摘要
介绍了一种基于卡尔曼滤波(Kalman filter)的在线评估ECG(electrocardiogram)信号状态的技术。当生理系统发生变化时,ECG信号会有许多突发转变点如跳跃和偏移等,及时准确地检测出这些异常点对临床具有重要意义。系统状态估计误差的突变可以直接预示生理信息的改变。本文介绍了此方法并通过实验验证了该方法的实用性。
In this paper, a prediction and real-time monitoring method for changing in ECG signals is proposed based on Kalman Filter technique. It is important that the change point such as jump and drift could be predicted and diagnosed from the measurement, so as to keep it safely. The Kalman filter technique can be used in estimating system states in real-time way. The sudden changes of the estimation errors of system status can he used as the predictor for the physiologic changes. This method is validated in practice according to the experimental results.
出处
《生物医学工程学杂志》
EI
CAS
CSCD
北大核心
2007年第1期215-218,共4页
Journal of Biomedical Engineering
