具有相位同步功能的多软件传感器无监督组合:一种用于心电图衍生呼吸的稳健方法。

IF 2.3 4区 医学 Q3 BIOPHYSICS Physiological measurement Pub Date : 2024-04-03 DOI:10.1088/1361-6579/ad290b
Jacob McErlean, John Malik, Yu-Ting Lin, Ronen Talmon, Hau-Tieng Wu
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引用次数: 0

摘要

目的我们的目标是融合不同心电图衍生呼吸(EDR)算法的输出,以创建一个质量更高的 EDR 信号:我们将每种 EDR 算法视为从不同有利位置记录呼吸活动的软件传感器,根据呼吸信号质量指数确定高质量的软件传感器,使用基于图连接拉普拉卡方的相位同步技术对最高质量的 EDR 进行对齐,最后融合这些对齐的高质量 EDR。我们将输出称为同步组装 EDR 信号。我们在两个大型整夜多导睡眠图数据库中对所提出的算法进行了评估。我们使用不同硬件传感器记录的三种呼吸信号评估了所提算法的性能,并将其与其他现有的 EDR 算法进行了比较。我们共对五种情况进行了敏感性分析:取 EDR 信号的平均值进行融合,以及不进行和进行同步、不进行和进行信号质量选择的四种 EDR 信号对齐情况:从同步相关性(-score)、最佳传输(OT)距离和平均频率(AF)得分来看,同步组装的 EDR 算法优于现有的 EDR 算法,且均具有统计学意义。灵敏度分析表明,信号质量选择和 EDR 信号对齐对性能至关重要,二者均有统计学意义:同步组装的 EDR 可从心电图中提供可靠的呼吸信息:相位同步不仅在理论上是严谨的,而且在设计稳健的 EDR 方面也是实用的。
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Unsupervised ensembling of multiple software sensors with phase synchronization: a robust approach for electrocardiogram-derived respiration.

Objective.We aimed to fuse the outputs of different electrocardiogram-derived respiration (EDR) algorithms to create one higher quality EDR signal.Methods.We viewed each EDR algorithm as a software sensor that recorded breathing activity from a different vantage point, identified high-quality software sensors based on the respiratory signal quality index, aligned the highest-quality EDRs with a phase synchronization technique based on the graph connection Laplacian, and finally fused those aligned, high-quality EDRs. We refer to the output as the sync-ensembled EDR signal. The proposed algorithm was evaluated on two large-scale databases of whole-night polysomnograms. We evaluated the performance of the proposed algorithm using three respiratory signals recorded from different hardware sensors, and compared it with other existing EDR algorithms. A sensitivity analysis was carried out for a total of five cases: fusion by taking the mean of EDR signals, and the four cases of EDR signal alignment without and with synchronization and without and with signal quality selection.Results.The sync-ensembled EDR algorithm outperforms existing EDR algorithms when evaluated by the synchronized correlation (γ-score), optimal transport (OT) distance, and estimated average respiratory rate score, all with statistical significance. The sensitivity analysis shows that the signal quality selection and EDR signal alignment are both critical for the performance, both with statistical significance.Conclusion.The sync-ensembled EDR provides robust respiratory information from electrocardiogram.Significance.Phase synchronization is not only theoretically rigorous but also practical to design a robust EDR.

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来源期刊
Physiological measurement
Physiological measurement 生物-工程:生物医学
CiteScore
5.50
自引率
9.40%
发文量
124
审稿时长
3 months
期刊介绍: Physiological Measurement publishes papers about the quantitative assessment and visualization of physiological function in clinical research and practice, with an emphasis on the development of new methods of measurement and their validation. Papers are published on topics including: applied physiology in illness and health electrical bioimpedance, optical and acoustic measurement techniques advanced methods of time series and other data analysis biomedical and clinical engineering in-patient and ambulatory monitoring point-of-care technologies novel clinical measurements of cardiovascular, neurological, and musculoskeletal systems. measurements in molecular, cellular and organ physiology and electrophysiology physiological modeling and simulation novel biomedical sensors, instruments, devices and systems measurement standards and guidelines.
期刊最新文献
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