Peltokangas Mikko, Vehkaoja Antti, Huotari Matti, Verho Jarmo, Mattila Ville M, Röning Juha, Romsi Pekka, Lekkala Jukka, Oksala Niku
Department of Automation Science and Engineering, BioMediTech, Tampere University of Technology, Tampere, Finland.
Physiol Meas. 2017 Feb;38(2):139-154. doi: 10.1088/1361-6579/aa4eb0. Epub 2017 Jan 5.
In this study, we propose and analyze a noninvasive method for detecting the atherosclerotic changes of vasculature based on the analysis of photoplethysmographic (PPG) signals.
the proposed method is called finger-toe (FT)-plot analysis that utilizes both finger and toe PPG signals. For the features extracted from the FT-plots, we implemented different linear discriminant analysis based classifiers and analyzed seven promising ones in detail. We used the signals recorded from altogether 75 test subjects (categorized as 27 atherosclerotic patients and 48 control subjects based on ankle brachial pressure index, symptoms and disease history) in the training, and testing of the method. Besides leave one out cross validation, we tested the method by using training data independent signals recorded with two different PPG devices. The performance of the FT-plot is compared with other indicators related to the risk of cardiovascular diseases.
we found an average area under ROC (receiver operating characteristic) curve of [Formula: see text] (mean ± standard deviation based on different datasets), sensitivity of [Formula: see text], specificity of [Formula: see text], accuracy of [Formula: see text], performance of [Formula: see text] and positive and negative predictive values of [Formula: see text] and [Formula: see text], respectively, for the different tested classifiers.
the study shows that the FT-plot analysis could be a useful additional tool for detecting atherosclerotic changes. Our findings provide evidence for the utility of multi-channel pulse wave measurements and analysis for the detection of atherosclerosis. This may facilitate development of novel early diagnostic approaches and preventive strategies.
在本研究中,我们提出并分析了一种基于光电容积脉搏波描记法(PPG)信号分析来检测血管系统动脉粥样硬化变化的非侵入性方法。
所提出的方法称为指-趾(FT)图分析,它利用手指和脚趾的PPG信号。对于从FT图中提取的特征,我们实现了不同的基于线性判别分析的分类器,并详细分析了七个有前景的分类器。我们使用了总共75名测试对象记录的信号(根据踝臂压力指数、症状和疾病史分为27名动脉粥样硬化患者和48名对照对象)来训练和测试该方法。除了留一法交叉验证外,我们还使用两种不同PPG设备记录的独立于训练数据的信号来测试该方法。将FT图的性能与其他与心血管疾病风险相关的指标进行比较。
对于不同测试的分类器,我们发现受试者工作特征(ROC)曲线下的平均面积为[公式:见原文](基于不同数据集的均值±标准差),灵敏度为[公式:见原文],特异性为[公式:见原文],准确率为[公式:见原文],性能为[公式:见原文],阳性预测值和阴性预测值分别为[公式:见原文]和[公式:见原文]。
该研究表明FT图分析可能是检测动脉粥样硬化变化的一种有用的辅助工具。我们的研究结果为多通道脉搏波测量和分析在动脉粥样硬化检测中的实用性提供了证据。这可能有助于开发新的早期诊断方法和预防策略。