Advancing Non-Cuff Hypertension Detection: Leveraging 1D Convolutional Neural Network and Time Domain Physiological Signals

N. Nuryani, T. P. Utomo, N. Prabowo, Aripriharta, Muhammad Yazid, Mohtar Yunianto
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Abstract

Timely identification of hypertension (HT) is crucial for effectively managing and reducing the potential health consequences, including cardiovascular events such as heart attacks and strokes, as well as the development of kidney disease. Traditional cuff-based devices often discourage regular monitoring because they cause discomfort. Furthermore, the lack of symptoms in HT complicates the early detection of this condition. To address these challenges, our study employs a non-cuff methodology that utilizes unprocessed electrocardiogram (ECG) and photoplethysmogram (PPG) signals. We utilize a customized approach to enhance the features of a one-dimensional convolutional neural network (CNN) specifically tailored to optimize timeseries data. In contrast to previous research, our methodology avoids the need for complex signal extraction or transformation techniques. The main goal is to identify the optimal input signals and fine-tune the critical hyperparameters of CNNs. The clinical data underwent analysis, which revealed that the use of an integrated ECG and PPG approach resulted in the highest level of accuracy for detection. Notably, the F1 score achieved an impressive value of 98.88%. When evaluated separately, ECG outperformed PPG. Our study contributes to the advancement of the field by introducing a new approach that combines comfort and high accuracy in the early detection of HT. This method is practical and ensures a patient-friendly experience.
推进非袖带型高血压检测:利用一维卷积神经网络和时域生理信号
及时发现高血压(HT)对于有效控制和减少潜在的健康后果至关重要,包括心脏病发作和中风等心血管事件以及肾脏疾病的发展。传统的袖带式设备通常会引起不适,因此不鼓励定期进行监测。此外,高血压没有症状,这也使早期检测变得复杂。为了应对这些挑战,我们的研究采用了一种非袖带方法,利用未经处理的心电图(ECG)和光电搏动图(PPG)信号。我们采用定制方法来增强一维卷积神经网络(CNN)的特征,该网络专门为优化时间序列数据而定制。与以往的研究不同,我们的方法无需复杂的信号提取或转换技术。主要目标是确定最佳输入信号,并微调 CNN 的关键超参数。对临床数据进行分析后发现,使用心电图和 PPG 集成方法的检测准确率最高。值得注意的是,F1 分数达到了令人印象深刻的 98.88%。在单独评估时,ECG 的表现优于 PPG。我们的研究引入了一种新方法,将早期检测 HT 的舒适性和高准确性相结合,为该领域的发展做出了贡献。这种方法非常实用,可确保为患者提供友好的体验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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