Three‐dimensional printing (3DP) has recently gained importance in the medical industry, especially in surgical specialties. It uses different techniques and materials based on patients’ needs, which allows bioprofessionals to design and develop unique pieces using medical imaging provided by computed tomography (CT) and magnetic resonance imaging (MRI). Therefore, the Department of Biology and Medicine and the Department of Physics and Engineering, at the Bioastronautics and Space Mechatronics Research Group, have managed and supervised an international cooperation study, in order to present a general review of the innovative surgical applications, focused on anatomical systems, such as the nervous and craniofacial system, cardiovascular system, digestive system, genitourinary system, and musculoskeletal system. Finally, the integration with augmented, mixed, virtual reality is analyzed to show the advantages of personalized treatments, taking into account the improvements for preoperative, intraoperative planning, and medical training. Also, this article explores the creation of devices and tools for space surgery to get better outcomes under changing gravity conditions.

Current powered prosthetic and orthotic devices are mostly based on rigid actuators, which exhibit some intrinsic limitations, such as the reduced number of degrees of freedom, high weight, and limited flexibility. As progress is made in the soft robotics field, artificial muscles arise as potential candidates to replace current rigid actuator technologies. Dielectric elastomer actuators (DEAs) are a very promising class of soft actuator and are attracting attention due to their high energy density, fast response, and high actuation strains, similar or even superior to natural muscles. Such remarkable properties can lead the DEAs to be the next generation of actuators for wearable robots, and overcome the limitations imposed by the rigid actuators currently used. This paper reviews the state of art of the applications of DEAs to prostheses, orthoses, and rehabilitation devices. We analyzed the main configurations that are suitable as artificial muscles for the above-mentioned applications and presented the basic model of a dielectric elastomer transducer. When compared to the properties of natural skeletal muscle, some of these configurations stand out. However, there are still some drawbacks that prevent the large-scale application of DEAs, for instance the high operating voltages, durability issues, and nonlinearities that make them difficult to control. We investigated recent advances in materials, control strategies and fabrication methods that tackle these drawbacks, and they indicate that dielectric elastomers are great candidates to be the next generation of actuators for bionic devices.

Lower-limb gait training exoskeletons are extraordinary tools used to reduce the burden of locomotor impairments in patients with neurological diseases. However, the transparent operation and backdrivability of such systems still needs to be improved. Moreover, it is not completely understood how the mechanical design of the robot can interfere with the user's gait pattern. Aiming to address these shortcomings, we investigate the required driving torques and mechanical power to move the legs under a wide range of actuator's mass, inertia and friction and thigh/shank lengths. We used the ExoRoboWalker, a six-degree-of-freedom lower-limb exoskeleton, to build a framework model based on the double-pendulum approach integrated with the actuators' mechanical impedance. Decoupled joint apparent inertia and the Rayleigh's dissipation function were introduced to the robot's Lagrangian to consider the effects of gearhead ratio and joint friction in the model. Firstly, it is presented the isolated effect of such variables on the required driving torques of the system. The oscillation frequency for the minimum joint torque was severely affected by variations of inertia, friction, and links length. Secondly, the combined effect of the actuator's mass, inertia and friction reveled that a heavier exoskeleton with low-ratio transmission required less torque and mechanical power than a lighter one with greater reduction ratio depending on the oscillation frequency, which is remarkable. These findings have important implications for new designs of lower-limb gait training systems.

Motor Imagery (MI)-Brain Computer-Interfaces (BCI) illiteracy defines that not all subjects can achieve a good performance in MI-BCI systems due to different factors related to the fatigue, substance consumption, concentration, and experience in the use. To reduce the effects of lack of experience in the use of BCI systems (naïve users), this paper presents the implementation of three Deep Learning (DL) methods with the hypothesis that the performance of BCI systems could be improved compared with baseline methods in the evaluation of naïve BCI users. The methods proposed here are based on Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM)/Bidirectional Long Short-Term Memory (BiLSTM), and a combination of CNN and LSTM used for upper limb MI signal discrimination on a dataset of 25 naïve BCI users. The results were compared with three widely used baseline methods based on the Common Spatial Pattern (CSP), Filter Bank Common Spatial Pattern (FBCSP), and Filter Bank Common Spatial-Spectral Pattern (FBCSSP), in different temporal window configurations. As results, the LSTM-BiLSTM-based approach presented the best performance, according to the evaluation metrics of Accuracy, F-score, Recall, Specificity, Precision, and ITR, with a mean performance of 80% (maximum 95%) and ITR of 10 bits/min using a temporal window of 1.5 s. The DL Methods represent a significant increase of 32% compared with the baseline methods (p < 0.05). Thus, with the outcomes of this study, it is expected to increase the controllability, usability, and reliability of the use of robotic devices in naïve BCI users.

Flexible and rigid long chain polymers in very dilute solutions can significantly reduce the drag in turbulent flows. The polymers successively stretch and coil by interacting with the turbulent structures, which changes the turbulent flow and further imposes a transient behavior on the drag reduction (DR) as well as a subsequent mechanical polymer degradation. This time-dependent phenomenon is strongly affected by a number of parameters, which are analyzed here, such as the Reynolds number, polymer concentration, polymer molecular weight, and salt concentration. This last parameter can dramatically modify the polymeric structure. The investigation of the salt concentration's impact on the DR is mostly motivated by some potential applications of this technique to ocean transport and saline fluid flows. In the present paper, a cylindrical double gap rheometer device is used to study the effects of salt concentration on DR over time. The reduction of drag is induced by three polymers: poly (ethylene oxide) (PEO), polyacrylamide (PAM), and xanthan gum (XG). These polymers are dissolved in deionized water both in the presence of salt and in its absence. The DR is displayed from the very start of the test to the time when the DR achieves its final level of efficiency, following the mechanical degradations. The presence of salt in PEO and XG solutions reduces the maximum DR, DR_max, as well as the time to achieve it. In contrast, the DR does not significantly change over the time for PAM solutions upon the addition of salt.

Lower limb exoskeletons (LLE) have been successfully used in robotic-assisted rehabilitation to reduce the burden of locomotor impairment of disabled people. However, the design limitations of LLE mechanisms, such as the lack of kinematic compatibility relative to the user’s joints and the use of high stiff or heavy actuators, limit the outcomes of treatment and increase the risk of injury. To address these shortcomings, in this work we present the design of the MRKneeExo, a highly backdrivable and kinematically compatible active knee exoskeleton. The powertrain of the system is composed of a BLDC 70 W motor associated with a harmonic drive gearbox and a customized magneto-rheological (MR) clutch. To improve kinematic compatibility with the user’s knee, a crossed four-bar linkage mechanism (FBLM) was optimally designed to follow the trajectory of the instant center of rotation (ICR) of the knee projected in the parasagittal plane where the joint is placed. The MR clutch is used to decouple the motor-reducer from the FBLM, thus enabling high backdrivability. The results showed a small error (<3 mm) between the FBLM and the knee ICR. Furthermore, the MR clutch allowed for low back-drive torque (1.28 N m) compared to the torque to back-drive the motor-reducer (18.51 N m). This paper is presented in a framework that can be generalized to support the design of other knee exoskeletons.