsystem dynamics interactions rigorously managed and maintained by means of virtual power flow. This approach is used to deal with different masses, joint stiffness and biomechanical variations of diverse subjects, allowing the control technique to naturally adapt to the variances involved and to maintain a successful control task. The results obtained in real time on a 7DOF exoskeleton robot arm show the effectiveness of the approach. [ABSTRACT FROM AUTHOR]

World health organization reports, annually more than 15 million people worldwide suffer a stroke and cardiovascular disease, among which 85% of stroke patients incur acute arm impairment, and 40% of victims are chronically impaired or permanently disabled. This results a burden on the families, communities and to the country as well. Rehabilitation programs are the main way to promote functional recovery in these individuals. Since the number of such cases is constantly growing and that the duration of treatment is long, an intelligent robot could significantly contribute to the success of these programs. We therefore developed a new 5DoFs robotic exoskeleton named MARSE-5 (motion assistive robotic-exoskeleton for superior extremity) that supposed to be worn on the lateral side of upper arm to rehabilitate and ease the shoulder, elbow and forearm movements. This paper focused on the design, modeling, development and control of the proposed MARSE-5. To control the exoskeleton, a nonlinear sliding mode control (SMC) technique was employed. In experiments, trajectory tracking that corresponds to typical passive rehabilitation exercises was carried out. Experimental results reveal that the controller is able to maneuver the MARSE-5 efficiently to track the desired trajectories. [ABSTRACT FROM AUTHOR]

Proper functioning of the shoulder, elbow, and wrist movements play a vital role in the performance of essential daily activities. To assist physically disabled people with impaired upper-limb function, we have been developing an exoskeleton robot (ExoRob) to rehabilitate and to ease upper limb motion. The proposed ExoRob will be comprised of seven degrees of freedom (DOFs) to enable natural movements of the human upper-limb. This paper focuses on the kinematic and dynamic modeling of the proposed ExoRob that corresponds to human upper-limbs. For this purpose, a nonlinear computed torque control technique was employed. In simulations, trajectory tracking corresponding to typical rehabilitation exercises were carried out to evaluate the performances of the developed model and controller. For the experimental part, only 3DOFs (elbow, wrist flexion/extension, wrist abduction/adduction) were considered. Simulated and experimental results show that the controller was able to maneuver the proposed ExoRob efficiently in order to track the desired trajectories, which in this case consisted in passive arm movements. Such movements are widely used in therapy and were performed efficiently with the developed ExoRob and the controller. [ABSTRACT FROM AUTHOR]

The design of an upper limb rehabilitation robot for post-stroke patients is considered a benchmark problem regarding improving functionality and ensuring better human–robot interaction (HRI). Existing upper limb robots perform either joint-based exercises (exoskeleton-type functionality) or end-point exercises (end-effector-type functionality). Patients may need both kinds of exercises, depending on the type, level, and degree of impairments. This work focused on designing and developing a seven-degrees-of-freedom (DoFs) upper-limb rehabilitation exoskeleton called 'u-Rob' that functions as both exoskeleton and end-effector types device. Furthermore, HRI can be improved by monitoring the interaction forces between the robot and the wearer. Existing upper limb robots lack the ability to monitor interaction forces during passive rehabilitation exercises; measuring upper arm forces is also absent in the existing devices. This research work aimed to develop an innovative sensorized upper arm cuff to measure the wearer's interaction forces in the upper arm. A PID control technique was implemented for both joint-based and end-point exercises. The experimental results validated both types of functionality of the developed robot. [ABSTRACT FROM AUTHOR]

Rehabilitation robots have become an influential tool in physiotherapy treatment because they are able to provide intensive rehabilitation treatment over a long period of time. However, this technology still suffers from various problems such as dynamic uncertainties, external disturbances, and human-robot interaction. In this paper, we propose a robust adaptive control approach of an exoskeleton robot with an unknown dynamic model and external disturbances. First, the dynamics of the exoskeleton's arm is presented. Then, we design a robust adaptive sliding mode control in which the parameter uncertainties and the disturbances are estimated by the adaptive update methods. The proposed control ensures a good tracking of the system with a finite time convergence of sliding surface to zero. Throughout this paper, the designed control law and the global stability analysis are formulated and demonstrated based on the appropriate choice of the candidate Lyapunov function. The experimental and comparative results, performed for seven degrees-of-freedom (DOFs) exoskeleton arm with three healthy subjects to track a passive rehabilitation motion, confirm the effectiveness and robustness of the proposed control law compared with conventional adaptive approach. [ABSTRACT FROM AUTHOR]

This paper proposes a real-time human inverse kinematics approach based on the Gaussian Process (GP) to address the open problem of finding appropriate inverse kinematic solutions for upper-limb rehabilitation using redundant robotic exoskeletons. The proposed approach is validated using recorded data from a Motion Capture (MoCap) system and is shown to achieve accurate and unique upper-limb natural solutions for different rehabilitation exercises. This approach is a computationally tractable alternative to existing solutions, which are not always feasible and unsuitable for real-time rehabilitation tests, as they are based on optimizing discomfort indices online or computationally demanding learning methods. A comparison with existing inverse kinematics solutions confirms the superior performance of the proposed approach. Additionally, a robust Model Predictive Control (MPC) with an Integral Sliding Mode (ISM) combination is proposed for safe trajectory tracking during rehabilitation exercises. Several real-time experiments were conducted on a 7-DoF exoskeleton robot with and without the presence of a healthy subject to verify the effectiveness of the proposed methods. • Swivel angle estimation based on learning for human inverse kinematic solutions. • Robust model predictive control and integral sliding mode for upper-limb exercises. • Real-time implementation of proposed improvements on a 7 DOF robotic exoskeleton. [ABSTRACT FROM AUTHOR]