基于遗传算法的心肺复苏术仿真模型下肢参数优化研究

Research on Optimization of Lower Limb Parameters of Cardiopulmonary Resuscitation Simulation Model Based on Genetic Algorithm

心脏骤停是所有急症中最危重的临床综合征之一,而对于心脏骤停患者来说,必须采取的救治方法就是对其施行心肺复苏术(CPR)。为了更好地仿真双泵复苏术下人体血流动力学效果,即辅以体外反搏和吸气阻力阀的主动按压/放松CPR,并能更详细地研究人体下肢各部分的生理参数变化,我们对Babbs建立的CPR仿真模型进行了细化,将下肢部分细分成了髂部、大腿和小腿,其中包含15个生理参数。然后,利用遗传算法对这15个生理参数进行了优化研究,得到了较为理想的仿真结果。

Sudden cardiac arrest is one of the critical clinical syndromes in emergency situations. A cardiopulmonary resuscitation （CPR） is a necessary curing means for those patients with sudden cardiac arrest. In order to simulate effectively the hemodynamic effects of human under AEI-CPR, which is active compression-decompression CPR cou- pled with enhanced external counter-pulsation and inspiratory impedance threshold valve, and research physiological parameters of each part of lower limbs in more detail, a CPR simulation model established by Babbs was refined. The part of lower limbs was divided into iliac, thigh and calf, which had 15 physiological parameters. Then, these 15 physiological parameters based on genetic algorithm were optimized, and ideal simulation results were obtained finally.