Martínez Gloria, Howard Newton, Abbott Derek, Lim Kenneth, Ward Rabab, Elgendi Mohamed
School of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
Center for Research and Advanced Studies (Cinvestav), Monterrey's Unit, Apodaca N. L. 66600, México.
J Clin Med. 2018 Sep 30;7(10):316. doi: 10.3390/jcm7100316.
Arterial Blood Pressure (ABP) and photoplethysmography (PPG) are both useful techniques to monitor cardiovascular status. Though ABP monitoring is more widely employed, this procedure of signal acquisition whether done invasively or non-invasively may cause inconvenience and discomfort to the patients. PPG, however, is simple, noninvasive, and can be used for continuous measurement. This paper focuses on analyzing the similarities in time and frequency domains between ABP and PPG signals for normotensive, prehypertensive and hypertensive subjects and the feasibility of the classification of subjects considering the results of the analysis performed. From a database with 120 records of ABP and PPG, each 120 s in length, the records where separated into epochs taking into account 10 heartbeats, and the following statistical measures were performed: Correlation (), Coherence (COH), Partial Coherence (pCOH), Partial Directed Coherence (PDC), Directed Transfer Function (DTF), Full Frequency Directed Transfer Function (ffDTF) and Direct Directed Transfer Function (dDTF). The correlation coefficient was r > 0.9 on average for all groups, indicating a strong morphology similarity. For COH and pCOH, coherence (linear correlation in frequency domain) was found with significance ( < 0.01) in differentiating between normotensive and hypertensive subjects using PPG signals. For the dataset at hand, only two synchrony measures are able to convincingly distinguish hypertensive subjects from normotensive control subjects, i.e., ffDTF and dDTF. From PDC, DTF, ffDTF, and dDTF, a consistent, a strong significant causality from ABP→PPG was found. When all synchrony measures were combined, an 87.5 % accuracy was achieved to detect hypertension using a Neural Network classifier, suggesting that PPG holds most informative features that exist in ABP.
动脉血压(ABP)和光电容积脉搏波描记法(PPG)都是监测心血管状态的有用技术。尽管ABP监测应用更为广泛,但这种信号采集过程,无论是侵入性还是非侵入性的,都可能给患者带来不便和不适。然而,PPG简单、无创,可用于连续测量。本文重点分析血压正常、高血压前期和高血压患者的ABP与PPG信号在时域和频域上的相似性,以及根据分析结果对受试者进行分类的可行性。从一个包含120条ABP和PPG记录(每条记录时长120秒)的数据库中,将记录按10个心跳分成若干段,并进行了以下统计测量:相关性()、相干性(COH)、偏相干性(pCOH)、偏定向相干性(PDC)、定向传递函数(DTF)、全频定向传递函数(ffDTF)和直接定向传递函数(dDTF)。所有组的平均相关系数r>0.9,表明形态相似性很强。对于COH和pCOH,发现在使用PPG信号区分血压正常和高血压受试者时,相干性(频域中的线性相关性)具有显著性(<0.01)。对于手头的数据集,只有两种同步测量方法能够令人信服地将高血压受试者与血压正常的对照受试者区分开来,即ffDTF和dDTF。从PDC、DTF、ffDTF和dDTF中,发现从ABP到PPG存在一致且显著的因果关系。当所有同步测量方法结合使用时,使用神经网络分类器检测高血压的准确率达到了87.5%,这表明PPG包含了ABP中存在的大多数信息特征。