Plasma Polishing as a New Polishing Option to Reduce the Surface Roughness of Porous Titanium Alloy for 3D Printing.

Porous titanium alloy implants with simulated trabecular bone fabricated by 3D printing technology have broad prospects. However, due to the fact that some powder adheres to the surface of the workpiece during the manufacturing process, the surface roughness in direct printing pieces is relatively high. At the same time, since the internal pores of the porous structure cannot be polished by conventional mechanical polishing, an alternative method needs to be found. As a surface technology, plasma polishing technology is especially suitable for parts with complex shapes that are difficult to polish mechanically. It can effectively remove particles and fine splash residues attached to the surface of 3D printed porous titanium alloy workpieces. Therefore, it can reduce surface roughness. Firstly, titanium alloy powder is used to print the porous structure of the simulated trabecular bone with a metal 3D printer. After printing, heat treatment, removal of the supporting structure, and ultrasonic cleaning is carried out. Then, plasma polishing is performed, consisting of adding a polishing electrolyte with the pH set to 5.7, preheating the machine to 101.6 °C, fixing the workpiece on the polishing fixture, and setting the voltage (313 V), current (59 A), and polishing time (3 min). After polishing, the surface of the porous titanium alloy workpiece is analyzed by a confocal microscope, and the surface roughness is measured. Scanning electron microscopy is used to characterize the surface condition of porous titanium. The results show that the surface roughness of the whole porous titanium alloy workpiece changed from Ra (average roughness) = 126.9 µm to Ra = 56.28 µm, and the surface roughness of the trabecular structure changed from Ra = 42.61 µm to Ra = 26.25 µm. Meanwhile, semi-molten powders and ablative oxide layers are removed, and surface quality is improved.

Adaptive Gravity Compensation Framework Based on Human Upper Limb Model for Assistive Robotic Arm Extender.

The Assistive Robotic Arm Extender (ARAE) is an upper limb assistive and rehabilitation robot that belongs to the end-effector type, enabling it to assist patients with upper limb movement disorders in three-dimensional space. However, the problem of gravity compensation for the human upper limb with this type of robot is crucial, which directly affects the deployment of the robot in the assistive or rehabilitation field. This paper presents an adaptive gravity compensation framework that calculates the compensated force based on the estimated human posture in 3D space. First, we estimated the human arm joint angles in real-time without any wearable sensors, such as inertial measurement unit (IMU) or magnetic sensors, only through the kinematic data of the robot and established human model. The performance of the estimation method was evaluated through a motion capture system, which validated the accuracy of joint angle estimation. Second, the estimated human joint angles were input to the rigid link model to demonstrate the support force profile generated by the robot. The force profile showed that the support force provided by the developed ARAE robot could adaptively change with human arm postures in 3D space. The adaptive gravity compensation framework can improve the usability and feasibility of the 3D end-effector rehabilitation or assistive robot.

Injectable composite hydrogels encapsulating gelatin methacryloyl/chitosan microspheres as ARPE-19 cell transplantation carriers.

Retinal pigment epithelial (RPE) cell transplantation is being explored as a feasible approach for treating age-related macular degeneration. The low aggregation ability of RPE cell suspensions or microtissues after transplantation has limited cell utilisation. Therefore, alternative transplantation strategies should be explored to induce cell aggregation and maintain cell viability. Herein, we propose a composite hydrogel that encapsulates gelatin methacryloyl (GelMA)/chitosan microspheres (GCMSs) as ARPE-19 cell transplantation carriers. The diameter of the GCMS was adjusted by tuning the parameters of the microfluidic devices, yielding a cell-adhering platform that induced uniform cell spreading. The live/dead assay and immunofluorescence results showed that ARPE-19 cells adhered and spread uniformly around the microspheres. Moreover, the hydrogel sheets were used to provide an aggregated protective shell, and the ARPE-19 cells on the microspheres encapsulated within these hydrogel sheets remained viable post-injection and produced fewer reactive oxygen species after cyclic stretching. Furthermore, we found that the composite hydrogel was biodegradable and biocompatible in vivo. Therefore, GCMSs provide an injectable microcarrier for ARPE-19 cells, and the hydrogel provides an aggregated protective shell in this novel platform, which has considerable potential for an alternative injectable and highly aggregated RPE cell transplantation strategy design.

A Greedy Assist-as-Needed Controller for Upper Limb Rehabilitation.

Previous studies on robotic rehabilitation have shown that subjects' active participation and effort involved in rehabilitation training can promote the performance of therapies. In order to improve the voluntary effort of participants during the rehabilitation training, assist-as-needed (AAN) control strategies regulating the robotic assistance according to subjects' performance and conditions have been developed. Unfortunately, the heterogeneity of patients' motor function capability in task space is not taken into account during the implementation of these controllers. In this paper, a new scheme called greedy AAN (GAAN) controller is designed for the upper limb rehabilitation training of neurologically impaired subjects. The proposed GAAN control paradigm includes a baseline controller and a Gaussian RBF network that is utilized to model the functional capability of subjects and to provide corresponding a task challenge for them. In order to avoid subjects' slacking and encourage their active engagement, the weight vectors of RBF networks evaluating subjects' impairment level are updated based on a greedy strategy that makes the networks progressively learn the maximum forces over time provided by subjects. Simultaneously, a challenge level modification algorithm is employed to adjust the task challenge according to the task performance of subjects. Experiments on 12 subjects with neurological impairment are conducted to validate the performance and feasibility of the GAAN controller. The results show that the proposed GAAN controller has significant potential to promote the subjects' voluntary engagement during training exercises.

Kinematic Redundancy Analysis during Goal-Directed Motion for Trajectory Planning of an Upper-Limb Exoskeleton Robot.

The kinematic redundancy of human arm imposes challenges on joint space trajectory planning for upper-limb rehabilitation robot. This paper aims to investigate normal motion patterns in reaching and reach-to-grasp movements, and obtain the unique solution in joint space for a five-DOF exoskeleton. Firstly, a six-camera optical motion tracking system was used to capture participants' arm motion during goal-directed reaching or reach-to-grasp movements. Secondly, statistical analysis was executed to explore the characteristics of swivel angle, which revealed that the swivel angle can be approximated to the mean value (155° ± 5°) in resolving the arm redundancy problem. Thirdly, combined with the minimum-jerk trajectory of end-effector, the generated joint trajectory complied well with the joint trajectory captured in healthy humans. Consequently, the obtained results facilitate a new way for three-dimensional trajectory planning of the exoskeleton robot. Further, adaptive assist-as-needed control of the exoskeleton robot can be implemented based on the optimal reference trajectory, with aims to provide assistance according to the patient's performance, and in turn promote neural plasticity.