1. Comparison between heart rate variability and pulse rate variability during different sleep stages for sleep apnea patients
- Author
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Shoushui Wei, Jing Teng, Xianghua Qi, Shuangyan Liu, and Chengyu Liu
- Subjects
Male ,medicine.medical_specialty ,Polysomnography ,Biomedical Engineering ,Biophysics ,Health Informatics ,Bioengineering ,030204 cardiovascular system & hematology ,Biomaterials ,Correlation ,Electrocardiography ,03 medical and health sciences ,Sleep Apnea Syndromes ,0302 clinical medicine ,Heart Rate ,Photoplethysmogram ,Internal medicine ,medicine ,Humans ,Heart rate variability ,Photoplethysmography ,Pulse ,Sleep Stages ,business.industry ,virus diseases ,Sleep apnea ,Middle Aged ,medicine.disease ,Sample entropy ,Cardiology ,Female ,Ecg signal ,business ,030217 neurology & neurosurgery ,Information Systems ,Pulse rate variability - 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.
- Published
- 2017