KUBAI: Sensor Fusion for Non-Invasive Fetal Heart Rate Tracking.
KUBAI: Sensor Fusion for Non-Invasive Fetal Heart Rate Tracking.
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KUBAI：用于无创胎儿心率跟踪的传感器融合。
DOI：
10.1109/tbme.2023.3238736
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发表时间：
2023
期刊：
影响因子：
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通讯作者：
Ghiasi,Soheil
中科院分区：
文献类型：
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作者：
Kasap,Begum;Vali,Kourosh;Qian,Weitai;Saffarpour,Mahya;Ghiasi,Soheil
目的胎儿心率（FHR）是围产期胎儿监护的重要指标。然而，运动、收缩和其他动态可能会大大降低采集信号的质量，阻碍FHR的鲁棒跟踪。我们的目标是展示如何使用多个传感器来帮助克服这些挑战。方法开发一种新的随机传感器融合算法KUBAI1，提高FHR监测精度。为了证明我们的方法的有效性，我们使用一种新型的无创胎儿脉搏血氧仪对从金标准大型妊娠动物模型收集的数据进行了评估。结果该方法对侵入式地面真值测量的精度进行了评价。我们在五个不同的数据集上使用KUBAI获得了低于6次/分钟（BPM）的均方根误差（RMSE）。KUBAI的性能也与单传感器版本的算法进行了比较，以证明由于传感器融合的鲁棒性。KUBAI发现，与单传感器FHR估计相比，多传感器估计的RMSE总体降低了23.5%至84%。5个实验中RMSE的改进均值为11.959.62 BPM。此外，与文献中发现的另一种多传感器FHR跟踪方法相比，KUBAI的RMSE降低了84%，与参考文献的相关性提高了3倍。结论所提出的传感器融合算法KUBAI能够在不同噪声水平下无创准确地估计胎儿心率。本文提出的方法可以使其他多传感器测量装置受益，这些装置可能受到低测量频率，低信噪比或测量信号间歇性损失的挑战。
ObjectiveFetal heart rate (FHR) is critical for perinatal fetal monitoring. However, motions, contractions and other dynamics may substantially degrade the quality of acquired signals, hindering robust tracking of FHR. We aim to demonstrate how use of multiple sensors can help overcome these challenges.MethodsWe develop KUBAI1, a novel stochastic sensor fusion algorithm, to improve FHR monitoring accuracy. To demonstrate the efficacy of our approach, we evaluate it on data collected from gold standard large pregnant animal models, using a novel non-invasive fetal pulse oximeter.ResultsThe accuracy of the proposed method is evaluated against invasive ground-truth measurements. We obtained below 6 beats-per-minute (BPM) root-mean-square error (RMSE) with KUBAI, on five different datasets. KUBAI's performance is also compared against a single-sensor version of the algorithm to demonstrate the robustness due to sensor fusion. KUBAI's multi-sensor estimates are found to give overall 23.5% to 84% lower RMSE than single-sensor FHR estimates. The meanSD of improvement in RMSE is 11.959.62 BPM across five experiments. Furthermore, KUBAI is shown to have 84% lower RMSE and3 times highercorrelation with reference compared to another multi-sensor FHR tracking method found in literature.ConclusionThe results support the effectiveness of KUBAI, the proposed sensor fusion algorithm, to non-invasively and accurately estimate fetal heart rate with varying levels of noise in the measurements.SignificanceThe presented method can benefit other multi-sensor measurement setups, which may be challenged by low measurement frequency, low signal-to-noise ratio, or intermittent loss of measured signal.