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Tremor, a prevalent symptom in Parkinson's patients, is conventionally treated with medications and craniotomy. However, the associated side effects and high surgical costs pose challenges for some individuals. In this study, a lightweight constant current electrical stimulator was developed, which is driven by the FPGA to control the underlying logic and has multiple programmable stimulation parameters. Clinical experiments involving patients with Parkinson's-related resting tremor symptoms were conducted to assess the efficacy of peripheral electrical stimulation. Two Co-contraction Avoidance Stimulation (CAS) strategies targeting nerves and muscles were proposed to reduce tremors. Four Parkinson's disease (PD) patients were recruited to verify the effectiveness of these strategies. Kinematic data recorded by inertial sensors showed that the radial nerve and muscle intervention strategies reduced the average angular velocity amplitude of finger joints during resting tremor by 75.92% and 82.41%, respectively. Notably, under low-frequency pulse stimulation (100 Hz) focused on muscle interference, a low-intensity current of no more than 8 mA maintained a tremor suppression rate of 59.91% even 5 minutes post-stimulation. Based on the experimental results, it is concluded that the constant current electrical stimulator developed in this study can effectively suppress tremor under specific stimulation strategies. These findings have significant implications for the development of lightweight, wearable tremor suppression devices. The stimulator's adaptability, coupled with its precise control parameters, demonstrates promise for advancing non-invasive and cost-effective tremor management in Parkinson's patients.

Background: This study aims to develop a venipuncture robot to replace manual venipuncture to ease the heavy workload, lower the risk of 2019-nCoV infection, and boost venipuncture success rates., Method: The robot is designed with decoupled position and attitude. It consists of a 3-degree-of-freedom positioning manipulator to locate the needle and a 3-degree-of-freedom end-effector that is always vertical to adjust the yaw and pitch angles of the needle. The near-infrared vision and laser sensors obtain the three-dimensional information of puncture positions, while the change in force detects the state feedback of punctures., Results: The experimental results demonstrate that the venipuncture robot has a compact design, flexible motion, high positioning accuracy and repeatability (0.11 and 0.04 mm), and a high success rate when puncturing the phantom., Conclusion: This paper presents a decoupled position and attitude venipuncture robot guided by near-infrared vision and force feedback to replace manual venipuncture. The robot is compact, dexterous, and accurate, which helps to improve the success rate of venipuncture, and it is expected to achieve fully automatic venipuncture in the future., (© 2023 John Wiley & Sons Ltd.)

Venipuncture robots have superior perception and stability to humans and are expected to replace manual venipuncture. However, their use is greatly restricted because they cannot make decisions regarding the puncture sites. Thus, this study presents a multi-information fusion method for determining puncture sites for venipuncture robots to improve their autonomy in the case of limited resources. Here, numerous images have been gathered and processed to establish an image dataset of human forearms for training the U-Net with the soft attention mechanism (SAU-Net) for vein segmentation. Then, the veins are segmented from the images, feature information is extracted based on near-infrared vision, and a multiobjective optimization model for puncture site decision is provided by considering the depth, diameter, curvature, and length of the vein to determine the optimal puncture site. Experiments demonstrate that the method achieves a segmentation accuracy of 91.2% and a vein extraction rate of 86.7% while achieving the Pareto solution set (average time: 1.458 s) and optimal results for each vessel. Finally, a near-infrared camera is applied to the venipuncture robot to segment veins and determine puncture sites in real time, with the results transmitted back to the robot for an attitude adjustment. Consequently, this method can enhance the autonomy of venipuncture robots if implemented dramatically., (© Science China Press and Springer-Verlag GmbH Germany, part of Springer Nature 2022.)

This paper aims to tackle the controller design issue of highly nonlinear and stochastic inflatable robotic arms (IRAs). A novel control scheme, i.e., hybrid adaptive disturbance rejection control (HADRC), is devised to handle the challenging tracking control of hard-to-model IRAs. The model-free adaptive control (MFAC) that linearizes the dynamics by leveraging solely the online input and output (I/O) data of plants is analytically enhanced for superlinear convergence. Both internal and external disturbances are rejected via the active disturbance rejection control (ADRC) that requires little prior model information. The fuzzy logic control (FLC) is subsequently implemented to correlate the two sub-controllers and contribute to attaining smooth motions. The superiority of the proposed scheme is demonstrated by the comparative simulations and experiments on a 2-degree-of-freedom (DOF) IRA., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 ISA. Published by Elsevier Ltd. All rights reserved.)

Automatic venipuncture robots are expected to replace manual venipuncture methods owing to their high control precision, steady operation, and measurable perception. However, the lack of perception of the venipuncture status in the human body leads to an increased risk and failure rate, which further restricts the development of such robots. To address this, we propose a humanoid venipuncture method guided by a biomechanical model to imitate human sensations and feedback. This method intends to perceive the venipuncture status and improve the performance of the venipuncture robot. First, this study establishes a biomechanical venipuncture model, which thoroughly considers the elastic deformation, cutting, and friction of tissues and can be applied to different venipuncture conditions. Then, venipuncture simulations and in vitro phantom experiments are performed under various settings to analyze and validate the model. Finally, to evaluate the robotic humanoid venipuncture method, we apply the method to a self-developed six-degree-of-freedom venipuncture robot via rabbit ear veins with a success rate of approximately 90%. This work demonstrates that the humanoid venipuncture method based on the biomechanical model is practical and rapid in processing simple information in venipuncture robots., Competing Interests: Conflicts of InterestWe declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work. There is no professional or other personal interest of any nature or kind in any product, service, or company that could be construed as influencing the position presented in or the review of the manuscript entitled., (© The Author(s), under exclusive licence to Springer Nature B.V. 2022, Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

Adsorption behavior and dynamics of Arg-Gly-Asp (RGD) tripeptides with different orientations onto the rutile TiO(2) (110) surface in water solution were systematically investigated by molecular dynamics (MD) simulations, using two different water models, TIP3P (transferable intermolecular potential 3P) and SPC/E (extended simple point charge). Possible RGD-TiO(2) binding modes in the form of hydrogen-bonding interactions, involving the amide groups (NH(3)(+) or NH(2)(+), NH(2)) and surface oxygen atoms were identified. The behavior of RGD in contact with the TiO(2) layer was elucidated in detail by the analysis of atom-atom distances, backbone dihedral angles and hydration layers distributed over the interface. The simulation results suggest that, the attachment modes of tripeptides with the same starting arrangement are similar when solvated in TIP3P and SPC/E water, but the conformational stability of the amino sequence is somewhat sensitive to the adopted solvent model. Moreover, the intensity of peptide-surface interaction varies widely depending on the initial arrangement of the RGD sequence.