Shuangyan Liu1, Jing Teng2, Xianghua Qi3, Shoushui Wei1, Chengyu Liu1. 1. Institute of Biomedical Engineering, School of Control Science and Engineering, Shandong University, Jinan 250061, Shandong, China. 2. Department of Internal Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan 250011, Shandong, China. 3. Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan 250061, Shandong, China.
Abstract
BACKGROUND: 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. OBJECTIVE: 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. METHODS: 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. RESULTS: 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). CONCLUSIONS: PRV measurement could present the similar results as HRV analysis for sleep apnea patients during different sleep stages.
BACKGROUND: 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. OBJECTIVE: 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. METHODS: Seventy-five sleep apneapatients 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. RESULTS: 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). CONCLUSIONS: PRV measurement could present the similar results as HRV analysis for sleep apneapatients during different sleep stages.
Authors: Daniel Álvarez; C Ainhoa Arroyo; Julio F de Frutos; Andrea Crespo; Ana Cerezo-Hernández; Gonzalo C Gutiérrez-Tobal; Fernando Vaquerizo-Villar; Verónica Barroso-García; Fernando Moreno; Tomás Ruiz; Roberto Hornero; Félix Del Campo Journal: Entropy (Basel) Date: 2020-12-12 Impact factor: 2.524
Authors: Cai Liangming; Cai Xiaoqiong; Du Min; Miao Binxin; Lin Minfen; Zeng Zhicheng; Li Shumin; Ruan Yuxin; Hu Qiaolin; Yang Shuqin Journal: Front Public Health Date: 2021-11-16