首页> 外文期刊>Annals of Biomedical Engineering: The Journal of the Biomedical Engineering Society >Photoplethysmograph Signal Reconstruction based on a Novel Motion Artifact Detection-Reduction Approach. Part II: Motion and Noise Artifact Removal
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Photoplethysmograph Signal Reconstruction based on a Novel Motion Artifact Detection-Reduction Approach. Part II: Motion and Noise Artifact Removal

机译:基于一种新颖的运动伪像检测-减少方法的光电容积描记器信号重建。第二部分:去除运动和噪声伪像

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We introduce a new method to reconstruct motion and noise artifact (MNA) contaminated photoplethysmogram (PPG) data. A method to detect MNA corrupted data is provided in a companion paper. Our reconstruction algorithm is based on an iterative motion artifact removal (IMAR) approach, which utilizes the singular spectral analysis algorithm to remove MNA artifacts so that the most accurate estimates of uncorrupted heart rates (HRs) and arterial oxygen saturation (SpO(2)) values recorded by a pulse oximeter can be derived. Using both computer simulations and three different experimental data sets, we show that the proposed IMAR approach can reliably reconstruct MNA corrupted data segments, as the estimated HR and SpO(2) values do not significantly deviate from the uncorrupted reference measurements. Comparison of the accuracy of reconstruction of the MNA corrupted data segments between our IMAR approach and the time-domain independent component analysis (TD-ICA) is made for all data sets as the latter method has been shown to provide good performance. For simulated data, there were no significant differences in the reconstructed HR and SpO(2) values starting from 10 dB down to 215 dB for both white and colored noise contaminated PPG data using IMAR; for TD-ICA, significant differences were observed starting at 10 dB. Two experimental PPG data sets were created with contrived MNA by having subjects perform random forehead and rapid side-to-side finger movements show that; the performance of the IMAR approach on these data sets was quite accurate as non-significant differences in the reconstructed HR and SpO(2) were found compared to non-contaminated reference values, in most subjects. In comparison, the accuracy of the TD-ICA was poor as there were significant differences in reconstructed HR and SpO(2) values in most subjects. For non-contrived MNA corrupted PPG data, which were collected with subjects performing walking and stair climbing tasks, the IMAR significantly outperformed TD-ICA as the former method provided HR and SpO(2) values that were non-significantly different than MNA free reference values.
机译:我们介绍一种新的方法来重建运动和噪声伪像(MNA)污染的光电容积描记(PPG)数据。随附的论文中提供了一种检测MNA损坏的数据的方法。我们的重建算法基于迭代运动伪影去除(IMAR)方法,该方法利用奇异频谱分析算法来去除MNA伪影,以便最准确地估计未损坏的心率(HR)和动脉血氧饱和度(SpO(2))可以导出脉搏血氧仪记录的值。使用计算机模拟和三个不同的实验数据集,我们表明,提出的IMAR方法可以可靠地重建MNA损坏的数据段,因为估计的HR和SpO(2)值不会明显偏离未损坏的参考测量值。我们对所有数据集的IMAR方法和时域独立分量分析(TD-ICA)之间的MNA损坏的数据段的重建精度进行了比较,因为后者已被证明可以提供良好的性能。对于模拟数据,对于使用IMAR的受白色和彩色噪声污染的PPG数据,从10 dB到215 dB开始的重构HR和SpO(2)值没有显着差异。对于TD-ICA,从10 dB开始观察到显着差异。通过使受试者进行随机的前额和快速的左右手指移动表明,人为的MNA创建了两个实验性PPG数据集。 IMAR方法在这些数据集上的性能非常准确,因为在大多数受试者中,与未污染的参考值相比,在重建的HR和SpO(2)中发现了无显着差异。相比之下,TD-ICA的准确性很差,因为在大多数受试者中,重建的HR和SpO(2)值存在显着差异。对于由伪造的MNA损坏的PPG数据,这些数据是由执行步行和爬楼梯任务的受试者收集的,IMA的性能明显优于TD-ICA,因为前一种方法提供的HR和SpO(2)值与MNA免费参考无明显差异价值观。

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