基于非稳态时间序列的生理控制模型研究

生理控制系统通过多个生理变量(血压、心率、呼吸等)之间相互作用与反馈实现自动调节,达到在内外干扰下维持着体内平衡.这种作用与反馈能力的减弱,甚至丧失,与衰老和疾病息息相关.本文提出了一种将生理模型与切换线性动力学结合的方法--P-SLD,通过来自PhysioNet数据库近300例成人ICU患者的平均动脉压和心率的非稳态生理时间序列以及256例健康人不同姿态(仰卧、非仰卧)下血压和心率的非稳态生理时间序列,对P-SLD传递函数和功率谱分析,验证了本文所提的方法可以用来揭示与严重的全身炎症反应综合征(SIRS)相关联的变化以及可以自动捕获姿势改变对压力反射增益的影响.同时本文研究结果表明,即使在调整临床的干预之后,平均压与心率的偶联度的降低与严重的SIRS强相关,为健康和疾病条件下生理控制的自动调节的分解提供了假说.

Study of physiological control model based on unsteady time series

Physiological control system can adjust automatically through the interaction and feedback among many physiological variables (blood pressure, heart rate, respiration, etc.), and maintain internal and external balance. The weakening or even loss of the function and feedback ability is closely related to aging and disease. A method combining physiological models with switched linear dynamics is proposed in this paper, called P-SLD, the transfer function and power spectrum of the P-SLD are analyzed by using the unsteady physiological time series of mean arterial pressure and heart rate from nearly 300 adult ICU patients and 256 healthy people with different postures (supine and non-supine) from PhysioNet database, verifying that the proposed method can be used to reveal the changes associated with severe systemic inflammatory response syndrome (SIRS) and automatically capture the effects of postural changes on baroreflex gain. At the same time, the results of the study in this paper show that the decrease of the coupling of the mean pressure and heart rate has strong correlation with severe SIRS, even after adjusting for clinical interventions, it provides a hypothesis for the decomposition of automatic regulation of physiological control under health and disease conditions.