Zhang Linjia, Yu Xiaomin, Lin Jian, Chou Chengen, Wang Zhengxian
Key Laboratory of Biomedical Effect of Physical Field and Instrument, School of Electrical and Electronic Engineering, Chengdu University of Information Technology, Chengdu 610225, P. R. China.
Chongqing Institute of Microelectronics and Microsystems, Beijing Institute of Techonology, Chongqing 401332, P. R. China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2024 Aug 25;41(4):818-825. doi: 10.7507/1001-5515.202310053.
The performance of a pulse oximeter based on photoelectric detection is greatly affected by motion noise (MA) in the photoplethysmographic (PPG) signal. This paper presents an algorithm for detecting motion oxygen saturation, which reconstructs a motion noise reference signal using ensemble of complete adaptive noise and empirical mode decomposition combined with multi-scale permutation entropy, and eliminates MA in the PPG signal using a convex combination least mean square adaptive filters to calculate dynamic oxygen saturation. The test results show that, under simulated walking and jogging conditions, the mean absolute error (MAE) of oxygen saturation estimated by the proposed algorithm and the reference oxygen saturation are 0.05 and 0.07, respectively, with means absolute percentage error (MAPE) of 0.05% and 0.07%, respectively. The overall Pearson correlation coefficient reaches 0.971 2. The proposed scheme effectively reduces motion artifacts in the corrupted PPG signal and is expected to be applied in portable photoelectric pulse oximeters to improve the accuracy of dynamic oxygen saturation measurement.
基于光电检测的脉搏血氧仪的性能会受到光电容积脉搏波信号（PPG）中的运动噪声（MA）的显著影响。本文提出了一种检测运动状态下血氧饱和度的算法，该算法利用完备总体自适应噪声与经验模态分解相结合并结合多尺度排列熵来重构运动噪声参考信号，并使用凸组合最小均方自适应滤波器消除PPG信号中的运动噪声，以计算动态血氧饱和度。测试结果表明，在模拟行走和慢跑条件下，所提算法估计的血氧饱和度与参考血氧饱和度的平均绝对误差（MAE）分别为0.05和0.07，平均绝对百分比误差（MAPE）分别为0.05%和0.07%。总体皮尔逊相关系数达到0.971 2。所提方案有效降低了受损PPG信号中的运动伪影，有望应用于便携式光电脉搏血氧仪中，以提高动态血氧饱和度测量的准确性。
