ECG Signal Tracking Based on Improved LMS Adaptive Algorithm
The environment is complicated and the risk is higher when people work on poles and towers in high-altitude.How-ever,the current risk assessment strategy is mainly based on the ideal monitoring factor value,unable to consider the impact of the changes of operators and environmental factors according to the field situation,which makes the risk assessment can not be carried out in real time and is not conducive to the personal safety of operators.In order to realize the risk assessment of falling operations at high-altitude,an improved least-mean-square(LMS)adaptive algorithm based on adaptive filtering is proposed in this paper by considering the real-time acquisition of electrocardiogram(ECG)data,one of the monitoring factors of risk as-sessment.Because the traditional LMS algorithm is sensitive to the input signal autocorrelation matrix,three dynamic weights are added to the weight updating formula to make the improved algorithm more robust.The method of variable step size is adopted to ensure that the improved algorithm can give consideration to both convergence speed and convergence accuracy.The ECG signal of BIT-MIH ECG database is superimposed with normal distributed noise and the signal tracking is carried out to verify the ECG signal tracking accuracy under different conditions.The results show that the improved LMS method based on adaptive filtering can better track ECG signals and provide accurate monitoring factor values for better risk assessment.There-fore,it can better real-time assess the risk of operators working on the tower.
tower operationLMS algorithmECG signaltracking of signal