Fig 1.
Algorithm of autocorrelated wave detection with adaptive threshold (ACAT).
The algorithm detects the temporal positions of cyclic variation of heart rate (CVHR) in the beat interval time series as the cyclic and autocorrelated dips that meet four specific criteria (modified from Fig 1 in Ref. [11]).
Fig 2.
Detection of CVHR from photoplethysmography (PPG) pulse interval time series by the ACAT algorithm in a representative subject (a 66-y male with a body mass index of 27.0 kg/m2 and an apnea-hypopnea index of 79.3).
Panel a: original pulse interval time series. Panel b: second-order polynomial fitting line (solid line) and the upper and lower envelopes of the fitting line (dashed lines). Panel c: the relative dip depth to the envelope width at the time. Panel d: mean morphological correlation coefficients of dip with the two preceding and two subsequent dips. Panel e: temporal positions (blue bars) of dips detected as CVHR.
Table 1.
Patients’ characteristics (n = 41).
Fig 3.
R-R interval and pulse interval time series from simultaneously recoded electrocardiogram (ECG) and PPG in a representative subject (a 66-y male with an AHI of 79.3).
Vertical blue lines show the temporal positions of CVHR.
Fig 4.
Relationships of PPG and ECG Fcv with AHI.
In all panels a-c, the plots represent individual subjects. The solid line in each panel represents the linear regression line of the data for all subjects. Horizontal and vertical dashed lines in panels a and c represent the thresholds of 15 for AHI, 11 /h for PPG Fcv, and 15 /h for ECG Fcv, respectively.
Table 2.
Correlations between pulse interval and R-R interval variability indices calculated from simultaneously recorded photoplethysmography (PPG) and electrocardiography (ECG) (n = 41).
Table 3.
Correlations of PPG pulse interval and ECG R-R interval variability indices with sleep apnea indices (n = 41).
Table 4.
PPG pulse interval and ECG R-R interval variability indices in patients grouped by AHI and the discriminant performance of the indices.
Table 5.
Classification performance of PPG and ECG Fcv between patients grouped by AHI.