由于微小型嵌入式系统尺寸和计算能力的限制,在对生命体征信号进行检查时,往往较难实现实时与精确兼顾。为了解决该问题,本文提出了一种基于二阶微分方程与仿射变换理论结合的心电信号滤波算法(ATSDEF),并进行了与粒子滤波方法的滤波性能对比实验,证明了ATSDEF方法有较粒子滤波更好的滤波性能。通过微小型嵌入式心电测量系统对正常与异常心电信号进行在线滤波实验,验证了该算法可以有效的滤除心电信号的噪声,且能够保持心电信号中较为微弱的细节特征,从而保证了信号滤波后的精度,解决了微小型嵌入式系统的实时信号处理难题。
Due to limitations in the size and computational power of miniature embedded systems,it is often difficult to achieve real-time and accurate reconciliation when testing vital signs. To solve this problem,we propose an ECG signal filtering algorithm based on a second-order differential equation and the affine transformation theory ( ATS -DEF ) .We compared the filtering performance of our proposed algorithm with that of the particle filter method and the results confirm the ATSDEF to be more effective. Lastly,w e validated the algorithm in normal and abnormal ECG filtering experiments,the results of which demonstrate its ability to not only effectively filter ECG signal noise, but also to retain detailed weak characteristics in the ECG signal to ensure the accuracy of signal filtering,thereby solving the longstanding problems of the real-time signal processing of miniature embedded systems.