Restoring Respiratory Complexity: A Fractal Approach to Post-Covid Pulmonary Rehabilitation
Abstract
Post-Covid patients often exhibit restrictive lung mechanics, impaired alveolar diffusion, and reduced respiratory complexity related to fibrosis and autonomic dysregulation. Conventional rehabilitation improves symptoms but offers limited tools for objective personalization. Nonlinear and fractal analysis may provide quantitative markers for monitoring recovery. Study Design: Single-arm prospective interventional study. This study evaluates an 8-week respiratory rehabilitation protocol based on spirometry, gas diffusion tests, and fractal monitoring on adults with post-Covid dyspneea and reduced DLCO. program consisting of: (i) diaphragmatic breathing and incentive spirometry (weeks 1–2); (ii) HRV-guided breathing and progressive effort (weeks 3–5); and (iii) resistance and fractal breathing exercises (weeks 6–8). Spirometry, DLCO, exertional SpO₂, and Higuchi fractal dimension (FD) of the respiratory signal were assessed at baseline and post-intervention. Changes were analyzed descriptively and correlated with clinical improvement. After eight weeks, FEV₁ increased by approximately 15–20%, DLCO improved by 10–15%, and mean exertional SpO₂ rose from ~90% to 96–97%. FD increased from 1.05 (low variability) to >1.25 (physiological complexity). Dyspnea decreased by about 3 VAS points. Improvements in FD paralleled spirometric recovery. Fractal-guided respiratory rehabilitation was associated with improved pulmonary function and restoration of respiratory complexity in post-Covid patients. The Higuchi FD shows promise as a quantitative digital biomarker for personalized monitoring. Controlled trials are warranted to confirm efficacy.
Fields of Study & Subjects
Chronic Obstructive Pulmonary Disease (COPD) Research
Long-Term Effects of COVID-19
Respiratory Support and Mechanisms
Publication details
- Journal / source
- Balneo and PRM Research Journal
- Publisher
- Romanian Association of Balneology
- Volume
- 17
- Issue
- Vol 17 No 1
- Publication date
- 31 March 2026