Using the Bioelectric Signals to Control of Wearable Orthosis of the Elbow Joint with Bi-Muscular Pneumatic Servo-Drive

Biosignal-integrated robotic systems with emerging trends in visual interfaces: A systematic review

Human-machine interfaces (HMI) are currently a trendy and rapidly expanding area of research. Interestingly, the human user does not readily observe the interface between humans and machines. Instead, interactions between the machine and electrical signals from the user's body are obscured by complex control algorithms. The result is effectively a one-way street, wherein data is only transmitted from human to machine. Thus, a gap remains in the literature: how can information be effectively conveyed to the user to enable mutual understanding between humans and machines? Here, this paper reviews recent advancements in biosignal-integrated wearable robotics, with a particular emphasis on "visualization"-the presentation of relevant data, statistics, and visual feedback to the user. This review article covers various signals of interest, such as electroencephalograms and electromyograms, and explores novel sensor architectures and key materials. Recent developments in wearable robotics are examined from control and mechanical design perspectives. Additionally, we discuss current visualization methods and outline the field's future direction. While much of the HMI field focuses on biomedical and healthcare applications, such as rehabilitation of spinal cord injury and stroke patients, this paper also covers less common applications in manufacturing, defense, and other domains.

Mechatronic Design of a Prototype Orthosis to Support Elbow Joint Rehabilitation

Injuries in the elbow area, such as lateral and medial epicondylitis, are the leading causes of consultation with health specialists. Therefore, this research proposes the mechatronic design of an orthosis with a graphic interface that supports professionals in the rehabilitation of the elbow joint through the execution of flexion–extension and pronation–supination movements. For the development of the rehabilitation prototype, mechatronic design, co-design, and IDEF0 methodologies are used, performing activities such as actuator characterization, simulations, and modeling, among others. Through the execution of a case study in a real environment, the device was validated, where the results suggest a functional and workable prototype that supports the treatment of pathologies in the elbow area through the execution of the mentioned movements, supposing that this is a low-cost alternative with elements to improve, such as the industrial design and new functionalities. The developed proposal shows potential as an economical product that health professionals can use. However, some limitations related to the design and functionalities in the application domain were identified.

Integration and Testing of a High-Torque Servo-Driven Joint and Its Electronic Controller with Application in a Prototype Upper Limb Exoskeleton

Mechatronic systems that allow motorized activation in robotic exoskeletons have evolved according to their specific applications and the characteristics of the actuation system, including parameters such as size, mechanical properties, efficiency, and power draw. Additionally, different control strategies and methods could be implemented in various electronic devices to improve the performance and usability of these devices, which is desirable in any application. This paper proposes the integration and testing of a high-torque, servo-driven joint and its electronic controller, exposing its use in a robotic exoskeleton prototype as a case study. Following a brief background review, the development and implementation of the proposal are presented, allowing the control of the servo-driven joint in terms of torque, rotational velocity, and position through a straightforward, closed-loop control architecture. Additionally, the stability and performance of the servo-driven joint were assessed with and without load. In conclusion and based on the obtained results, the servo-driven joint and its control system demonstrate consistent performance under the proposed test protocol (max values: angular velocity 97 °/s, torque 33 Nm, positioning RMSE 1.46°), enabling this approach for use in various applications related to robotic exoskeletons, including human performance enhancement, rehabilitation, or support for daily living activities.

Path Planning and Impedance Control of a Soft Modular Exoskeleton for Coordinated Upper Limb Rehabilitation

The coordinated rehabilitation of the upper limb is important for the recovery of the daily living abilities of stroke patients. However, the guidance of the joint coordination model is generally lacking in the current robot-assisted rehabilitation. Modular robots with soft joints can assist patients to perform coordinated training with safety and compliance. In this study, a novel coordinated path planning and impedance control method is proposed for the modular exoskeleton elbow-wrist rehabilitation robot driven by pneumatic artificial muscles (PAMs). A convolutional neural network-long short-term memory (CNN-LSTM) model is established to describe the coordination relationship of the upper limb joints, so as to generate adaptive trajectories conformed to the coordination laws. Guided by the planned trajectory, an impedance adjustment strategy is proposed to realize active training within a virtual coordinated tunnel to achieve the robot-assisted upper limb coordinated training. The experimental results showed that the CNN-LSTM hybrid neural network can effectively quantify the coordinated relationship between the upper limb joints, and the impedance control method ensures that the robotic assistance path is always in the virtual coordination tunnel, which can improve the movement coordination of the patient and enhance the rehabilitation effectiveness.

Analysis of the Possibilities of Using a Driver’s Brain Activity to Pneumatically Actuate a Secondary Foot Brake Pedal

The study deals with the use of the driver’s brain activity for wireless remote control of the pneumatic actuator exerting pressure on the secondary foot brake pedal. The conducted experimental tests confirm that bioelectrical signals (BES) induced by muscle tension within the head can be used for wireless remote control of a pneumatic actuator to exert a pressure force on a foot brake pedal for disabled drivers during car emergency braking. It has been shown that the BES artefacts generated by muscular tension inside the head (e.g., movement of the face and eyelids, clenching of jaws, and pressing the tongue on the palate) are the easiest to control of the pneumatic systems. The proposed car braking assistance system controlled by the driver’s brain activity can improve the driving safety of disabled people, e.g., by reducing the reaction time of pneumatically assisted emergency braking.