Due to the possibilities in miniaturization and wearability, photoplethysmography (PPG) has recently gained a large interest not only for heart rate measurement, but also for estimating heart rate variability, which is derived from ECG by convention. The agreement between PPG and ECG-based HRV has been assessed in several studies, but the feasibility of PPG-based HRV estimation is still largely unknown for many conditions. In this study, we assess the feasibility of HRV estimation based on finger PPG during rest, mild physical exercise and mild mental stress. In addition, we compare different variants of signal processing methods including selection of fiducial point and outlier correction. Based on five minutes synchronous recordings of PPG and ECG from 15 healthy participants during each of these three conditions, the PPG-based HRV estimation was assessed for the SDNN and RMSSD parameters, calculated based on two different fiducial points (foot point and maximum slope), with and without outlier correction. The results show that HRV estimation based on finger PPG is feasible during rest and mild mental stress, but can give large errors during mild physical exercise. A good estimation is very dependent on outlier correction and fiducial point selection, and SDNN seems to be a more robust parameter compared to RMSSD for PPG-based HRV estimation.
Both diabetes mellitus (DM) and the metabolic syndrome (MetS) are associated with autonomic neuropathy, which predisposes to cardiac events and death. Measures of heart rate variability (HRV) can be used to monitor the activity of the autonomic nervous system (ANS), and there are strong indications that HRV can be used to study the progression of ANS-related diabetes complications. This study aims to investigate differences in HRV in healthy, MetS and diabetic populations. Based on 7880 participants from the sixth health survey in Tromsø (Tromsø 6, 2007–2008), we found a significant negative association between the number of MetS components and HRV as estimated from short-term pulse wave signals (PRV). This decrease in PRV did not appear to be linear, instead it leveled off after the third component, with no significant difference in PRV between the MetS and DM populations. There was a significant negative association between HbA1c and PRV, showing a decrease in PRV occurring already within the normal HbA1c range. The MetS and DM populations are different from healthy controls with respect to PRV, indicating impaired ANS in both conditions. In the future, a study with assessment of PRV measurements in relation to prospective cardiovascular events seems justified.
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