To address the issue of reduced signal quality of photoplethysmography caused by local fluctuation,an approach called locally orthogonal weighted polynomial fitting(LOWPF)is proposed for signal smoothing.After determining the positions of the fluctuation sequences using the forward-backward difference XOR method,weighted polynomial fitting is applied to these sequences,and the fitted values are used to replace the fluctuation sequences to achieve signal smoothing.By constructing orthogonal basis functions,the condition number of the coefficient matrix is reduced,and the stability of the equation system solution for higher-order fitting is improved.Simulation results demonstrate that the smoothed signal's XOR smoothness of the proposed method surpasses that of the moving average algorithm and the empirical mode decomposition reconstruction algorithm.The smoothing results on 241 sets of measured PPG signals show that LOWPF achieves an efficiency of smoothness of 89.10%,significantly higher than the 78.05%of empirical mode decomposition and the 59.13%of the 5-point moving average algorithm.LOWPF has promising application prospects for smoothing signals with significant local fluctuations.

To address the issue of reduced signal quality of photoplethysmography caused by local fluctuation,an approach called locally orthogonal weighted polynomial fitting(LOWPF)is proposed for signal smoothing.After determining the positions of the fluctuation sequences using the forward-backward difference XOR method,weighted polynomial fitting is applied to these sequences,and the fitted values are used to replace the fluctuation sequences to achieve signal smoothing.By constructing orthogonal basis functions,the condition number of the coefficient matrix is reduced,and the stability of the equation system solution for higher-order fitting is improved.Simulation results demonstrate that the smoothed signal's XOR smoothness of the proposed method surpasses that of the moving average algorithm and the empirical mode decomposition reconstruction algorithm.The smoothing results on 241 sets of measured PPG signals show that LOWPF achieves an efficiency of smoothness of 89.10%,significantly higher than the 78.05%of empirical mode decomposition and the 59.13%of the 5-point moving average algorithm.LOWPF has promising application prospects for smoothing signals with significant local fluctuations.