Effects of Cardiovascular Rehabilitation on Myocardial Perfusion and Functional Exercise Capacity in Patients With Stable Coronary Artery Disease and Myocardial Ischemia

Figures

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  Fig. 1. Multisensory configuration for tissue perfusion monitoring. (A) Experimental setup during participant monitoring. (B) Placement of sensors: the NIRS sensor (1) on the thumb, the LDF sensor (2) on the index finger, and the PPG pulse oximeter sensor (3) on the middle finger. This arrangement enables simultaneous acquisition of NIRS-derived hemodynamic signals, microvascular blood Flux, arterial oxygen saturation, and perfusion index from anatomically adjacent sites

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  Fig. 2. Decomposition of total hemoglobin (THb) signal into AC and DC components. (A) Time-series plot showing the raw THb signal (green line) containing both AC and DC components, and the extracted DC component (blue line) obtained using a second-order Butterworth low-pass filter with a cutoff frequency of 0.5 Hz. The DC component represents the signal’s slowly varying baseline. (B) The isolated AC component (blue line) was extracted using a second-order Butterworth bandpass filter (0.5–5 Hz), with the red shaded area representing the area under the AC curve. Data shown for a 20-second window from a representative measurement

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  Fig. 3. Schematic of DRV calculation within a window and its distinction from a window-level slope. The THb waveform is segmented into non-overlapping windows (vertical dashed lines). Within a window, the first derivative is computed at every sample using finite differences, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{d}_{i}=\varDelta\:TH{b}_{i}∕\varDelta\:{t}_{i}$$\end{document} (colored markers), then converted to the magnitude \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:\left|{d}_{i}\right|$$\end{document} so that rising and falling portions of the cardiac waveform contribute positively and do not cancel. DRV is obtained by summarizing \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek}…

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  Fig. 4. Pipeline from acquisition to analysis for RTPI and reference comparisons.

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  Fig. 5. Temporal dynamics of all three features during the entire protocol. Time-series plot showing robust-scaled values of NIRS-derived features: pulse amplitude ratio (PAR), area under the AC curve (AUAC), and first derivative (DRV) over the full 30-minute experimental protocol

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  Fig. 6. Comparative hemodynamic responses of NIRS tissue perfusion index (RTPI-PCA), THb, and TOI during complete and partial ischemia challenges. Time-series plot showing robust-scaled values during a complete experimental protocol. The red-shaded region indicates complete ischemia induced by inflation of a 200-mmHg cuff, producing immediate and synchronized decreases in all three parameters. The blue-shaded area represents partial ischemia at a 100-mmHg cuff pressure, revealing divergent responses: RTPI (red) demonstrates immediate perfusion compromise, whereas TOI (black) initially increases due to venous congestion before ultimately declining. THb (green) shows pronounced accumulation during partial ischemia, reflecting blood pooling from obstructed venous return

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  Fig. 7. Temporal dynamics of NIRS regional tissue perfusion index (RTPI) compared with reference perfusion measurements throughout the ischemia-reperfusion protocol. Time-series plot showing robust-scaled values of RTPI derived from principal component analysis (red), photoplethysmography perfusion index (PI, green), and laser Doppler Flux (blue) over the complete 30-minute experimental protocol. All three measures demonstrate roughly synchronized responses during complete ischemia and partial ischemia periods, with concordant perfusion cessation and reactive hyperemia upon reperfusion

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  Fig. 8. Examples of LDF pulse waveform morphology observed in the dataset. (A) typical pulse contour with the systolic peak preceding the dicrotic notch, (B) atypical morphology in which a notch-like feature precedes the systolic peak

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  Fig. 9. Representative robust-scaled time-series from two sessions of a single participant under the same protocol, showing RTPI (red), PPG PI (green), and LDF Flux (blue) traces. Shaded intervals indicate cuff-inflation phases. (A) Session 1 shows minimal net change in LDF Flux during the 100-mmHg occlusion phase, while RTPI and PI show a consistent decrease. (B) Session 2 shows a pronounced decrease in LDF Flux during the 100-mmHg occlusion phase, while RTPI and PI again decrease in the same direction, illustrating greater cross-session consistency for RTPI and PI than for LDF in this participant