This paper introduces time-synchronized convergence in fixed-time control,where all system states converge to the origin at the same time before a fixed time instant.Sufficient Lyapunov conditions are derived for fixe...This paper introduces time-synchronized convergence in fixed-time control,where all system states converge to the origin at the same time before a fixed time instant.Sufficient Lyapunov conditions are derived for fixed-time synchronized control(FTSC).An enhanced estimation method for synchronized settling time(ST)is proposed,with an explicit formula for its least upper bound(LUB),which reduces overestimation compared to existing methods.A switching-based technique is incorporated into the controller to avoid singularities while maintaining compatibility with the time-synchronized design.Simulation results validate the fixed-time synchronization properties and the improved ST estimation,demonstrating smoother output trajectories and reduced energy consumption.展开更多
In clinical settings,different kinds of patient monitoring systems and depth of anesthesia monitoring(DoA)systems have been widely used to assess the depth of sedation and patient's state.However,all these monitor...In clinical settings,different kinds of patient monitoring systems and depth of anesthesia monitoring(DoA)systems have been widely used to assess the depth of sedation and patient's state.However,all these monitoring systems are independent of each other.To date,no monitoring system has focused on the synchronized neural activities,cerebral metabolism,autonomic nervous system,and drug effects on the brain,as well as their interactions between neural activities and cerebral metabolism(i.e.,neurovascular coupling),and between brain and heart(i.e.,brain-heart coupling).In this study,we developed a time-synchronized multimodal monitoring system(TSMMS)that integrates electroencephalogram(EEG),near-infrared spectroscopy(NIRS),and standard physiological monitors(electrocardiograph,blood pressure,oxygen saturation)to provide a comprehensive view of the patient's physiological state during surgery.The coherence and Granger causality(GC)methods were used to quantify the neurovascular coupling and brain-heart coupling.The response surface model was used to estimate the combined propofol-remifentanil drug effect on the brain.TSMMS integrates data from various devices for a comprehensive analysis of vital signs.It enhances anesthesia monitoring through detailed EEG features,neurovascular,and brain-heart coupling indicators.Additionally,a response surface model estimates the combined effects of propofol and remifentanil,aiding anesthesiologists in drug administration.In conclusion,TSMMS provides a new tool for studying the coupling mechanism among neural activities,cerebral metabolism,and autonomic nervous system during general anesthesia.展开更多
基金supported by the National Natural Science Foundation of China under Grant No.62303256Shandong Higher Education Youth Innovation and Science,China Fund Support Program No.2023KJ362.
文摘This paper introduces time-synchronized convergence in fixed-time control,where all system states converge to the origin at the same time before a fixed time instant.Sufficient Lyapunov conditions are derived for fixed-time synchronized control(FTSC).An enhanced estimation method for synchronized settling time(ST)is proposed,with an explicit formula for its least upper bound(LUB),which reduces overestimation compared to existing methods.A switching-based technique is incorporated into the controller to avoid singularities while maintaining compatibility with the time-synchronized design.Simulation results validate the fixed-time synchronization properties and the improved ST estimation,demonstrating smoother output trajectories and reduced energy consumption.
基金supported by the National Natural Science Foundation of China(grant number 62073280)the Natural Science Fund for Distinguished Young Scholars,Hebei Province,China(F2021203033).
文摘In clinical settings,different kinds of patient monitoring systems and depth of anesthesia monitoring(DoA)systems have been widely used to assess the depth of sedation and patient's state.However,all these monitoring systems are independent of each other.To date,no monitoring system has focused on the synchronized neural activities,cerebral metabolism,autonomic nervous system,and drug effects on the brain,as well as their interactions between neural activities and cerebral metabolism(i.e.,neurovascular coupling),and between brain and heart(i.e.,brain-heart coupling).In this study,we developed a time-synchronized multimodal monitoring system(TSMMS)that integrates electroencephalogram(EEG),near-infrared spectroscopy(NIRS),and standard physiological monitors(electrocardiograph,blood pressure,oxygen saturation)to provide a comprehensive view of the patient's physiological state during surgery.The coherence and Granger causality(GC)methods were used to quantify the neurovascular coupling and brain-heart coupling.The response surface model was used to estimate the combined propofol-remifentanil drug effect on the brain.TSMMS integrates data from various devices for a comprehensive analysis of vital signs.It enhances anesthesia monitoring through detailed EEG features,neurovascular,and brain-heart coupling indicators.Additionally,a response surface model estimates the combined effects of propofol and remifentanil,aiding anesthesiologists in drug administration.In conclusion,TSMMS provides a new tool for studying the coupling mechanism among neural activities,cerebral metabolism,and autonomic nervous system during general anesthesia.
