心室颤动（室颤）是发生心脏骤停的主要原因。而电击除颤则是终止室颤及恢复心脏自主循环的唯一有效手段。对室颤的治疗每延误1分钟，除颤成功率就会下降10%左右，而不成功或者不必要的高能量除颤又会增加心肌的损伤程度，从而降低复苏的概率。由于病人的发病机制和从室颤发生到首次除颤的时间均不相同，因此对每个病人实施心肺复苏治疗的具体方法也应有所不同。如何有效区分需要先行除颤还是先行胸外按压的病人，并为他们提供最佳的心肺复苏手段，是摆在我们面前的一项重大挑战。运用现代生物医学信号处理与分析方法对室颤波形进行分解与特征提取， 获取与心肌的电生理状态及除颤成功率密切相关的算法指标，是解决这个问题的有效途径。本研究提出了一种基于二维时间窗的室颤波形分析及心肺复苏优化决策算法，以实现为不同心脏骤停患者提供个性化及最优化的治疗方案，并通过临床实验验证该算法在优化心肺复苏中的指导作用。

Ventricular fibrillation (VF) occurs during many cases of cardiac arrest and electrical defibrillation is still the only effective therapy for the termination of VF. For every minute that passes between collapse and defibrillation, survival rates decrease 10% if no cardiopulmonary resuscitation (CPR) is provided. However, unneccesary or reptitive high energy defibrillations are associated with decresed postresuscitation myocardial function. Optimizing the timing of defibrillation is of great importance in order to discriminate the patients should receive immediate defibrillation versus delayed shock attempts with alternate therapies such as CPR in priority during cardiac arrest. The VF waveform change over time and CPR, which exhibits predictable ability of defibrillation success, therefore has the potential to guide CPR. The purpose of VF waveform analysis is to obtain information about the state of the myocardium and the probability of successful defibrillation. However, the value of VF waveform analysis to guide CPR management is still under investigation. This project is aimed to develop an improved VF waveform analysis and decision algorithm with the combination of nonlinear decomposition and time-frequency analysis for the optimization of CPR. The algorithm will be validated by clinical trials for the improvement of resuscitation outcome by predicting the defibrillation results and optimizing the timing of defibrillation.