Objective. This study aimed to quantify cardiopulmonary physiological modulation in patients with hypertension (HTN) and ischaemic heart disease (IHD) using electrocardiogram (ECG) and respiration signals recorded before and after a 7 d Panchakarma-based integrative residential programme. Approach. Simultaneous 10 min ECG and respiration recordings were acquired before and after the programme. A predefined signal-quality pipeline was applied before graph construction. ECG-derived cardiac dynamics were based on normal-to-normal (NN) intervals after artefact and ectopy screening, while respiration cycles were screened for physiologically plausible breath intervals. From each acceptable recording, a clean 300 s segment was selected. NN-derived heart rate (HR) and respiration-rate series were interpolated to a common 4 Hz time base, detrended and standardised. Natural visibility graphs (VGs), weighted VGs and a two-layer multilayer VG (MLVG) were then constructed using synchronous HR-respiration interlayer coupling. Graph index complexity (GIC), average path length, assortativity and pulse-respiration quotient PRQ-derived features were analysed using paired Wilcoxon signed-rank tests with Hodges–Lehmann paired differences and false discovery rate correction. Main results. After quality control, alignment and graph-eligibility screening, paired graph-feature analysis included 20 HTN and 26 IHD subjects. The alignment procedure produced complete HR-respiration time series with negligible missing fractions. Post-program recordings showed measurable cardiopulmonary modulation. In HTN, PRQ decreased with false-discovery-rate-supported significance, while weighted GIC features showed descriptive post-program increases. In IHD, unweighted respiration-VG and MLVG GIC increased descriptively, whereas weighted and path-based metrics showed heterogeneous changes. Interlayer surrogate validation further quantified whether identity-coupled MLVG complexity exceeded shifted-coupling null networks. Significance. The proposed framework provides a reproducible ECG-respiration network-physiology workflow combining NN-based quality control, respiration-cycle screening, common-time-base alignment, unimodal and multilayer VG modelling, PRQ analysis and surrogate validation. The findings support objective quantification of post-program cardiopulmonary modulation while avoiding causal attribution to Panchakarma alone.