In recent years, the rapid advancement of digital technologies has driven a profound transformation in both individual lives and business operations. The integration of Industry 4.0 with advanced mechatronic systems is at the forefront of this digital transformation, reshaping the landscape of smart manufacturing. This article explores the convergence of digital technologies and physical systems, with a focus on the critical role of mechatronics in enabling this transformation. Using technologies such as advanced robotics, the Internet of Things (IoT), artificial intelligence (AI), and big data analytics, industries are developing intelligent and interconnected systems capable of real-time data exchange, distributed decision making, and automation. The paper further explores two case studies: one on a smart plastic injection moulding machine and another on soft robots. These examples illustrate the synergies, benefits, challenges, and future potential of integrating mechatronics with Industry 4.0 technologies. Ultimately, this convergence fosters the development of smart factories and products, enhancing manufacturing efficiency, adaptability, and productivity, while also contributing to sustainability by reducing waste, optimising resource usage, and lowering the environmental impact of industrial production. This marks a significant shift in industrial production towards more sustainable practices.

This paper presents the design, control, and experimental evaluation of a needle-guiding robot intended for use in laser ablation (LA) of liver tumors under guidance by magnetic resonance imaging (MRI). The robot provides alignment of a needle guide inside the MRI scanner bore and employs manual needle insertion. In order to minimize MR-image deterioration, the robot is actuated using plastic pneumatic cylinders and long pipes connecting to control valves located outside the MRI scanner room. A new time-delay control scheme was employed to achieve high position accuracy without requiring pressure or force measurements in the MRI scanner. The control scheme was compared with experiments to a previously developed sliding mode controller. A marker localization method based on the convolution theorem of Fourier transform was employed to register the robot in the MRI scanner coordinate system and to verify the position of the needle guide before the manual needle insertion. Experiments in a closed-bore MRI scanner showed a variation in SNR below 5%. A phantom study indicates that the targeting error in robot-assisted needle insertions is below 5 mm and suggest a potential time saving of 30 min compared to the manual MRI-guided LA procedure.

Background and Purpose: Stroke, predominantly a condition of older age, is a major cause of acquired disability in the global population and puts an increasing burden on health care resources. Clear evidence for the importance of intensity of therapy in optimizing functional outcomes is found in animal models, supported by neuroimaging and behavioral research, and strengthened by recent meta-analyses from multiple clinical trials. However, providing intensive therapy using conventional treatment paradigms is expensive and sometimes not feasible because of social and environmental factors. This article addresses the need for cost-effective increased intensity of practice and suggests potential benefits of telehealth (TH) as an innovative model of care in physical therapy. Summary of Key Points: We provide an overview of TH and present evidence that a web-supported program, used in conjunction with constraint-induced therapy (CIT), can increase intensity and adherence to a rehabilitation regimen. The design and feasibility testing of this web-based program, “LifeCIT,” is presented. We describe how wearable sensors can monitor activity and provide feedback to patients and therapists. The methodology for the development of a wearable device with embedded inertial and mechanomyographic sensors, algorithms to classify functional movement, and a graphical user interface to present meaningful data to patients to support a home exercise program is explained. Recommendations for Clinical Practice: We propose that wearable sensor technologies and TH programs have the potential to provide most-effective, intensive, home-based stroke rehabilitation.

Soft continuum manipulators offer levels of compliance and inherent safety that can render them a superior alternative to conventional rigid robots for a variety of tasks, such as medical interventions or human–robot interaction. However, the ability of soft continuum manipulators to compensate for external disturbances needs to be further enhanced to meet the stringent requirements of many practical applications. In this paper, we investigate the control problem for soft continuum manipulators that consist of one inextensible segment of constant section, which bends under the effect of the internal pressure and is subject to unknown disturbances acting in the plane of bending. A rigid-link model of the manipulator with a single input pressure is employed for control purposes and an energy-shaping approach is proposed to derive the control law. A method for the adaptive estimation of disturbances is detailed and a disturbance compensation strategy is proposed. Finally, the effectiveness of the controller is demonstrated with simulations and with experiments on an inextensible soft continuum manipulator that employs pneumatic actuation.

Loss of mobility and/or balance resulting from neural trauma is a critical public health issue. Robotic exoskeletons hold great potential for rehabilitation and assisted movement. However, the synergy of robot operation with human effort remains a problem. In particular, optimal assist-as-needed (AAN) control remains unresolved given pathological variance among patients. We introduce a model predictive control (MPC) architecture for lower limb exoskeletons that achieves on-the-fly transitions between modes of assistance. The architecture implements a fuzzy logic algorithm (FLA) to map key modes of assistance based on human involvement. Three modes are utilised: passive, for human relaxed and robot dominant; active-assist, for human cooperation with the task; and safety, in the case of human resistance to the robot. Electromyography (EMG) signals are further employed to predict the human torque. EMG output is used by the MPC for trajectory following and by the FLA for decision making. Experimental validation using a 1-DOF knee exoskeleton demonstrates the controller tracking a sinusoidal trajectory with relaxed, assistive, and resistive operational modes. Results demonstrate rapid and appropriate transfers among the assistance modes, and satisfactory AAN performance in each case, offering a new level of human-robot synergy for mobility assist and rehabilitation.

This paper investigates the model-based nonlinear control of a class of soft continuum pneumatic manipulators that bend due to pressurization of their internal chambers and that operate in the presence of disturbances. A port-Hamiltonian formulation is employed to describe the closed loop system dynamics, which includes the pressure dynamics of the pneumatic actuation, and new nonlinear control laws are constructed with an energy-based approach. In particular, a multi-step design procedure is outlined for soft continuum manipulators operating on a plane and in 3D space. The resulting nonlinear control laws are combined with adaptive observers to compensate the effect of unknown disturbances and model uncertainties. Stability conditions are investigated with a Lyapunov approach, and the effect of the tuning parameters is discussed. For comparison purposes, a different control law constructed with a backstepping procedure is also presented. The effectiveness of the control strategy is demonstrated with simulations and with experiments on a prototype. To this end, a needle valve operated by a servo motor is employed instead of more sophisticated digital pressure regulators. The proposed controllers effectively regulate the tip rotation of the prototype, while preventing vibrations and compensating the effects of disturbances, and demonstrate improved performance compared to the backstepping alternative and to a PID algorithm.