Figure 1.
Overview of the CSD-based algorithm.
Initially the PPG signal is segmented into windows (60 s or 120 s) with 50% of overlap. In the subsequent step the CSD is applied to calculate the spectrum of the windowed signals. The HR is estimated by detecting the maximum frequency peak within the cardiac frequency band. The signal is then low pass filtered and the RR is estimated by detecting the maximum frequency peak within the respiratory frequency band.
Figure 2.
Time-varying CSD of 8-min PPG signal.
Both respiratory and cardiac frequency peaks reflect RR and HR, respectively. Respiratory frequency peak is around 0.3 Hz (18 breaths/min) and cardiac frequency peak around 1.25 Hz (75 beats/min).
Figure 3.
Time-varying estimated and manually labeled reference RR and HR.
Estimated (solid blue with * markers) and manually labeled (dotted red with+markers) reference RR in (A) and HR in (B). For this subject the RMS errors estimating RR and HR are 0.25 breaths/min and 0.35 beats/min, respectively.
Figure 4.
CSD sensitivity to the kernel parameter.
CSD-based algorithm’s perfomance estimating RR is illustrated for the kernel values: ,
,
and
. The
is calculated by Silverman’s rule.
Figure 5.
CSD applied to a simulated signal.
(A) Simulated signal with 0.2 Hz modulation respiratory frequency (12 breaths/min), 1 Hz cardiac frequency (60 beats/min), and , (B) same simulated signal with some outliers randomly added, (C) and (D) the CSD of the simulated signal with and without outliers, and (E) and (F) the PSD of the simulated signal with and without outliers, respectively. CSD analysis provides a clearer and more robust against outliers respiratory frequency peak than conventional PSD.
Figure 6.
CSD applied to an in-vivo signal.
CSD and PSD performance applied to an in-vivo signal (1 min) of one infant subject: (A) reference HR (dotted red line with markers) and mean HR represented by a dotted grey line, (B) reference RR (dotted red line with
markers) and mean RR represented by a dotted grey line, (C) ECG signal, (D) capnometry, (E) PPG signal, (F) CSD and (G) PSD applied to the PPG signal. In addition, the average CSD and PSD spectrum of the database’s population is illustrated in the background on (F) and (G) respectively, where the cardiac component is represented in dark grey and the filtered signal that corresponds to respiration in light grey.
Figure 7.
Boxplot of the (A) RR and (B) HR RMS error estimated using time windows of 60 s and 120 s and tracked around extended RR (from 8 to 60 breaths/min) and HR (from 30 to 180 beats/min). quartile, median, and
quartile values are displayed as bottom, middle and top horizontal line of the boxes. Whiskers are used to represent the most extreme values within 3 times the interquartile range from the quartile. Outliers (data with values beyond the ends of the whiskers) were displayed as crosses.
Table 1.
RMS error estimating RR and HR with different methods.
Figure 8.
Bland-Altman for HR and RR estimation.
Bland-Altman plots for comparison of (A) HR and (B) RR to the reference HR and RR manually labeled by the research assistant. The bias and 95% of limits of agreement are ploted in solid lines. It showed a bias of 0.18 and limits of agreement of −1.52 to 1.91 beats/min for the estimated HR versus reference HR and a bias of −1.1 and limits of agreement of −6.52 to 4.32 breaths/min for the estimated RR versus reference RR.
Figure 9.
Scatter plot, error per subject.
Scatter plot showing the median value of estimated and reference values of (A) RR and (B) HR for each subject using 60-s time window. The respiratory and cardiac frequency peaks are detected around the extended RR and HR range. Observations with artifacts are included. The dotted line represents the optimal performance.
Figure 10.
Scatter plot, error per time window.
Scatter plot showing the estimated and reference values of (A) RR and (B) HR for each 60-s time window (represented by blue +) and for each 120-s time window (represented by black *). The respiratory and cardiac frequency peaks are detected around the extended RR and HR range. Observations with artifacts are included. The dotted line represents the optimal performance.