Dynamics of peripheral blood flow across sleep stages

Abstract

AbstractStudy ObjectivesPulse rate variability (PRV) derived from peripheral blood flow has been reported as a surrogate parameter for heart rate variability (HRV). However, there are currently no studies reporting systematic comparisons of PRV with HRV in a normal sleep state. Whether PRV can provide similar information regarding sleep stages remains unclear. Peripheral blood flow may also be modulated differently across sleep stages. Thus, we aimed to investigate blood flow dynamics and compare PRV with HRV across sleep stages to see if blood flow can provide further information about sleep stages.MethodsWe performed electrocardiography and simultaneously measured blood flow from the right index finger and ear concha of 45 healthy participants (13 women; mean age, 22.5 ± 3.4 years) during one night of sleep. Time-domain, frequency-domain, and non-linear indices of PRV/HRV, and time- and frequencydomain blood flow parameters were calculated.ResultsFinger-PRV results showed similar patterns to HRV results for most parameters. Finger-blood flow parameters in the time and frequency domains also showed information about the different sleep stages. Further, both finger- and ear-blood flow results showed 0.2–0.3 Hz oscillations that varied with sleep stages, with a significant increase in N3, suggesting a modulation (of respiration) within this frequency band.ConclusionsThese results suggest that PRV can provide as much information as HRV for different sleep stages. Furthermore, the results show that blood flow + PRV could be more advantageous than HRV alone in the assessment of the sleep state and related autonomic nervous activity.Statement of SignificanceThe research provides comprehensive information on peripheral blood flow (BF) activity across sleep stages for the first time, as the major novelty of our work. The second contribution is a systematic study comparing BF-derived pulse rate variability (PRV) with heart rate variability across sleep stages in a normal sleep state. We believe that our work makes a significant contribution to the literature because it provides comprehensive information on the potential of BF+PRV as a new biomarker for assessing the sleep state. Further, this study contributes to developing a more convenient method of assessing the sleep state in the clinical and home/work setting.