ABSTRACT
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.
Subject(s)
Humans , Artifacts , Signal Processing, Computer-Assisted , Electrocardiography, Ambulatory/methods , Electrocardiography , MotionABSTRACT
Objective:To evaluate a self-designed intelligent robot-assisted minimally invasive reduction system in the reduction of unstable pelvic fractures by a cadaveric anatomic study.Methods:Ten unembalmed cadavers (7 male and 3 female ones) were used in this study. In each cadaveric specimen an unstable pelvic fracture was created in accordance with clinical case models (3 cases of type B1, 4 cases of type B2 and 3 cases of type C1 by the Tile classification). A self-designed intelligent robot-assisted minimally invasive reduction system was used to assist the reduction in the cadaveric models. Intraoperative registration and navigation time, autonomous reduction time, total operation time and reduction error were measured.Results:Effective reduction was completed in 10 bone models with the assistance of our self-designed intelligent robot-assisted minimally invasive reduction system. The time for intraoperative registration and navigation averaged 47.4 min (from 32 to 74 min), the autonomous reduction time 73.9 min (from 48 to 96 min), and the total operation time 121.3 min (from 83 to 170 min). The reduction error averaged 2.02 mm (from 1.67 to 2.62 mm), and the reduction results met the clinical requirements.Conclusion:Our self-designed intelligent robot-assisted minimally invasive reduction system is a new clinical solution for unstable pelvic fractures, showing advantages of agreement with clinical operative procedures, high reduction accuracy and operational feasibility, and reduced radiation exposure compared to a conventional operation.