A new single degree-of-freedom （1 DOF） resonance device was developed. It mainly comprises a linear motor, a vibrating screen, a supporting spring set, a supporting frame and a damper set. Forces acting on the vibra...A new single degree-of-freedom （1 DOF） resonance device was developed. It mainly comprises a linear motor, a vibrating screen, a supporting spring set, a supporting frame and a damper set. Forces acting on the vibrating screen were found. A differential equation for describing the forces was set up. Equations that were used to evaluate the exciting force and exciting frequency in resonance were derived from the solution to the differential equation. In addition, an equation for evaluating the deformed magnitude of the damping springs in the damper set was presented so that the suitable damping may be obtained. Finally, a Matlab/Simulink model of the new i DOF resonance device was also built. Displacement-time curves of the vibrating screen under four conditions were obtained in the use of the Matlab/Simulink simulation. The curves indicate that it can shorten the time for the vibrating screen to be into the stable resonance with increasing the damping, and it can lengthen the time with increasing the vibrated mass or amplitude, but every given angular frequency cannot acquire the desired amplitude value of resonance.展开更多
Atrial fibrillation(AF) has been considered as a growing epidemiological problem in the world,with a substantial impact on morbidity and mortality.Ambulatory electrocardiography(e.g.,Holter) monitoring is commonly use...Atrial fibrillation(AF) has been considered as a growing epidemiological problem in the world,with a substantial impact on morbidity and mortality.Ambulatory electrocardiography(e.g.,Holter) monitoring is commonly used for AF diagnosis and therapy and the automated detection of AF is of great significance due to the vast amount of information provided.This study presents a combined method to achieve high accuracy in AF detection.Firstly,we detected the suspected transitions between AF and sinus rhythm using the delta RR interval distribution difference curve,which were then classified by a combination analysis of P wave and RR interval.The MIT-BIH AF database was used for algorithm validation and a high sensitivity and a high specificity(98.2% and 97.5%,respectively) were achieved.Further,we developed a dataset of 24-h paroxysmal AF Holter recordings(n=45) to evaluate the performance in clinical practice,which yielded satisfactory accuracy(sensitivity=96.3%,specificity=96.8%).展开更多
文摘A new single degree-of-freedom （1 DOF） resonance device was developed. It mainly comprises a linear motor, a vibrating screen, a supporting spring set, a supporting frame and a damper set. Forces acting on the vibrating screen were found. A differential equation for describing the forces was set up. Equations that were used to evaluate the exciting force and exciting frequency in resonance were derived from the solution to the differential equation. In addition, an equation for evaluating the deformed magnitude of the damping springs in the damper set was presented so that the suitable damping may be obtained. Finally, a Matlab/Simulink model of the new i DOF resonance device was also built. Displacement-time curves of the vibrating screen under four conditions were obtained in the use of the Matlab/Simulink simulation. The curves indicate that it can shorten the time for the vibrating screen to be into the stable resonance with increasing the damping, and it can lengthen the time with increasing the vibrated mass or amplitude, but every given angular frequency cannot acquire the desired amplitude value of resonance.
文摘Atrial fibrillation(AF) has been considered as a growing epidemiological problem in the world,with a substantial impact on morbidity and mortality.Ambulatory electrocardiography(e.g.,Holter) monitoring is commonly used for AF diagnosis and therapy and the automated detection of AF is of great significance due to the vast amount of information provided.This study presents a combined method to achieve high accuracy in AF detection.Firstly,we detected the suspected transitions between AF and sinus rhythm using the delta RR interval distribution difference curve,which were then classified by a combination analysis of P wave and RR interval.The MIT-BIH AF database was used for algorithm validation and a high sensitivity and a high specificity(98.2% and 97.5%,respectively) were achieved.Further,we developed a dataset of 24-h paroxysmal AF Holter recordings(n=45) to evaluate the performance in clinical practice,which yielded satisfactory accuracy(sensitivity=96.3%,specificity=96.8%).
