[Anti-motion Artifact Performance Test System for Ambulatory ECG Monitoring Equipment].

Anti-motion artifact is one of the most important properties of ambulatory ECG monitoring equipment. At present, there is a lack of standardized means to test the performance of anti-motion artifact. ECG simulator and special conductive leather are used to build the simulator, it is used to simulate human skin, to generate ECG signal input for the ECG monitoring equipment attached to it. The mechanical arm and fixed support are used to build a motion simulation system to fix the conductive leather. The mechanical arm is programmed to simulate various motion states of the human body, so that the ECG monitoring equipment can produce corresponding motion artifacts. The collected ECG signals are read wirelessly, observed, analyzed and compared, and the anti-motion artifact performance of ECG monitoring equipment is evaluated. The test results show that by artificially creating the small difference between the two groups of ambulatory ECG monitoring equipment, the system can accurately test the interference signals introduced under the conditions of controlled movement such as tension and torsion, and compare the advantages and disadvantages. The research shows that the test system can provide convenient and accurate verification means for the research of optimizing anti-motion interference.

Fast and precise collision detection for detailed and complex physiological structures.

BACKGROUND AND OBJECTIVES: Virtual reality has been proved indispensable in computer-assisted surgery, especially for surgical planning, and simulation systems. Collision detection is an essential part of surgery simulators and its accuracy and computational efficiency play a decisive role in the fidelity of simulations. Nevertheless, current collision detection methods in surgical simulation and planning struggle to meet precise requirements, especially for detailed and complex physiological structures. To address this, the primary objective of this study was to develop a new algorithm that enables fast and precise collision detection to facilitate the improvement of the realism of virtual reality surgical procedures. METHODS: The method consists of two main parts, bounding spheres formation and two-level collision detection. A specified surface subdivision method is devised to reduce the radius of basic bounding spheres formed by circumcenters of underlying triangles. The spheres are then clustered and adjusted to obtain a compact personalized hierarchy whose position is updated in real time during surgical simulation, followed by two-level collision detection. Triangular facets with collision potential through interaction between hierarchies and then accurate results are obtained by means of precise detection phase. The effectiveness of the algorithm was evaluated in various models and surgical scenarios and was compared with prior relevant implementations. RESULTS: Results on multiple models demonstrated that the method can generate a personalized hierarchy with fewer and smaller bounding spheres for tight wrapping. Simulation experiments proved that the proposed approach is significantly superior to comparable methods under the premise of error-free detection, even for severe model-model collision. CONCLUSIONS: The algorithm proposed through this study enables higher numerical efficiency and detection accuracy, which is capable of significantly enlarging the fidelity/realism of haptic simulators and surgical planning methods.

OL-SLAM: A Robust and Versatile System of Object Localization and SLAM.

This paper proposes a real-time, versatile Simultaneous Localization and Mapping (SLAM) and object localization system, which fuses measurements from LiDAR, camera, Inertial Measurement Unit (IMU), and Global Positioning System (GPS). Our system can locate itself in an unknown environment and build a scene map based on which we can also track and obtain the global location of objects of interest. Precisely, our SLAM subsystem consists of the following four parts: LiDAR-inertial odometry, Visual-inertial odometry, GPS-inertial odometry, and global pose graph optimization. The target-tracking and positioning subsystem is developed based on YOLOv4. Benefiting from the use of GPS sensor in the SLAM system, we can obtain the global positioning information of the target; therefore, it can be highly useful in military operations, rescue and disaster relief, and other scenarios.

Influence of the quality of intraoperative fluoroscopic images on the spatial positioning accuracy of a CAOS system.

BACKGROUND: Spatial positioning accuracy is a key issue in a computer-assisted orthopaedic surgery (CAOS) system. Since intraoperative fluoroscopic images are one of the most important input data to the CAOS system, the quality of these images should have a significant influence on the accuracy of the CAOS system. But the regularities and mechanism of the influence of the quality of intraoperative images on the accuracy of a CAOS system have yet to be studied. METHODS: Two typical spatial positioning methods - a C-arm calibration-based method and a bi-planar positioning method - are used to study the influence of different image quality parameters, such as resolution, distortion, contrast and signal-to-noise ratio, on positioning accuracy. The error propagation rules of image error in different spatial positioning methods are analyzed by the Monte Carlo method. RESULTS: Correlation analysis showed that resolution and distortion had a significant influence on spatial positioning accuracy. In addition the C-arm calibration-based method was more sensitive to image distortion, while the bi-planar positioning method was more susceptible to image resolution. The image contrast and signal-to-noise ratio have no significant influence on the spatial positioning accuracy. The result of Monte Carlo analysis proved that generally the bi-planar positioning method was more sensitive to image quality than the C-arm calibration-based method. CONCLUSIONS: The quality of intraoperative fluoroscopic images is a key issue in the spatial positioning accuracy of a CAOS system. Although the 2 typical positioning methods have very similar mathematical principles, they showed different sensitivities to different image quality parameters. The result of this research may help to create a realistic standard for intraoperative fluoroscopic images for CAOS systems.

Experimental investigations and finite element simulation of cutting heat in vibrational and conventional drilling of cortical bone.

Heat generated during bone drilling could cause irreversible thermal damage, which can lead to bone necrosis or even osteomyelitis. In this study, vibrational drilling was applied to fresh bovine bones to investigate the cutting heat in comparison with conventional drilling through experimental investigation and finite element analysis (FEA). The influence of vibrational frequency and amplitude on cutting heat generation and conduction were studied. The experimental results showed that, compared with the conventional drilling, vibrational drilling could significantly reduce the cutting temperature in drilling of cortical bone (P<0.05): the cutting temperature tended to decrease with increasing vibrational frequency and amplitude. The FEA results also showed that the vibrational amplitude holds a significant effect on the cutting heat conduction.