The individual difference of motor imagery ability evoked by visual stimulus and its personality manifestation.

Motor imagery has been commonly studied as a means of motor rehabilitation but, the individual differences limit its practical application. Visually evoked motor imagery has been widely highlighted by researchers because of its vivid stimulus. However, this modality is still not applicable to all persons.

Technologies evolution in robot-assisted fracture reduction systems: a comprehensive review.

Robot-assisted fracture reduction systems can potentially reduce the risk of infection and improve outcomes, leading to significant health and economic benefits. However, these systems are still in the laboratory stage and not yet ready for commercialization due to unresolved difficulties. While previous reviews have focused on individual technologies, system composition, and surgical stages, a comprehensive review is necessary to assist future scholars in selecting appropriate research directions for clinical use.

An Integrated Method of Biomechanics Modeling for Pelvic Bone and Surrounding Soft Tissues.

The pelvis and its surrounding soft tissues create a complicated mechanical environment that greatly affects the success of fixing broken pelvic bones with surgical navigation systems and/or surgical robots. However, the modeling of the pelvic structure with the more complex surrounding soft tissues has not been considered in the current literature. The study developed an integrated finite element model of the pelvis, which includes bone and surrounding soft tissues, and verified it through experiments.

Dual enzyme-like Co-FeSe nanoflowers with GSH degradation capability for NIR II-enhanced catalytic tumor therapy.

Nanozymes mediated catalytic therapy can produce toxic reactive oxygen species (ROS) and destroy the metabolic balance of tumor cells, providing a new direction for cancer treatment. However, the catalytic efficiency of a single nanozyme is limited by the complexity of the tumor microenvironment (hypoxia, GSH overexpression, ). In order to overcome these problems, we designed flower-like Co-doped FeSe (Co-FeSe) nanozymes by a simple wet chemistry method.

An Auxiliary Synthesis Framework for Enhancing EEG-Based Classification With Limited Data.

While deep learning algorithms significantly improves the decoding performance of brain-computer interface (BCI) based on electroencephalogram (EEG) signals, the performance relies on a large number of high-resolution data for training. However, collecting sufficient usable EEG data is difficult due to the heavy burden on the subjects and the high experimental cost. To overcome this data insufficiency, a novel auxiliary synthesis framework is first introduced in this paper, which composes of a pre-trained auxiliary decoding model and a generative model.

An automatic extraction method on medical feature points based on PointNet++ for robot-assisted knee arthroplasty.

Background: Image registration is a crucial technology in robot-assisted knee arthroplasty, which provides real-time patient information by registering the pre-operative image data with data acquired during the operation. The existing registration method requires surgeons to manually pick up medical feature points (i.e.

A Novel Two-Stage Refine Filtering Method for EEG-Based Motor Imagery Classification.

Cerebral stroke is a common disease across the world, and it is a promising method to recognize the intention of stroke patients with the help of brain-computer interface (BCI). In the field of motor imagery (MI) classification, appropriate filtering is vital for feature extracting of electroencephalogram (EEG) signals and consequently influences the accuracy of MI classification. In this case, a novel two-stage refine filtering method was proposed, inspired by Gradient-weighted Class Activation Mapping (Grad-CAM), which uses the gradients of any target concept flowing into the final convolutional layer to highlight the important part of training data for predicting the concept.

Stereotactic technology for 3D bioprinting: from the perspective of robot mechanism.

Three-dimensional (3D) bioprinting has been widely applied in the field of biomedical engineering because of its rapidly individualized fabrication and precisely geometric designability. The emerging demand for bioprinted tissues/organs with bio-inspired anisotropic property is stimulating new bioprinting strategies. Stereotactic bioprinting is regarded as a preferable strategy for this purpose, which can perform bioprinting at the target position from any desired orientation in 3D space.

Correlated Skin Surface and Tumor Motion Modeling for Treatment Planning in Robotic Radiosurgery.

In robotic radiosurgery, motion tracking is crucial for accurate treatment planning of tumor inside the thoracic or abdominal cavity. Currently, motion characterization for respiration tracking mainly focuses on markers that are placed on the surface of human chest. Nevertheless, limited markers are not capable of expressing the comprehensive motion feature of the human chest and abdomen.

A topology optimization method of robot lightweight design based on the finite element model of assembly and its applications.

Topology optimization is a widely used lightweight design method for structural design of the collaborative robot. In this article, a topology optimization method for the robot lightweight design is proposed based on finite element analysis of the assembly so as to get the minimized weight and to avoid the stress analysis distortion phenomenon that compared the conventional topology optimization method by adding equivalent confining forces at the analyzed part's boundary. For this method, the stress and deformation of the robot's parts are calculated based on the finite element analysis of the assembly model.

Detecting self-paced walking intention based on fNIRS technology for the development of BCI.

Since more and more elderly people suffer from lower extremity movement problems, it is of great social significance to assist persons with motor dysfunction to walk independently again and reduce the burden on caregivers. The self-paced walking intention, which could increase the ability of self-control on the start and stop of motion, was studied by applying brain-computer interface (BCI) technology, a novel research field. The cerebral hemoglobin signal, which was obtained from 30 subjects by applying functional near-infrared spectroscopy (fNIRS) technology, was processed to detect self-paced walking intention in this paper.

A Multi-Branch 3D Convolutional Neural Network for EEG-Based Motor Imagery Classification.

One of the challenges in motor imagery (MI) classification tasks is finding an easy-handled electroencephalogram (EEG) representation method which can preserve not only temporal features but also spatial ones. To fully utilize the features on various dimensions of EEG, a novel MI classification framework is first introduced in this paper, including a new 3D representation of EEG, a multi-branch 3D convolutional neural network (3D CNN) and the corresponding classification strategy. The 3D representation is generated by transforming EEG signals into a sequence of 2D array which preserves spatial distribution of sampling electrodes.

Intelligent Control for Human-Robot Cooperation in Orthopedics Surgery.

Cooperation between surgeon and robot is one of the key technologies that limit the robot to be widely used in orthopedic clinics. In this study, the evolution of human-robot cooperation methods and the control strategies for typical human-robot cooperation in robot-assisted orthopedics surgery were reviewed at first. Then an intelligent admittance control method, which combines the fuzzy model reference learning control with the virtual constraint control, is proposed to solve the requirements of intuitive human-robot interaction during orthopedics surgery.

A novel passive/active hybrid robot for orthopaedic trauma surgery.

Background: Image guided navigation systems (IGNS) have been implemented successfully in orthopaedic trauma surgery procedures because of their ability to help surgeons position and orient hand-held drills at optimal entry points. However, current IGNS cannot prevent drilling tools or instruments from slipping or deviating from the planned trajectory during the drilling process. A method is therefore needed to overcome such problems.