Liu Shuangyan, Teng Jing, Qi Xianghua, Wei Shoushui, Liu Chengyu
Institute of Biomedical Engineering, School of Control Science and Engineering, Shandong University, Jinan 250061, Shandong, China.
Department of Internal Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan 250011, Shandong, China.
Technol Health Care. 2017;25(3):435-445. doi: 10.3233/THC-161283.
The usefulness of heart rate variability (HRV) in the clinical research has been verified in numerous studies. However, it is controversy that using pulse rate variability (PRV) as a surrogate of HRV in different clinical applications.
We aimed to investigate whether PRV extracted from finger pulse photoplethysmography (Pleth) signal could substitute HRV from ECG signal during different sleep stages by analyzing the common time-domain, frequency-domain and non-linear indices.
Seventy-five sleep apnea patients were enrolled. For each patient, ECG and Pleth signals were simultaneously recorded for the whole night using Alice Sleepware Polysomnographic System and the sleep stage signals were automatically calculated by this System. Time-domain, frequency-domain and non-linear indices of both HRV and PRV were calculated for each sleep stage.
Mann-Whitney U-test showed that for both time-domain and frequency-domain indices, there were no statistical differences between HRV and PRV results during all four sleep stages. For non-linear indices, sample entropy reported statistical differences between HRV and PRV results for N1, N2 and REM sleeps (all P< 0.01) whereas fuzzy measure entropy only reported statistical differences for REM sleep (P< 0.05). SDNN, LF and LF/HF indices decreased for both HRV and PRV with the sleep deepening while HF and non-linear indices increased. In addition, there were strong and significant correlation between HRV and PRV indices during all four sleep stages (all P< 0.01).
PRV measurement could present the similar results as HRV analysis for sleep apnea patients during different sleep stages.
心率变异性（HRV）在临床研究中的实用性已在众多研究中得到验证。然而，在不同临床应用中使用脉搏率变异性（PRV）作为HRV的替代指标存在争议。
我们旨在通过分析常见的时域、频域和非线性指标，研究从手指脉搏光电容积脉搏波描记图（Pleth）信号中提取的PRV是否可以在不同睡眠阶段替代心电图信号中的HRV。
招募了75名睡眠呼吸暂停患者。对于每位患者，使用Alice Sleepware多导睡眠监测系统同时记录整夜的心电图和Pleth信号，并且该系统自动计算睡眠阶段信号。计算每个睡眠阶段HRV和PRV的时域、频域和非线性指标。
曼-惠特尼U检验显示，对于时域和频域指标，在所有四个睡眠阶段HRV和PRV结果之间均无统计学差异。对于非线性指标，样本熵显示N1、N2和快速眼动（REM）睡眠阶段HRV和PRV结果之间存在统计学差异（所有P<0.01），而模糊测度熵仅显示REM睡眠阶段存在统计学差异（P<0.05）。随着睡眠加深，HRV和PRV的标准差（SDNN）、低频（LF）和LF/高频（HF）指标均下降，而HF和非线性指标则升高。此外，在所有四个睡眠阶段HRV和PRV指标之间均存在强且显著的相关性（所有P<0.01）。
对于睡眠呼吸暂停患者，在不同睡眠阶段PRV测量结果与HRV分析结果相似。
