Peng Rong-Chao, Li Yi, Yan Wen-Rong
School of Biomedical Engineering, Guangdong Medical University, Dongguan, 523808, Guangdong, China.
School of Biomedical Sciences, The Chinese University of Hong Kong, Hong Kong, 999077, China.
Sci Rep. 2021 May 27;11(1):11215. doi: 10.1038/s41598-021-90056-2.
Beat-to-beat R-R intervals (RRI) and pulse arrival time (PAT) provide pivotal information to evaluate cardiac autonomic functions for predicting arrhythmias and cardiovascular morbidity. However, their relationship has not been clearly understood. In this study, we simultaneously recorded electrocardiograms and photoplethysmograms on 34 subjects in the natural state, and on 55 subjects under the cold stimulation. The RRI and the PAT were calculated and then analyzed using Pearson correlation coefficient. The results showed that the RRI and the PAT were strongly correlated (r = 0.562) and the RRI series were 2.18 ± 0.40 beats advanced to the PAT series. After smoothing, the RRI and the PAT were more correlated in the low frequency than in the high frequency. Furthermore, when involving RRI with the phase effect, the proposed PAT based model showed better performance for blood pressure estimation. We think these results are helpful to understand the underlying regulatory mechanisms of the two cardiovascular factors, and would provide useful suggestions for non-invasive cuffless blood pressure estimation.
逐搏R-R间期(RRI)和脉搏波传导时间(PAT)为评估心脏自主神经功能以预测心律失常和心血管疾病提供了关键信息。然而,它们之间的关系尚未被清楚地理解。在本研究中,我们在自然状态下对34名受试者以及在冷刺激下对55名受试者同时记录了心电图和光电容积脉搏波图。计算RRI和PAT,然后使用Pearson相关系数进行分析。结果表明,RRI和PAT高度相关(r = 0.562),且RRI序列比PAT序列提前2.18±0.40个搏动。平滑处理后,RRI和PAT在低频段比在高频段的相关性更强。此外,当考虑RRI的相位效应时,所提出的基于PAT的模型在血压估计方面表现更好。我们认为这些结果有助于理解这两种心血管因素的潜在调节机制,并将为无创无袖带血压估计提供有用的建议。