Figure 4.

An analytical pipeline for pre-processing the cardiac data. (A) Upon filtering noise and detrending the ECG data, the R-peaks are localized, and in (B), the temporal distances between the peaks are obtained. This produces the RR-peaks series data or inter-beat interval times series (IBI). (C) The temporal domain is assessed by obtaining the Poincaré plot, a shifted version of the time series one step forward along the y-axis and the current time version along the x-axis. The scatter is fitted by an ellipse, and the principal axes are examined as SD1 (variability associated with the parasympathetic system) and SD2 (variability associated with the sympathetic system). These parameters are then examined in relation to noise regimes from the empirically estimated micro-movement spikes (micro-peaks) distributions. (D) In this step, we perform frequency domain analysis using power spectral decomposition techniques and obtain the low- and high-frequency bands for examination of the sympathetic and parasympathetic regimes associated with lower and higher frequencies, respectively. A magnitude scalogram can then be used to visualize the data as frequency over time with power information (color bar representing the magnitude/power levels).